The effect of knee flexion contracture following total knee arthroplasty on the energy cost of walking.

This study evaluated the energy cost of walking (Cw) with knee flexion contractures (FC) simulated with a knee brace, in total knee arthroplasty (TKA) recipients (n=16) and normal controls (n=15), and compared it to baseline (no brace). There was no significant difference in Cw between the groups at baseline but TKA recipients walked slower (P=0.048) and with greater knee flexion in this condition (P=0.003). Simulated FC significantly increased Cw in both groups (TKA P=0.020, control P=0.002) and this occurred when FC exceeded 20° in the TKA group and 15° in the controls. Reported perceived exertion was only significantly increased by FC in the control group (control P<0.001, TKA P=0.058). Simulated knee FCs less than 20° do not increase Cw or perceived exertion in TKA recipients.

Effect of shoes' heel height on the energy cost during jogging

The purpose of this study is to examine the changes of energy cost during a high-heeled continuous jogging.Thirteen healthy female volunteers jointed in this study with heel height of the shoes varied from 1, 4.5 and 7 cm, respectively. Each subjects jogged on the treadmill with K4b2 portable gas analysis system. The results of this study showed that ventilnation, relative oxygen consumption and energy expenditure increased with the increase of heel height and these values shows significantly larger when the heel height reached to 7 cm. Present study suggest that wearing high heel shoes jogging could directly increase energy consumption, causing neuromuscular fatigue.

Sustainable building envelope design by considering energy cost and occupant satisfaction

The built environment is a major contributor to the world’s carbon dioxide emissions, with a considerable amount of energy being consumed in buildings due to heating, ventilation and air-conditioning, space illumination, use of electrical appliances, etc., to facilitate various anthropogenic activities. The development of sustainable buildings seeks to ameliorate this situation mainly by reducing energy consumption. Sustainable building design, however, is a complicated process involving a large number of design variables, each with a range of feasible values. There are also multiple, often conflicting, objectives involved such as the life cycle costs and occupant satisfaction. One approach to dealing with this is through the use of optimization models. In this paper, a new multi-objective optimization model is developed for sustainable building design by considering the design objectives of cost and energy consumption minimization and occupant comfort level maximization. In a case study demonstration, it is shown that the model can derive a set of suitable design solutions in terms of life cycle cost, energy consumption and indoor environmental quality so as to help the client and design team gain a better understanding of the design space and trade-off patterns between different design objectives. The model can very useful in the conceptual design stages to determine appropriate operational settings to achieve the optimal building performance in terms of minimizing energy consumption and maximizing occupant comfort level.

Running behavior and its energy cost in mice selectively bred for high voluntary locomotor activity

Locomotion is central to behavior and intrinsic to many fitnesscritical activities (e.g., migration, foraging), and it competes with other life-history components for energy. However, detailed analyses of how changes in locomotor activity and running behavior affect energy budgets are scarce. We quantified these effects in four replicate lines of house mice that have been selectively bred for high voluntary wheel running (S lines) and in their four nonselected control lines (C lines). We monitored wheel speeds and oxygen consumption for 24-48 h to determine daily energy expenditure (DEE), resting metabolic rate (RMR), locomotor costs, and running behavior (bout characteristics). Daily running distances increased roughly 50%-90% in S lines in response to selection. After we controlled for body mass effects, selection resulted in a 23% increase in DEE in males and a 6% increase in females. Total activity costs (DEE - RMR) accounted for 50%-60% of DEE in both S and C lines and were 29% higher in S males and 5% higher in S females compared with their C counterparts. Energetic costs of increased daily running distances differed between sexes because S females evolved higher running distances by running faster with little change in time spent running, while S males also spent 40% more time running than C males. This increase in time spent running impinged on high energy costs because the majority of running costs stemmed from postural costs (the difference between RMR and the zero-speed intercept of the speed vs. metabolic rate relationship). No statistical differences in these traits were detected between S and C females, suggesting that large changes in locomotor behavior do not necessarily effect overall energy budgets. Running behavior also differed between sexes: within S lines, males ran with more but shorter bouts than females. Our results indicate that selection effects on energy budgets can differ dramatically between sexes and that energetic constraints in S males might partly explain the apparent selection limit for wheel running observed for over 15 generations. © 2009 by The University of Chicago. All rights reserved.

