Energy demands in taekwondo athletes during combat simulation

The purpose of this study was to investigate energy system contributions and energy costs in combat situations. The sample consisted of 10 male taekwondo athletes (age: 21 +/- 6 years old; height: 176.2 +/- 5.3 cm; body mass: 67.2 +/- 8.9 kg) who compete at the national or international level. To estimate the energy contributions, and total energy cost of the fights, athletes performed a simulated competition consisting of three 2 min rounds with a 1 min recovery between each round. The combats were filmed to quantify the actual time spent fighting in each round. The contribution of the aerobic (WAER), anaerobic alactic (W-PCR), and anaerobic lactic (Wleft perpendicularLA-right perpendicular) energy systems was estimated through the measurement of oxygen consumption during the activity, the fast component of excess post-exercise oxygen consumption, and the change in blood lactate concentration in each round, respectively. The mean ratio of high intensity actions to moments of low intensity (steps and pauses) was similar to 1:7. The W-AER, W-PCR and (Wleft perpendicularLA-right perpendicular) system contributions were estimated as 120 +/- 22 kJ (66 +/- 6%), 54 +/- 21 kJ (30 +/- 6%), 8.5 kJ (4 +/- 2%), respectively. Thus, training sessions should be directed mainly to the improvement of the anaerobic alactic system (responsible by the highintensity actions), and of the aerobic system (responsible by the recovery process between high- intensity actions).

Renewable energy scenarios for South Karelia – non-industrial energy demands

Tässä diplomityössä tarkastellaan täysin uusiutuvaa energiajärjestelmää Etelä-Karjalan maakunnan alueella, mikä onkin jo tällä hetkellä Suomen uusiutuvin maakunta. Diplomityössä tarkastellaan julkisen sektorin, liikenteen ja rakennusten energian kulutusta mutta teollisuuden energiankäyttö jätetään tarkastelun ulkopuolelle. Työssä tutustutaan tämän hetken Etelä-Karjalan energiajärjestelmään ja sen perusteella tehdään referenssi-skenaario. Tulevaisuuden skenaariot tehdään vuosille 2030 ja 2050. Tulevaisuuden skenaarioissa muutos keskittyy järjestelmän sähköistymiseen ja uusiutuvien tuotantomuotojen integroimiseen järjestelmään. Sähköistyminen kasvattaa sähkönkulutusta, joka pyritään kattamaan uusiutuvilla tuotantomuodoilla, lähinnä tuuli- ja aurinkovoimalla. Liikennesektori rajataan kumipyöräliikenteeseen ja sen muutos tulee olemaan haastavin ja aikaa vievin. Muutokseen pyritään liikennepolttoaineiden tuotannolla maakunnassa sekä sähköautoilulla. Uusiutuva energiajärjestelmä tarvitsee tuotannon ja kysynnän joustoa sekä älyä järjestelmältä. Työssä tarkastellaan myös järjestelmän kustannuksia sekä työllisyysvaikutuksia.

Determinants of brain cell metabolic phenotypes and energy substrate utilization unraveled with a modeling approach.

Although all brain cells bear in principle a comparable potential in terms of energetics, in reality they exhibit different metabolic profiles. The specific biochemical characteristics explaining such disparities and their relative importance are largely unknown. Using a modeling approach, we show that modifying the kinetic parameters of pyruvate dehydrogenase and mitochondrial NADH shuttling within a realistic interval can yield a striking switch in lactate flux direction. In this context, cells having essentially an oxidative profile exhibit pronounced extracellular lactate uptake and consumption. However, they can be turned into cells with prominent aerobic glycolysis by selectively reducing the aforementioned parameters. In the case of primarily oxidative cells, we also examined the role of glycolysis and lactate transport in providing pyruvate to mitochondria in order to sustain oxidative phosphorylation. The results show that changes in lactate transport capacity and extracellular lactate concentration within the range described experimentally can sustain enhanced oxidative metabolism upon activation. Such a demonstration provides key elements to understand why certain brain cell types constitutively adopt a particular metabolic profile and how specific features can be altered under different physiological and pathological conditions in order to face evolving energy demands.

A Cellular Perspective on Brain Energy Metabolism and Functional Imaging.

