Anaerobic energy expenditure and mechanical efficiency during exhaustive leg press exercise

[EN] Information about anaerobic energy production and mechanical efficiency that occurs over time during short-lasting maximal exercise is scarce and controversial. Bilateral leg press is an interesting muscle contraction model to estimate anaerobic energy production and mechanical efficiency during maximal exercise because it largely differs from the models used until now. This study examined the changes in muscle metabolite concentration and power output production during the first and the second half of a set of 10 repetitions to failure (10RM) of bilateral leg press exercise. On two separate days, muscle biopsies were obtained from vastus lateralis prior and immediately after a set of 5 or a set of 10 repetitions. During the second set of 5 repetitions, mean power production decreased by 19% and the average ATP utilisation accounted for by phosphagen decreased from 54% to 19%, whereas ATP utilisation from anaerobic glycolysis increased from 46 to 81%. Changes in contraction time and power output were correlated to the changes in muscle Phosphocreatine (PCr; r = -0.76; P<0.01) and lactate (r = -0.91; P<0.01), respectively, and were accompanied by parallel decreases (P<0.01-0.05) in muscle energy charge (0.6%), muscle ATP/ADP (8%) and ATP/AMP (19%) ratios, as well as by increases in ADP content (7%). The estimated average rate of ATP utilisation from anaerobic sources during the final 5 repetitions fell to 83% whereas total anaerobic ATP production increased by 9% due to a 30% longer average duration of exercise (18.4 +/- 4.0 vs 14.2 +/- 2.1 s). These data indicate that during a set of 10RM of bilateral leg press exercise there is a decrease in power output which is associated with a decrease in the contribution of PCr and/or an increase in muscle lactate. The higher energy cost per repetition during the second 5 repetitions is suggestive of decreased mechanical efficiency.

Energy requirements in pressure irrigation systems

Modernization of irrigation schemes, generally understood as transformation of surface irrigation systems into pressure –sprinkler and trickle- irrigation systems, aims at, among others, improving irrigation efficiency and reduction of operation and maintenance efforts made by the irrigators. However, pressure irrigation systems, in contrast, carry a serious energy cost. Energy requirements depend on decisions taken on management strategies during the operation phase, which are conditioned by previous decisions taken on the design project of the different elements which compose the irrigation system. Most of the countries where irrigation activity is significant bear in mind that modernization irrigation must play a key role in the agricultural infrastructure policies. The objective of this study is to characterize and estimate the mean and variation of the energy consumed by common types of irrigation systems and their management possibilities. The work includes all processes involved from the diversion of water into irrigation specific infrastructure to water discharge by the emitters installed on the crop fields. Simulation taking into account all elements comprising the irrigation system has been used to estimate the energy requirements of typical irrigation systems of several crop production systems. It has been applied to extensive and intensive crop systems, such us extensive winter crops, summer crops and olive trees, fruit trees and vineyards and intensive horticulture in greenhouses. The simulation of various types of irrigation systems and management strategies, in the framework imposed by particular cropping systems, would help to develop criteria for improving the energy balance in relation to the irrigation water supply productivity.

Leveraging heterogeneity for energy minimization in data centers

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

Control motion approach of a lower limb orthosis to reduce energy consumption

By analysing the dynamic principles of the human gait, an economic gait‐control analysis is performed, and passive elements are included to increase the energy efficiency in the motion control of active orthoses. Traditional orthoses use position patterns from the clinical gait analyses (CGAs) of healthy people, which are then de‐normalized and adjusted to each user. These orthoses maintain a very rigid gait, and their energy cosT is very high, reducing the autonomy of the user. First, to take advantage of the inherent dynamics of the legs, a state machine pattern with different gains in eachstate is applied to reduce the actuator energy consumption. Next, different passive elements, such as springs and brakes in the joints, are analysed to further reduce energy consumption. After an off‐line parameter optimization and a heuristic improvement with genetic algorithms, a reduction in energy consumption of 16.8% is obtained by applying a state machine control pattern, and a reduction of 18.9% is obtained by using passive elements. Finally, by combining both strategies, a more natural gait is obtained, and energy consumption is reduced by 24.6%compared with a pure CGA pattern.

