STUDIES ON ENERGY METABOLISM IN THE HIPPOCAMPUS AFTER ISCHEMIA

The gerbil model of ischemia was used to determine the effect of carotid occlusion on energy metabolites in cellular layers of discrete regions of the hippocampus and dentate gyrus. Levels of glucose, glycogen, ATP and phosphocreatine (PCr) were unchanged after 1 minute of ischemia. However, 3 minutes of ischemia produced a dramatic decrease in net levels of all metabolites. No additional decrease was observed after 15 minutes of ischemia. Re-establishment of the blood flow for 5 minutes after a 15 minute ischemic episode returned all metabolites to pre-ischemia levels. Concentrations of glucose and glycogen were elevated in sham-operated animals as a function of the pentobarbital anesthetic employed. In other studies, elevated GABA levels (produced by inhibiting GABA-transaminase with (gamma)-vinyl-GABA (GVG)) were found to decrease the rate of utilization of the high-energy phosphate metabolites ATP and PCr in the mouse cortex. In addition, glucose and glycogen levels were increased. Thus, tonic inhibition by GABA produced decreased cellular activity. Additional experiments demonstrated the attenuation of ischemia-induced metabolite depletion in cellular layers of regions of the hippocampus, dentate gyrus and cortex after GVG administration. Under ether, 1 minute of bilateral carotid occlusion produced a dramatic decrease in metabolite levels. After GVG treatment, the decrease was blocked completely for glucose, glycogen and ATP, and partially for PCr. Therefore, GABA-transaminase inhibition produced increased levels of GABA which subsequently decreased cellular activity. The protection against ischemia may have been due to (a)decreased metabolic rate; the available energy stores were utilized at a slower rate, and (b)increased levels of energy substrates; additional supplies available to maintain viability. These data suggest that the functional state of neural tissue can determine the response to metabolic stress. ^

Interactive effects of light, nitrogen source, and carbon dioxide on energy metabolism in the diatom Thalassiosira pseudonana

Due to the ongoing effects of climate change, phytoplankton are likely to experience enhanced irradiance, more reduced nitrogen, and increased water acidity in the future ocean. Here, we used Thalassiosira pseudonana as a model organism to examine how phytoplankton adjust energy production and expenditure to cope with these multiple, interrelated environmental factors. Following acclimation to a matrix of irradiance, nitrogen source, and CO2 levels, the diatom's energy production and expenditures were quantified and incorporated into an energetic budget to predict how photosynthesis was affected by growth conditions. Increased light intensity and a shift from inline image to inline image led to increased energy generation, through higher rates of light capture at high light and greater investment in photosynthetic proteins when grown on inline image. Secondary energetic expenditures were adjusted modestly at different culture conditions, except that inline image utilization was systematically reduced by increasing pCO2. The subsequent changes in element stoichiometry, biochemical composition, and release of dissolved organic compounds may have important implications for marine biogeochemical cycles. The predicted effects of changing environmental conditions on photosynthesis, made using an energetic budget, were in good agreement with observations at low light, when energy is clearly limiting, but the energetic budget over-predicts the response to inline image at high light, which might be due to relief of energetic limitations and/or increased percentage of inactive photosystem II at high light. Taken together, our study demonstrates that energetic budgets offered significant insight into the response of phytoplankton energy metabolism to the changing environment and did a reasonable job predicting them.