The energy demands of the brain are high: they account for at least 20% of the body's energy consumption. Evolutionary studies indicate that the emergence of higher cognitive functions in humans is associated with an increased glucose utilization and expression of energy metabolism genes. Functional brain imaging techniques such as fMRI and PET, which are widely used in human neuroscience studies, detect signals that monitor energy delivery and use in register with neuronal activity. Recent technological advances in metabolic studies with cellular resolution have afforded decisive insights into the understanding of the cellular and molecular bases of the coupling between neuronal activity and energy metabolism and point at a key role of neuron-astrocyte metabolic interactions. This article reviews some of the most salient features emerging from recent studies and aims at providing an integration of brain energy metabolism across resolution scales.

Mitochondrial CB₁ receptors regulate neuronal energy metabolism

The mammalian brain is one of the organs with the highest energy demands, and mitochondria are key determinants of its functions. Here we show that the type-1 cannabinoid receptor (CB(1)) is present at the membranes of mouse neuronal mitochondria (mtCB(1)), where it directly controls cellular respiration and energy production. Through activation of mtCB(1) receptors, exogenous cannabinoids and in situ endocannabinoids decreased cyclic AMP concentration, protein kinase A activity, complex I enzymatic activity and respiration in neuronal mitochondria. In addition, intracellular CB(1) receptors and mitochondrial mechanisms contributed to endocannabinoid-dependent depolarization-induced suppression of inhibition in the hippocampus. Thus, mtCB(1) receptors directly modulate neuronal energy metabolism, revealing a new mechanism of action of G protein-coupled receptor signaling in the brain.

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.

Localization and Tracking in Energy-Constrained Networks with Dynamic Connectivity