Vehicle to vehicle energy exchange in smart grid applications

This paper presents a novel vehicle to vehicle energy exchange market (V2VEE) between electric vehicles (EVs) for decreasing the energy cost to be paid by some users whose EVs must be recharged during the day to fulfil their daily scheduled trips and also reducing the impact of charging on the electric grid. EVs with excess of energy in their batteries can transfer this energy among other EVs which need charge during their daily trips. These second type of owners can buy the energy directly to the electric grid or they can buy the energy from other EV at lower price. An aggregator is responsible for collecting all information among vehicles located in the same area at the same time and make possible this energy transfer.

The investigation of energy efficiency measures in the traditional buildings in Oporto World Heritage Site

Background The improvement of energy efficiency in buildings is widely promoted as a measure to mitigate climate change through the reduction of CO2 emissions. Thermal regulations worldwide promote it, for both new and existing buildings. Among the existing stock, traditional and historic buildings pose the additional challenge of heritage conservation. Their energy efficiency upgrade raises the risk of provoking negative impacts on their significance. Aims and Methodology This research used an approach based on impact assessment methodologies, defining an inital baseline scenario for both heritage and energy, from which the appropriate improvement solutions were identified and assessed. The measures were dynamically simulated and the results for energy, CO2, cost and comfort compared with the initial scenario, and then being further assessed for their heritage impact to eventually determine the most feasible solutions. To test this method, ten case studies, representative of the identified typological variants, were selected among Oporto’s traditional buildings located in the World Heritage Site. Findings and Conclusions The fieldwork data revealed that the energy consumption of these dwellings was below the European average. Additionally, the households expressed that their home comfort sensation was overall positive. The simulations showed that the introduction of insulation and solar thermal panels were ineffective on these cases in terms of energy, cost and comfort. At the same time, these measures pose a great risk to the buildings heritage value. The most efficient solutions were obtained from behavioural changes and DHW retrofit. The study reinforced the idea that traditional buildings performed better than expected and can be retrofitted and updated at a low-cost and with passive solutions. The use of insulation and solar panels should be disregarded.

The modelling of energy efficient drying for DSM (BL)

This thesis investigates the modelling of drying processes for the promotion of market-led Demand Side Management (DSM) as applied to the UK Public Electricity Suppliers. A review of DSM in the electricity supply industry is provided, together with a discussion of the relevant drivers supporting market-led DSM and energy services (ES). The potential opportunities for ES in a fully deregulated energy market are outlined. It is suggested that targeted industrial sector energy efficiency schemes offer significant opportunity for long term customer and supplier benefit. On a process level, industrial drying is highlighted as offering significant scope for the application of energy services. Drying is an energy-intensive process used widely throughout industry. The results of an energy survey suggest that 17.7 per cent of total UK industrial energy use derives from drying processes. Comparison with published work indicates that energy use for drying shows an increasing trend against a background of reducing overall industrial energy use. Airless drying is highlighted as offering potential energy saving and production benefits to industry. To this end, a comprehensive review of the novel airless drying technology and its background theory is made. Advantages and disadvantages of airless operation are defined and the limited market penetration of airless drying is identified, as are the key opportunities for energy saving. Limited literature has been found which details the modelling of energy use for airless drying. A review of drying theory and previous modelling work is made in an attempt to model energy consumption for drying processes. The history of drying models is presented as well as a discussion of the different approaches taken and their relative merits. The viability of deriving energy use from empirical drying data is examined. Adaptive neuro fuzzy inference systems (ANFIS) are successfully applied to the modelling of drying rates for 3 drying technologies, namely convective air, heat pump and airless drying. The ANFIS systems are then integrated into a novel energy services model for the prediction of relative drying times, energy cost and atmospheric carbon dioxide emission levels. The author believes that this work constitutes the first to use fuzzy systems for the modelling of drying performance as an energy services approach to DSM. To gain an insight into the 'real world' use of energy for drying, this thesis presents a unique first-order energy audit of every ceramic sanitaryware manufacturing site in the UK. Previously unknown patterns of energy use are highlighted. Supplementary comments on the timing and use of drying systems are also made. The limitations of such large scope energy surveys are discussed.