Assessment of Hydrogen as suistinable clean energy

The progressive depletion of fossil fuels and their high contribution to the energy supply in this modern society forces that will be soon replaced by renewable fuels. But the dispersion and alternation of renewable energy production also undertake to reduce their costs to use as energy storage and hydrogen carrier. It is necessary to develop technologies for hydrogen production from all renewable energy storage technologies and the development of energy production from hydrogen fuel cells and cogeneration and tri generation systems. In order to propel this technological development discussed where the hydrogen plays a key role as energy storage and renewable energy, the National Centre of Hydrogen and Fuel Cell Technology Experimentation in Spain equipped with installations that enable scientific and technological design, develop, verify, certify, approve, test, measure and, more importantly, the facility ensures continuous operation for 24 hours a day, 365 days year. At the same time, the system is scalable so as to allow continuous adaptation of new technologies are developed and incorporated into the assembly to verify integration at the same time it checks the validity of their development. The transformation sector can be said to be the heart of the system, because without neglecting the other sectors, this should prove the validity of hydrogen as a carrier - energy storage are important efforts that have to do to demonstrate the suitability of fuel cells or internal combustion systems to realize the energy stored in hydrogen at prices competitive with conventional systems. The multiple roles to meet the fuel cells under different conditions of operation require to cover their operating conditions, many different sizes and applications. The fourth area focuses on integration is an essential complement within the installation. We must integrate not only the electricity produced, but also hydrogen is used and the heat generated in the process of using hydrogen energy. The energy management in its three forms: hydrogen chemical, electrical and thermal integration requires complicated and require a logic and artificial intelligence extremes to ensure maximum energy efficiency at the same time optimum utilization is achieved. Verification of the development and approval in the entire production system and, ultimately, as a demonstrator set to facilitate the simultaneous evolution of production technology, storage and distribution of hydrogen fuel cells has been assessed.

A review of the potential of renewable energy sources for the State of Jammu and Kashmir (India)

The future economic development trajectory for India is likely to result in rapid and accelerated growth in energy demand, with expected shortages. Many of its current policies and strategies are aimed at the improvement and possible maximization of energy production from the renewable sector. It is also clear that while energy-conservation and energy-efficiency can make an important contribution in the national energy strategy, renewable energies will be essential to the solution and are likely to play an increasingly important role for the growth of grid power, providing energy access, reducing consumption of fossil fuels, and helping India pursue its low carbon progressive pathway. However, most of the states in India, like the northernmost State of Jammu and Kashmir (J&K), have experienced an energy crisis over a sustained period of time. As India intends to be one of the emerging powers of the 21st century, it has to embark upon with these pressing issues in a more sustainable manner and accordingly initiate various renewable energy projects within these states. This paper will provide a broad-spectrum view about the energy situation within J&K and will highlight the current policies along with future strategies for the optimal utilization of renewable energy resources.

Potential of the renewable energy development in Jammu and Kashmir, India

The future economic growth for India is likely to result in rapid and accelerated surge in energy demand, with expected shortages in terms of supply. Many of its current policies and strategies are aimed at the improvement and possible maximization of energy production from the renewable sector. It is also clear that while energy conservation and energy efficiency can make an important contribution, renewable energies will be essential to the solution and are likely to play an increasingly important role for providing enhanced energy access, reducing consumption of fossil fuels, and helping India pursue its low-carbon progressive pathway. However, most of the states in India, like the northernmost state of Jammu and Kashmir, have experienced an energy crisis over a sustained period of time and the government both at center and state level has to embark upon with these pressing issues in a more sustainable manner and accordingly initiate various renewable energy projects within these states. This paper will provide a broad-spectrum view about the energy situation within Jammu and Kashmir and will highlight the current policies along with future strategies for the optimal utilization of renewable energy resources.

Evaluation, energy optimization, and spectrum analysis of an artificial noise technique to improve CWSN security

This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number of packets transmitted by the network and the active period of the nodes increase. Security evaluation demonstrates that these techniques are effective against eavesdropper attacks, but also optimization allows for the implementation of these approaches in low-resource networks such as Cognitive Wireless Sensor Networks. In this work, the scenario is formally modeled and the optimization according to the simulation results and the impact analysis over the frequency spectrum are presented.