Systems used for target localization, such as goods, individuals, or animals, commonly rely on operational means to meet the final application demands. However, what would happen if some means were powered up randomly by harvesting systems? And what if those devices not randomly powered had their duty cycles restricted? Under what conditions would such an operation be tolerable in localization services? What if the references provided by nodes in a tracking problem were distorted? Moreover, there is an underlying topic common to the previous questions regarding the transfer of conceptual models to reality in field tests: what challenges are faced upon deploying a localization network that integrates energy harvesting modules? The application scenario of the system studied is a traditional herding environment of semi domesticated reindeer (Rangifer tarandus tarandus) in northern Scandinavia. In these conditions, information on approximate locations of reindeer is as important as environmental preservation. Herders also need cost-effective devices capable of operating unattended in, sometimes, extreme weather conditions. The analyses developed are worthy not only for the specific application environment presented, but also because they may serve as an approach to performance of navigation systems in absence of reasonably accurate references like the ones of the Global Positioning System (GPS). A number of energy-harvesting solutions, like thermal and radio-frequency harvesting, do not commonly provide power beyond one milliwatt. When they do, battery buffers may be needed (as it happens with solar energy) which may raise costs and make systems more dependent on environmental temperatures. In general, given our problem, a harvesting system is needed that be capable of providing energy bursts of, at least, some milliwatts. Many works on localization problems assume that devices have certain capabilities to determine unknown locations based on range-based techniques or fingerprinting which cannot be assumed in the approach considered herein. The system presented is akin to range-free techniques, but goes to the extent of considering very low node densities: most range-free techniques are, therefore, not applicable. Animal localization, in particular, uses to be supported by accurate devices such as GPS collars which deplete batteries in, maximum, a few days. Such short-life solutions are not particularly desirable in the framework considered. In tracking, the challenge may times addressed aims at attaining high precision levels from complex reliable hardware and thorough processing techniques. One of the challenges in this Thesis is the use of equipment with just part of its facilities in permanent operation, which may yield high input noise levels in the form of distorted reference points. The solution presented integrates a kinetic harvesting module in some nodes which are expected to be a majority in the network. These modules are capable of providing power bursts of some milliwatts which suffice to meet node energy demands. The usage of harvesting modules in the aforementioned conditions makes the system less dependent on environmental temperatures as no batteries are used in nodes with harvesters--it may be also an advantage in economic terms. There is a second kind of nodes. They are battery powered (without kinetic energy harvesters), and are, therefore, dependent on temperature and battery replacements. In addition, their operation is constrained by duty cycles in order to extend node lifetime and, consequently, their autonomy. There is, in turn, a third type of nodes (hotspots) which can be static or mobile. They are also battery-powered, and are used to retrieve information from the network so that it is presented to users. The system operational chain starts at the kinetic-powered nodes broadcasting their own identifier. If an identifier is received at a battery-powered node, the latter stores it for its records. Later, as the recording node meets a hotspot, its full record of detections is transferred to the hotspot. Every detection registry comprises, at least, a node identifier and the position read from its GPS module by the battery-operated node previously to detection. The characteristics of the system presented make the aforementioned operation own certain particularities which are also studied. First, identifier transmissions are random as they depend on movements at kinetic modules--reindeer movements in our application. Not every movement suffices since it must overcome a certain energy threshold. Second, identifier transmissions may not be heard unless there is a battery-powered node in the surroundings. Third, battery-powered nodes do not poll continuously their GPS module, hence localization errors rise even more. Let's recall at this point that such behavior is tight to the aforementioned power saving policies to extend node lifetime. Last, some time is elapsed between the instant an identifier random transmission is detected and the moment the user is aware of such a detection: it takes some time to find a hotspot. Tracking is posed as a problem of a single kinetically-powered target and a population of battery-operated nodes with higher densities than before in localization. Since the latter provide their approximate positions as reference locations, the study is again focused on assessing the impact of such distorted references on performance. Unlike in localization, distance-estimation capabilities based on signal parameters are assumed in this problem. Three variants of the Kalman filter family are applied in this context: the regular Kalman filter, the alpha-beta filter, and the unscented Kalman filter. The study enclosed hereafter comprises both field tests and simulations. Field tests were used mainly to assess the challenges related to power supply and operation in extreme conditions as well as to model nodes and some aspects of their operation in the application scenario. These models are the basics of the simulations developed later. The overall system performance is analyzed according to three metrics: number of detections per kinetic node, accuracy, and latency. The links between these metrics and the operational conditions are also discussed and characterized statistically. Subsequently, such statistical characterization is used to forecast performance figures given specific operational parameters. In tracking, also studied via simulations, nonlinear relationships are found between accuracy and duty cycles and cluster sizes of battery-operated nodes. The solution presented may be more complex in terms of network structure than existing solutions based on GPS collars. However, its main gain lies on taking advantage of users' error tolerance to reduce costs and become more environmentally friendly by diminishing the potential amount of batteries that can be lost. Whether it is applicable or not depends ultimately on the conditions and requirements imposed by users' needs and operational environments, which is, as it has been explained, one of the topics of this Thesis.

A techno-economic assessment of the use of fast pyrolysis bio-oil from UK energy crops in the production of electricity and combined heat and power

This thesis investigates the cost of electricity generation using bio-oil produced by the fast pyrolysis of UK energy crops. The study covers cost from the farm to the generator’s terminals. The use of short rotation coppice willow and miscanthus as feedstocks was investigated. All costs and performance data have been taken from published papers, reports or web sites. Generation technologies are compared at scales where they have proved economic burning other fuels, rather than at a given size. A pyrolysis yield model was developed for a bubbling fluidised bed fast pyrolysis reactor from published data to predict bio-oil yields and pyrolysis plant energy demands. Generation using diesel engines, gas turbines in open and combined cycle (CCGT) operation and steam cycle plants was considered. The use of bio-oil storage to allow the pyrolysis and generation plants to operate independently of each other was investigated. The option of using diesel generators and open cycle gas turbines for combined heat and power was examined. The possible cost reductions that could be expected through learning if the technology is widely implemented were considered. It was found that none of the systems analysed would be viable without subsidy, but with the current Renewable Obligation Scheme CCGT plants in the 200 to 350 MWe range, super-critical coal fired boilers co-fired with bio-oil, and groups of diesel engine based CHP schemes supplied by a central pyrolysis plant would be viable. It was found that the cost would reduce with implementation and the planting of more energy crops but some subsidy would still be needed to make the plants viable.