Energy efficient measures to reduce electrical energy use in commercial buildings in New York City

GEA Consulting Engineers, acting as the design engineers, was hired by the owner, East Village 207 Residential LLC2 for energy modeling for compliance with LEED NC V3 -- This report details the results of the energy simulation done with the 100% construction documents -- This report only refers to entities within the LEED3 project boundary -- The project consists of a new eight-story high-end residential condominium building with 81 units, as shown in illustration 1, and approximately 117,905 GSF, equivalent to 10,953.73 m2, is located at 211 E 13th Street in New York, NY -- The residential portion of the building will function 24-7 -- The design goal is to utilize energy efficient measures to reduce electrical energy use and aims to achieve LEED certification -- LEED EA Credit 14 requires a building to demonstrate a percentage improvement in the proposed building performance compared with the baseline building -- The Credit rewards 1 point for achieving 12% reduction in energy costs -- Additionally, the Credit rewards another point for each subsequent reduction of 2% in the building’s energy cost

Predicting the metabolic energy costs of bipedalism using evolutionary robotics

To understand the evolution of bipedalism among the homnoids in an ecological context we need to be able to estimate theenerrgetic cost of locomotion in fossil forms. Ideally such an estimate would be based entirely on morphology since, except for the rare instances where footprints are preserved, this is hte only primary source of evidence available. In this paper we use evolutionary robotics techniques (genetic algoritms, pattern generators and mechanical modeling) to produce a biomimentic simulation of bipedalism based on human body dimensions. The mechnaical simulation is a seven-segment, two-dimensional model with motive force provided by tension generators representing the major muscle groups acting around the lower-limb joints. Metabolic energy costs are calculated from the muscel model, and bipedal gait is generated using a finite-state pattern generator whose parameters are produced using a genetic algorithm with locomotor economy (maximum distance for a fixed energy cost) as the fitness criterion. The model is validated by comparing the values it generates with those for modern humans. The result (maximum efficiency of 200 J m-1) is within 15% of the experimentally derived value, which is very encouraging and suggests that this is a useful analytic technique for investigating the locomotor behaviour of fossil forms. Initial work suggests that in the future this technique could be used to estimate other locomotor parameters such as top speed. In addition, the animations produced by this technique are qualitatively very convincing, which suggests that this may also be a useful technique for visualizing bipedal locomotion.

Activity and energy expenditure in older people playing active video games

OBJECTIVES: To quantify energy expenditure in older adults playing interactive video games while standing and seated, and secondarily to determine whether participants' balance status influenced the energy cost associated with active video game play. DESIGN: Cross-sectional study. SETTING: University research center. PARTICIPANTS: Community-dwelling adults (N=19) aged 70.7±6.4 years. INTERVENTION: Participants played 9 active video games, each for 5 minutes, in random order. Two games (boxing and bowling) were played in both seated and standing positions. MAIN OUTCOME MEASURES: Energy expenditure was assessed using indirect calorimetry while at rest and during game play. Energy expenditure was expressed in kilojoules per minute and metabolic equivalents (METs). Balance was assessed using the mini-BESTest, the Activities-specific Balance Confidence Scale, and the Timed Up and Go (TUG). RESULTS: Mean ± SD energy expenditure was significantly greater for all game conditions compared with rest (all P≤.01) and ranged from 1.46±.41 METs to 2.97±1.16 METs. There was no significant difference in energy expenditure, activity counts, or perceived exertion between equivalent games played while standing and seated. No significant correlations were observed between energy expenditure or activity counts and balance status. CONCLUSIONS: Active video games provide light-intensity exercise in community-dwelling older people, whether played while seated or standing. People who are unable to stand may derive equivalent benefits from active video games played while seated. Further research is required to determine whether sustained use of active video games alters physical activity levels in community settings for this population.