Energy Management and Optimization for Video Decoders based on Functional-oriented Reconfiguration

In recent years, the increasing sophistication of embedded multimedia systems and wireless communication technologies has promoted a widespread utilization of video streaming applications. It has been reported in 2013 that youngsters, aged between 13 and 24, spend around 16.7 hours a week watching online video through social media, business websites, and video streaming sites. Video applications have already been blended into people daily life. Traditionally, video streaming research has focused on performance improvement, namely throughput increase and response time reduction. However, most mobile devices are battery-powered, a technology that grows at a much slower pace than either multimedia or hardware developments. Since battery developments cannot satisfy expanding power demand of mobile devices, research interests on video applications technology has attracted more attention to achieve energy-efficient designs. How to efficiently use the limited battery energy budget becomes a major research challenge. In addition, next generation video standards impel to diversification and personalization. Therefore, it is desirable to have mechanisms to implement energy optimizations with greater flexibility and scalability. In this context, the main goal of this dissertation is to find an energy management and optimization mechanism to reduce the energy consumption of video decoders based on the idea of functional-oriented reconfiguration. System battery life is prolonged as the result of a trade-off between energy consumption and video quality. Functional-oriented reconfiguration takes advantage of the similarities among standards to build video decoders reconnecting existing functional units. If a feedback channel from the decoder to the encoder is available, the former can signal the latter changes in either the encoding parameters or the encoding algorithms for energy-saving adaption. The proposed energy optimization and management mechanism is carried out at the decoder end. This mechanism consists of an energy-aware manager, implemented as an additional block of the reconfiguration engine, an energy estimator, integrated into the decoder, and, if available, a feedback channel connected to the encoder end. The energy-aware manager checks the battery level, selects the new decoder description and signals to build a new decoder to the reconfiguration engine. It is worth noting that the analysis of the energy consumption is fundamental for the success of the energy management and optimization mechanism. In this thesis, an energy estimation method driven by platform event monitoring is proposed. In addition, an event filter is suggested to automate the selection of the most appropriate events that affect the energy consumption. At last, a detailed study on the influence of the training data on the model accuracy is presented. The modeling methodology of the energy estimator has been evaluated on different underlying platforms, single-core and multi-core, with different characteristics of workload. All the results show a good accuracy and low on-line computation overhead. The required modifications on the reconfiguration engine to implement the energy-aware manager have been assessed under different scenarios. The results indicate a possibility to lengthen the battery lifetime of the system in two different use-cases.

Partioning of dietary energy of chickens fed maize or wheat-based diets with and without a commercial blend of phytogenic feed additives

The aim of the study was to investigate the effects of a standardized mixture of a commercial blend of phytogenic feed additives containing 5% carvacrol, 3% cinnamaldehyde, and 2% capsicum on utilization of dietary energy and performance in broiler chickens. Four experimental diets were offered to the birds from 7 to 21 d of age. These included 2 basal control diets based on either wheat or maize that contained 215 g CP/kg and 12.13 MJ/kg ME and another 2 diets using the basal control diets supplemented with the plant extracts combination at 100 mg/kg diet. Each diet was fed to 16 individually penned birds following randomization. Dietary plant extracts improved feed intake and weight gain (P < 0.05) and slightly (P < 0.1) improved feed efficiency of birds fed the maize-based diet. Supplementary plant extracts did not change dietary ME (P > 0.05) but improved (P < 0.05) dietary NE by reducing the heat increment (P < 0.05) per kilogram feed intake. Feeding phytogenics improved (P < 0.05) total carcass energy retention and the efficiency of dietary ME for carcass energy retention. The number of interactions between type of diet and supplementary phytogenic feed additive suggest that the chemical composition and the energy to protein ratio of the diet may influence the efficiency of phytogenics when fed to chickens. The experiment showed that although supplementary phytogenic additives did not affect dietary ME, they caused a significant improvement in the utilization of dietary energy for carcass energy retention but this did not always relate to growth performance.