Association between energy cost of walking, muscle activation, and biomechanical parameters in older female fallers and non-fallers

Objective: To determine the nervous activation, muscle strength, and biomechanical parameters that influence the cost of walking in older fallers and non-fallers. Methods: Maximal voluntary isokinetic torque was measured for the hip, knee and ankle of older women. Oxygen consumption was measured at rest and during 8 min of walking at self-selected speed. An additional minute of walking was performed to collect kinematic variables and the electromyographic signal of trunk, hip, knee, and ankle muscles, which was analyzed by the linear envelope. Cost of walking was calculated by subtracting resting body mass-normalized oxygen consumption from walking body mass-normalized oxygen consumption. Stride time and length, and ankle and hip range of motion were calculated from kinematic data. Findings: Older adult fallers had 28% lower knee extensor strength (p = 0.02), 47% lower internal oblique activation at heel contact (p = 0.03), and higher coactivation between tibialis anterior and gastrocnemius lateralis in each of the gait phases (p < 0.05). For fallers, a higher activation of gluteus maximus was associated with a higher cost of walking (r = 0.55, p < 0.05 and r = 0.71, p < 0.01, before and after heel contact, respectively). For non-fallers, an association between cost of walking and age (r = 0.60, p = 0.01) and cost of walking and thigh muscle coactivation (r = 0.53, p = 0.01) existed. Interpretation: This study demonstrated that there may be links between lower-extremity muscle weakness, muscle activation patterns, altered gait, and increased cost of walking in older fallers. © 2013 Elsevier Ltd. All rights reserved.

Excess body weight and gait influence energy cost of walking in older adults

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Pareto Frontier for the time-energy cost vector to an Earth-Moon transfer orbit using the patched-conic approximation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Energy cost and the Illinois Commerce Commission : some selected observations /

Caption title.

Lighting efficiency for better energy cost control : guidelines for lighting standards and low cost strategies for efficient use of lighting in Illinois state buildings /

"ILENR/BE-86-01."--Cover.

A fuzzy levelised energy cost method for renewable energy technology assessment

Renewable energy project development is highly complex and success is by no means guaranteed. Decisions are often made with approximate or uncertain information yet the current methods employed by decision-makers do not necessarily accommodate this. Levelised energy costs (LEC) are one such commonly applied measure utilised within the energy industry to assess the viability of potential projects and inform policy. The research proposes a method for achieving this by enhancing the traditional discounting LEC measure with fuzzy set theory. Furthermore, the research develops the fuzzy LEC (F-LEC) methodology to incorporate the cost of financing a project from debt and equity sources. Applied to an example bioenergy project, the research demonstrates the benefit of incorporating fuzziness for project viability, optimal capital structure and key variable sensitivity analysis decision-making. The proposed method contributes by incorporating uncertain and approximate information to the widely utilised LEC measure and by being applicable to a wide range of energy project viability decisions. © 2013 Elsevier Ltd. All rights reserved.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.

Management of public water supply to reduce energy cost and improve wind power uptake

This paper presents a study on the implementation of Real-Time Pricing (RTP) based Demand Side Management (DSM) of water pumping at a clean water pumping station in Northern Ireland, with the intention of minimising electricity costs and maximising the usage of electricity from wind generation. A Genetic Algorithm (GA) was used to create pumping schedules based on system constraints and electricity tariff scenarios. Implementation of this method would allow the water network operator to make significant savings on electricity costs while also helping to mitigate the variability of wind generation.