An energy-aware QoS enhanced method for service computing across clouds and data centers

QoS plays a key role in evaluating a service or a service composition plan across clouds and data centers. Currently, the energy cost of a service's execution is not covered by the QoS framework, and a service's price is often fixed during its execution. However, energy consumption has a great contribution in determining the price of a cloud service. As a result, it is not reasonable if the price of a cloud service is calculated with a fixed energy consumption value, if part of a service's energy consumption could be saved during its execution. Taking advantage of the dynamic energy-Aware optimal technique, a QoS enhanced method for service computing is proposed, in this paper, through virtual machine (VM) scheduling. Technically, two typical QoS metrics, i.e., the price and the execution time are taken into consideration in our method. Moreover, our method consists of two dynamic optimal phases. The first optimal phase aims at dynamically benefiting a user with discount price by transparently migrating his or her task execution from a VM located at a server with high energy consumption to a low one. The second optimal phase aims at shortening task's execution time, through transparently migrating a task execution from a VM to another one located at a server with higher performance. Experimental evaluation upon large scale service computing across clouds demonstrates the validity of our method.

An energy-aware virtual machine scheduling method for service QoS enhancement in clouds over big data

Because of the strong demands of physical resources of big data, it is an effective and efficient way to store and process big data in clouds, as cloud computing allows on-demand resource provisioning. With the increasing requirements for the resources provisioned by cloud platforms, the Quality of Service (QoS) of cloud services for big data management is becoming significantly important. Big data has the character of sparseness, which leads to frequent data accessing and processing, and thereby causes huge amount of energy consumption. Energy cost plays a key role in determining the price of a service and should be treated as a first-class citizen as other QoS metrics, because energy saving services can achieve cheaper service prices and environmentally friendly solutions. However, it is still a challenge to efficiently schedule Virtual Machines (VMs) for service QoS enhancement in an energy-aware manner. In this paper, we propose an energy-aware dynamic VM scheduling method for QoS enhancement in clouds over big data to address the above challenge. Specifically, the method consists of two main VM migration phases where computation tasks are migrated to servers with lower energy consumption or higher performance to reduce service prices and execution time. Extensive experimental evaluation demonstrates the effectiveness and efficiency of our method.

On the feasibility of using servo-mechanisms in wireless multimedia sensor network deployments

This paper considers the use of servo-mechanisms as part of a tightly integrated homogeneous Wireless Multi- media Sensor Network (WMSN). We describe the design of our second generation WMSN node platform, which has increased image resolution, in-built audio sensors, PIR sensors, and servo- mechanisms. These devices have a wide disparity in their energy consumption and in the information quality they return. As a result, we propose a framework that establishes a hierarchy of devices (sensors and actuators) within the node and uses frequent sampling of cheaper devices to trigger the activation of more energy-hungry devices. Within this framework, we consider the suitability of servos for WMSNs by examining the functional characteristics and by measuring the energy consumption of 2 analog and 2 digital servos, in order to determine their impact on overall node energy cost. We also implement a simple version of our hierarchical sampling framework to evaluate the energy consumption of servos relative to other node components. The evaluation results show that: (1) the energy consumption of servos is small relative to audio/image signal processing energy cost in WMSN nodes; (2) digital servos do not necessarily consume as much energy as is currently believed; and (3) the energy cost per degree panning is lower for larger panning angles.

Smart grid-demand side response model to mitigate prices and peak impact on the electrical system

The aims of this project is to develop demand side response model which assists electricity consumers who are exposed to the market price through aggregator to manage the air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimise the energy cost caused by the air-conditioning load considering the electricity market price and network overload. The model is tested with selected characteristics of the room, Queensland electricity market data from Australian Energy Market Operator and data from the Bureau of Statistics on temperatures in Brisbane, during weekdays on hot days from 2011 - 2012.

Demand-side response model to avoid spike of electricity price

The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.