Cognitive strategies for reducing energy consumption in wireless sensor networks

El consumo energético de las Redes de Sensores Inalámbricas (WSNs por sus siglas en inglés) es un problema histórico que ha sido abordado desde diferentes niveles y visiones, ya que no solo afecta a la propia supervivencia de la red sino que el creciente uso de dispositivos inteligentes y el nuevo paradigma del Internet de las Cosas hace que las WSNs tengan cada vez una mayor influencia en la huella energética. Debido a la tendencia al alza en el uso de estas redes se añade un nuevo problema, la saturación espectral. Las WSNs operan habitualmente en bandas sin licencia como son las bandas Industrial, Científica y Médica (ISM por sus siglas en inglés). Estas bandas se comparten con otro tipo de redes como Wi-Fi o Bluetooth cuyo uso ha crecido exponencialmente en los últimos años. Para abordar este problema aparece el paradigma de la Radio Cognitiva (CR), una tecnología que permite el acceso oportunista al espectro. La introducción de capacidades cognitivas en las WSNs no solo permite optimizar su eficiencia espectral sino que también tiene un impacto positivo en parámetros como la calidad de servicio, la seguridad o el consumo energético. Sin embargo, por otra parte, este nuevo paradigma plantea algunos retos relacionados con el consumo energético. Concretamente, el sensado del espectro, la colaboración entre los nodos (que requiere comunicación adicional) y el cambio en los parámetros de transmisión aumentan el consumo respecto a las WSN clásicas. Teniendo en cuenta que la investigación en el campo del consumo energético ha sido ampliamente abordada puesto que se trata de una de sus principales limitaciones, asumimos que las nuevas estrategias deben surgir de las nuevas capacidades añadidas por las redes cognitivas. Por otro lado, a la hora de diseñar estrategias de optimización para CWSN hay que tener muy presentes las limitaciones de recursos de estas redes en cuanto a memoria, computación y consumo energético de los nodos. En esta tesis doctoral proponemos dos estrategias de reducción de consumo energético en CWSNs basadas en tres pilares fundamentales. El primero son las capacidades cognitivas añadidas a las WSNs que proporcionan la posibilidad de adaptar los parámetros de transmisión en función del espectro disponible. La segunda es la colaboración, como característica intrínseca de las CWSNs. Finalmente, el tercer pilar de este trabajo es teoría de juegos como algoritmo de soporte a la decisión, ampliamente utilizado en WSNs debido a su simplicidad. Como primer aporte de la tesis se presenta un análisis completo de las posibilidades introducidas por la radio cognitiva en materia de reducción de consumo para WSNs. Gracias a las conclusiones extraídas de este análisis, se han planteado las hipótesis de esta tesis relacionadas con la validez de usar capacidades cognitivas como herramienta para la reducción de consumo en CWSNs. Una vez presentada las hipótesis, pasamos a desarrollar las principales contribuciones de la tesis: las dos estrategias diseñadas para reducción de consumo basadas en teoría de juegos y CR. La primera de ellas hace uso de un juego no cooperativo que se juega mediante pares de jugadores. En la segunda estrategia, aunque el juego continúa siendo no cooperativo, se añade el concepto de colaboración. Para cada una de las estrategias se presenta el modelo del juego, el análisis formal de equilibrios y óptimos y la descripción de la estrategia completa donde se incluye la interacción entre nodos. Con el propósito de probar las estrategias mediante simulación e implementación en dispositivos reales hemos desarrollado un marco de pruebas compuesto por un simulador cognitivo y un banco de pruebas formado por nodos cognitivos capaces de comunicarse en tres bandas ISM desarrollados en el B105 Lab. Este marco de pruebas constituye otra de las aportaciones de la tesis que permitirá el avance en la investigación en el área de las CWSNs. Finalmente, se presentan y discuten los resultados derivados de la prueba de las estrategias desarrolladas. La primera estrategia proporciona ahorros de energía mayores al 65% comparados con una WSN sin capacidades cognitivas y alrededor del 25% si la comparamos con una estrategia cognitiva basada en el sensado periódico del espectro para el cambio de canal de acuerdo a un nivel de ruido fijado. Este algoritmo se comporta de forma similar independientemente del nivel de ruido siempre que éste sea espacialmente uniformemente. Esta estrategia, a pesar de su sencillez, nos asegura el comportamiento óptimo en cuanto a consumo energético debido a la utilización de teoría de juegos en la fase de diseño del comportamiento de los nodos. La estrategia colaborativa presenta mejoras respecto a