Developing an enhanced model for combined heat and air infiltration energy simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. ^ Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. ^ Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building's energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. ^ In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. ^ An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.^

Sustainable Energy Production in the United States: Life Cycle Assessment of Biofuels and Bioenergy

The United States of America is making great efforts to transform the renewable and abundant biomass resources into cost-competitive, high-performance biofuels, bioproducts, and biopower. This is the key to increase domestic production of transportation fuels and renewable energy, and reduce greenhouse gas and other pollutant emissions. This dissertation focuses specifically on assessing the life cycle environmental impacts of biofuels and bioenergy produced from renewable feedstocks, such as lignocellulosic biomass, renewable oils and fats. The first part of the dissertation presents the life cycle greenhouse gas (GHG) emissions and energy demands of renewable diesel (RD) and hydroprocessed jet fuels (HRJ). The feedstocks include soybean, camelina, field pennycress, jatropha, algae, tallow and etc. Results show that RD and HRJ produced from these feedstocks reduce GHG emissions by over 50% compared to comparably performing petroleum fuels. Fossil energy requirements are also significantly reduced. The second part of this dissertation discusses the life cycle GHG emissions, energy demands and other environmental aspects of pyrolysis oil as well as pyrolysis oil derived biofuels and bioenergy. The feedstocks include waste materials such as sawmill residues, logging residues, sugarcane bagasse and corn stover, and short rotation forestry feedstocks such as hybrid poplar and willow. These LCA results show that as much as 98% GHG emission savings is possible relative to a petroleum heavy fuel oil. Life cycle GHG savings of 77 to 99% were estimated for power generation from pyrolysis oil combustion relative to fossil fuels combustion for electricity, depending on the biomass feedstock and combustion technologies used. Transportation fuels hydroprocessed from pyrolysis oil show over 60% of GHG reductions compared to petroleum gasoline and diesel. The energy required to produce pyrolysis oil and pyrolysis oil derived biofuels and bioelectricity are mainly from renewable biomass, as opposed to fossil energy. Other environmental benefits include human health, ecosystem quality and fossil resources. The third part of the dissertation addresses the direct land use change (dLUC) impact of forest based biofuels and bioenergy. An intensive harvest of aspen in Michigan is investigated to understand the GHG mitigation with biofuels and bioenergy production. The study shows that the intensive harvest of aspen in MI compared to business as usual (BAU) harvesting can produce 18.5 billion gallons of ethanol to blend with gasoline for the transport sector over the next 250 years, or 32.2 billion gallons of bio-oil by the fast pyrolysis process, which can be combusted to generate electricity or upgraded to gasoline and diesel. Intensive harvesting of these forests can result in carbon loss initially in the aspen forest, but eventually accumulates more carbon in the ecosystem, which translates to a CO2 credit from the dLUC impact. Time required for the forest-based biofuels to reach carbon neutrality is approximately 60 years. The last part of the dissertation describes the use of depolymerization model as a tool to understand the kinetic behavior of hemicellulose hydrolysis under dilute acid conditions. Experiments are carried out to measure the concentrations of xylose and xylooligomers during dilute acid hydrolysis of aspen. The experiment data are used to fine tune the parameters of the depolymerization model. The results show that the depolymerization model successfully predicts the xylose monomer profile in the reaction, however, it overestimates the concentrations of xylooligomers.

Developing an Enhanced Model for Combined Heat and Air Infiltration Energy Simulation