la anterior en términos de protección frente al ruido en escenarios de ruido más complejos donde aporta una mejora del 50% comparada con la estrategia anterior. ABSTRACT Energy consumption in Wireless Sensor Networks (WSNs) is a known historical problem that has been addressed from different areas and on many levels. But this problem should not only be approached from the point of view of their own efficiency for survival. A major portion of communication traffic has migrated to mobile networks and systems. The increased use of smart devices and the introduction of the Internet of Things (IoT) give WSNs a great influence on the carbon footprint. Thus, optimizing the energy consumption of wireless networks could reduce their environmental impact considerably. In recent years, another problem has been added to the equation: spectrum saturation. Wireless Sensor Networks usually operate in unlicensed spectrum bands such as Industrial, Scientific, and Medical (ISM) bands shared with other networks (mainly Wi-Fi and Bluetooth). To address the efficient spectrum utilization problem, Cognitive Radio (CR) has emerged as the key technology that enables opportunistic access to the spectrum. Therefore, the introduction of cognitive capabilities to WSNs allows optimizing their spectral occupation. Cognitive Wireless Sensor Networks (CWSNs) do not only increase the reliability of communications, but they also have a positive impact on parameters such as the Quality of Service (QoS), network security, or energy consumption. These new opportunities introduced by CWSNs unveil a wide field in the energy consumption research area. However, this also implies some challenges. Specifically, the spectrum sensing stage, collaboration among devices (which requires extra communication), and changes in the transmission parameters increase the total energy consumption of the network. When designing CWSN optimization strategies, the fact that WSN nodes are very limited in terms of memory, computational power, or energy consumption has to be considered. Thus, light strategies that require a low computing capacity must be found. Since the field of energy conservation in WSNs has been widely explored, we assume that new strategies could emerge from the new opportunities presented by cognitive networks. In this PhD Thesis, we present two strategies for energy consumption reduction in CWSNs supported by three main pillars. The first pillar is that cognitive capabilities added to the WSN provide the ability to change the transmission parameters according to the spectrum. The second pillar is that the ability to collaborate is a basic characteristic of CWSNs. Finally, the third pillar for this work is the game theory as a decision-making algorithm, which has been widely used in WSNs due to its lightness and simplicity that make it valid to operate in CWSNs. For the development of these strategies, a complete analysis of the possibilities is first carried out by incorporating the cognitive abilities into the network. Once this analysis has been performed, we expose the hypotheses of this thesis related to the use of cognitive capabilities as a useful tool to reduce energy consumption in CWSNs. Once the analyses are exposed, we present the main contribution of this thesis: the two designed strategies for energy consumption reduction based on game theory and cognitive capabilities. The first one is based on a non-cooperative game played between two players in a simple and selfish way. In the second strategy, the concept of collaboration is introduced. Despite the fact that the game used is also a non-cooperative game, the decisions are taken through collaboration. For each strategy, we present the modeled game, the formal analysis of equilibrium and optimum, and the complete strategy describing the interaction between nodes. In order to test the strategies through simulation and implementation in real devices, we have developed a CWSN framework composed by a CWSN simulator based on Castalia and a testbed based on CWSN nodes able to communicate in three different ISM bands. We present and discuss the results derived by the energy optimization strategies. The first strategy brings energy improvement rates of over 65% compared to WSN without cognitive techniques. It also brings energy improvement rates of over 25% compared with sensing strategies for changing channels based on a decision threshold. We have also seen that the algorithm behaves similarly even with significant variations in the level of noise while working in a uniform noise scenario. The collaborative strategy presents improvements respecting the previous strategy in terms of noise protection when the noise scheme is more complex where this strategy shows improvement rates of over 50%.

Pre-investigation of water electrolysis for flexible energy storage at large scales: the case of the Spanish power system

This report analyzes the basis of hydrogen and power integration strategies, by using water electrolysis processes as a means of flexible energy storage at large scales. It is a prospective study, where the scope is to describe the characteristics of current power systems (like the generation technologies, load curves and grid constraints), and define future scenarios of hydrogen for balancing the electrical grids, considering the efficiency, economy and easiness of operations. We focus in the "Spanish case", which is a good example for planning the transition from a power system holding large reserve capacities, high penetration of renewable energies and limited interconnections, to a more sustainable energy system being capable to optimize the volumes, the regulation modes, the utilization ratios and the impacts of the installations. Thus, we explore a novel aspect of the "hydrogen economy" which is based in the potentials of existing power systems and the properties of hydrogen as energy carrier, by considering the electricity generation and demand globally and determining the optimal size and operation of the hydrogen production processes along the country; e.g. the cost production of hydrogen becomes viable for a base-load scenario with 58 TWh/year of power surplus at 0.025 V/kWh, and large number electrolyzer plants (50 MW) running in variable mode (1-12 kA/m2)

Orchestration of energy efficiency capabilities for a sustainable network management

The energy demand for operating Information and Communication Technology (ICT) systems has been growing, implying in high operational costs and consequent increase of carbon emissions. Both in datacenters and telecom infrastructures, the networks represent a significant amount of energy spending. Given that, there is an increased demand for energy eficiency solutions, and several capabilities to save energy have been proposed. However, it is very dificult to orchestrate such energy eficiency capabilities, i.e., coordinate or combine them in the same network, ensuring a conflict-free operation and choosing the best one for a given scenario, ensuring that a capability not suited to the current bandwidth utilization will not be applied and lead to congestion or packet loss. Also, there is no way in the literature to do this taking business directives into account. In this regard, a method able to orchestrate diferent energy eficiency capabilities is proposed considering the possible combinations and conflicts among them, as well as the best option for a given bandwidth utilization and network characteristics. In the proposed method, the business policies specified in a high-level interface are refined down to the network level in order to bring highlevel directives into the operation, and a Utility Function is used to combine energy eficiency and performance requirements. A Decision Tree able to determine what to do in each scenario is deployed in a Software Defined Network environment. The proposed method was validated with diferent experiments, testing the Utility Function, checking the extra savings when combining several capabilities, the decision tree interpolation and dynamicity aspects. The orchestration proved to be valid to solve the problem of finding the best combination for a given scenario, achieving additional savings due to the combination, besides ensuring a conflict-free operation.

Sustainable Energy Plan for a Small Island Economy: St. Vincent & the Grenadines

This paper defines a sustainable energy plan to provide the basis for renewable energy initiatives that will increase energy security, reduce negative economic impacts and provide a cleaner environment. The hotel, agriculture, transportation, construction, utility, government and private sectors will play pivotal roles in achieving targets and will see significant gains. Government policies, educational campaigns and financial incentives will be required to facilitate and encourage renewable energy development and entrepreneurship. Utilization of solar energy, energy conservation measures and the use of efficient and alternative fuel vehicles by the commercial/industrial and private sectors will be crucial in meeting targets. The utility company will be charged with developing large scale renewable energy applications and with improving efficiency of the electrical system.

Program planning document highway vehicle alternative fuels utilization program (AFUP).

April 1978.

Utilization of radioisotopes in physical and biological sciences--general topics; a literature search.

At head of title: U.S. Atomic Energy Commission.

Effects of internal gain assumptions in building energy calculations /

The utilization of direct solar gains in buildings can be affected by operating profiles, such as schedules for internal gains, thermostat controls, and ventilation rates. Building energy analysis methods use various assumptions about these profiles. This paper describes the effects of typical internal gain assumptions in energy calculations. The results of this study indicate that calculations of annual heating and cooling loads are sensitive to internal gains, but in most cases are relatively insensitive to hourly variation in internal gains.