The need for efficient, sustainable, and planned utilization of resources is ever more critical. In the U.S. alone, buildings consume 34.8 Quadrillion (1015) BTU of energy annually at a cost of $1.4 Trillion. Of this energy 58% is utilized for heating and air conditioning. Several building energy analysis tools have been developed to assess energy demands and lifecycle energy costs in buildings. Such analyses are also essential for an efficient HVAC design that overcomes the pitfalls of an under/over-designed system. DOE-2 is among the most widely known full building energy analysis models. It also constitutes the simulation engine of other prominent software such as eQUEST, EnergyPro, PowerDOE. Therefore, it is essential that DOE-2 energy simulations be characterized by high accuracy. Infiltration is an uncontrolled process through which outside air leaks into a building. Studies have estimated infiltration to account for up to 50% of a building’s energy demand. This, considered alongside the annual cost of buildings energy consumption, reveals the costs of air infiltration. It also stresses the need that prominent building energy simulation engines accurately account for its impact. In this research the relative accuracy of current air infiltration calculation methods is evaluated against an intricate Multiphysics Hygrothermal CFD building envelope analysis. The full-scale CFD analysis is based on a meticulous representation of cracking in building envelopes and on real-life conditions. The research found that even the most advanced current infiltration methods, including in DOE-2, are at up to 96.13% relative error versus CFD analysis. An Enhanced Model for Combined Heat and Air Infiltration Simulation was developed. The model resulted in 91.6% improvement in relative accuracy over current models. It reduces error versus CFD analysis to less than 4.5% while requiring less than 1% of the time required for such a complex hygrothermal analysis. The algorithm used in our model was demonstrated to be easy to integrate into DOE-2 and other engines as a standalone method for evaluating infiltration heat loads. This will vastly increase the accuracy of such simulation engines while maintaining their speed and ease of use characteristics that make them very widely used in building design.

Assessment of resting energy expenditure in pediatric mitochondrial diseases with indirect calorimetry

Mitochondrial diseases (MD) are the most frequent inborn errors of metabolism. In affected tissues, MD can alter cellular oxygen consumption rate leading to potential decreases in whole-body resting energy expenditure (REE), but data on pediatric children are absent. We determined, using indirect calorimetry (IC), whole-body oxygen consumption (VO2), carbon dioxide production (VCO2), respiratory quotient (RQ) and REE in pediatric patients with MD and healthy controls. Another goal was to assess the accuracy of available predictive equations for REE estimation in this patient population. IC data were obtained under fasting and resting conditions in 20 MD patients and 27 age and gender-matched healthy peers. We determined the agreement between REE measured with IC and REE estimated with Schofield weight and FAO/WHO/UNU equations. Mean values of VO2, VCO2 (mL·min-1·kg-1) or RQ did not differ significantly between patients and controls (P = 0.085, P = 0.055 and P = 0.626 respectively). Accordingly, no significant differences (P = 0.086) were found for REE (kcal·day-1 kg-1) either. On the other hand, although we found no significant differences between IC-measured REE and Schofield or FAO/WHO/UNU-estimated REE, Bland-Altman analysis revealed wide limits of agreement and there were some important individual differences between IC and equation-derived REE. VO2, VCO2, RQ and REE are not significantly altered in pediatric patients with MD compared with healthy controls. The energy demands of pediatric patients with MD should be determined based on IC data in order to provide the best possible personalized nutritional management for these children.

Changes in slow and fast alpha bands in subjects submitted to different amounts of functional electrostimulation

Objective: To examine the changes in slow (8-10 Hz)and fast (10-12 Hz) alpha bands of EEG in three groups of subjects submitted to different amounts of functional electrostimulation (FES). Our hypothesis is that different amounts of electrostimulation may cause different patterns of activation in the sensorimotor cortex. In particular, we expect to see an increase in alpha power due to habituation effects. We examine the two bands comprised by alpha rhythm (i.e., slow and fast alpha), since these two sub-rhythms are related to distinct aspects: general energy demands and specific motor aspects, respectively. Methods: The sample was composed of 27 students, both sexes, aging between 25 and 40 years old. The subjects were randomly distributed in three groups: control (n = 9), G24 (n = 9) and G36 (n = 9). A FES equipment (Neuro Compact-2462) was used to stimulate the right index finger extension. Simultaneously, the electroencephalographic signal was acquired. We investigated the absolute power in slow and fast alpha bands in the sensorimotor cortex. Results: The G36 indicated a significant increasing in absolute power values in lower and higher alpha components, respectively, when compared with the control group. Particularly, in the following regions: pre-motor cortex and primary motor cortex. Discussion: FES seems to promote cortical adaptations that are similar to those observed when someone learns a procedural task. FES application in the G36 was more effective in promoting such neural changes. The lower and higher components of alpha rhythms behave differently in their topographical distribution during FES application. These results suggest a somatotopic organization in primary motor cortex which can be represented by the fast alpha component. (C) 2008 Elsevier Ireland Ltd. All rights reserved.

Avaliação energética de uma escola

Mestrado em Engenharia Química