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Purpose We compared running economy (RE) and 3-km time-trial (TT) variables of runners wearing Nike Vaporfly 4% (VP4), Saucony Endorphin lightweight racing flats (FLAT), and their habitual running (OWN) footwear. Methods Eighteen male recreational runners (mean +/− SD, age: 33.5 ± 11.9 year (mean ± standard deviation), peak oxygen uptake (VO2peak): 55.8 ± 4.4 mL/kg·min) attended 4 sessions approximately 7 days apart. The first session consisted of a VO2peak test to inform subsequent RE speeds set at 60%, 70%, and 80% of the speed eliciting VO2peak. In subsequent sessions, treadmill RE and 3-km TTs were assessed in the 3 footwear conditions in a randomized, counterbalanced crossover design. Results Oxygen consumption (mL/kg·min) was lesser in VP4 (from 4.3% to 4.4%, p ≤ 0.002) and FLAT (from 2.7% to 3.4%, p ≤ 0.092) vs. OWN across intensities, with a non-significant difference between VP4 and FLAT (1.0%–1.7%, p ≥ 0.292). Findings related to energy cost (W/kg) and energetics cost of transport (J/kg·m) were comparable. VP4 3-km TT performance (11:07.6 ± 0:56.6 mm:ss) was enhanced vs. OWN by 16.6 s (2.4%, p = 0.005) and vs. FLAT by 13.0 s (1.8%, p = 0.032). 3-km times between OWN and FLAT (0.5%, p = 0.747) were similar. Most runners (n = 11, 61%) ran their fastest TT in VP4. Conclusions Overall, VP4 improved laboratory-based RE measures in male recreational runners at relative speeds compared to OWN, but the RE improvements in VP4 were not significant vs. FLAT. More runners exhibited better treadmill TT performances in VP4 (61%) vs. FLAT (22%) and OWN (17%). The variability in RE (–10.3% to 13.3%) and TT (–4.7% to 9.3%) improvements suggests that responses to different types of shoes are individualized and warrant further investigation.

With the increasing supply of sour crude oil and rising demand of low-sulfur fuel oil products, desulfurization becomes important in refineries, leading to notable energy cost for desulfurization solvent regeneration. This paper presents the integration of desulfurization solvent network and develops a systematic targeting and design method in order to improve the overall solvent utilization. First, the desulfurization solvent sink/source and desulfurization solvent network are defined referring to the characteristics of desulfurization units. Next, a novel problem table method is developed to identify the minimum fresh solvent consumption and design the desulfurization solvent network simultaneously. A case study is conducted to provide quantitative insights in designing desulfurization solvent network and saving fresh desulfurization solvent. Such integration reduces the fresh solvent consumption by 25% and has a good practicability.

BACKGROUND: Energy cost of walking (ECw) is an important determinant of walking ability in people with a lower-limb amputation. Large variety in estimates of ECw has been reported, likely because of the heterogeneity of this population in terms of level and cause of amputation and walking speed. OBJECTIVES: To assess (1) differences in ECw between people with and without a lower-limb amputation, and between people with different levels and causes of amputation, and (2) the association between ECw and walking speed. STUDY DESIGN: Systematic review and meta-analysis. METHODS: We included studies that compared ECw in people with and without a lower-limb amputation. A meta-analysis was done to compare ECw between both groups, and between different levels and causes of amputation. A second analysis investigated the association between self-selected walking speed and ECw in people with an amputation. RESULTS: Out of 526 identified articles, 25 were included in the meta-analysis and an additional 30 in the walking speed analysis. Overall, people with a lower-limb amputation have significantly higher ECw compared to people without an amputation. People with vascular transfemoral amputations showed the greatest difference (+102%) in ECw. The smallest difference (+12%) was found for people with nonvascular transtibial amputations. Slower self-selected walking speed was associated with substantial increases in ECw. CONCLUSION: This study provides general estimates on the ECw in people with a lower-limb amputation, quantifying the differences as a function of level and cause of amputation, as well as the relationship with walking speed.

Given the background of electricity market, the electricity consumption optimization can reduce consumers’ energy cost, and also help to reduce the peak load and improve the accommodation level of clean energy. Aiming at solving the problem of consumers’ insufficient management of their own electricity consumption, a multi-objective optimization model of electricity consumption is proposed considering the correlation of equipment electricity consumption. First, the cross-correlation coefficient is adopted to identify the consumption correlation among various electricity equipment based on the historical load data of consumers, and the significance of the consumption correlation is analyzed by silhouette index. Next, a multi-objective optimization model is constructed and the optimal electricity consumption strategy is obtained to maximize the consumer-side economy and comfort benefits. Finally, the results of case studies on a Zhejiang stir-fried tea enterprise in China show that the proposed model is feasible and effective.

Target tracking is one of the most common applications in mobile sensor networks. However, since mobile sensors are often battery powered, determining how to schedule the movements of mobile sensors to reduce energy consumption remains an important and challenging task. In this paper, a partition-based target tracking framework with a modified continuous ant colony optimization approach is proposed to achieve flexible and energy-efficient tracking. In the proposed framework, the sensing area is divided into subregions, and the scopes of movement of the mobile sensors are limited to the corresponding subregions to balance the energy consumption among sensors. A modified continuous ant colony optimization method is proposed to adaptively adjust the parameters of the tracking system (e.g., the sensing radius of mobile sensors) in each time instant, minimize the energy cost of the tracking system and yield a satisfactory tracking accuracy. The simulation results indicate that the proposed framework offers promising performance.

Summary We simulate pathways for achieving up to 100% renewable energy (RE) electric power systems for the contiguous United States. Under base conditions, the least-cost buildout has RE penetration growing up to 57% in 2050. Relative to this base scenario, average CO2 abatement costs of achieving 80%, 90%, 95%, and 100% RE are $25, $33, $40, and $61/ton, respectively, with system costs growing from $30 to $36/MWh at 95% (achieved in 2040) and $39/MWh at 100%. Incremental abatement costs from 99% to 100% RE reach $930/ton, driven primarily by the need for firm RE capacity. In addition to the base conditions, we also examined 22 alternative conditions for a buildout of up to 100%. These sensitivities capture different technology trajectories, compliance requirements, requirement timing, electrification, and transmission availability. Nonlinear marginal costs for the last few percent approaching 100% RE were found for all sensitivities, which might motivate alternative nonelectric-sector abatement opportunities.

Background Physical activity becomes increasingly fragmented with age, which may be an early marker of functional decline. Energetic cost of walking and energy capacity are also linked with functional decline, but their associations with activity fragmentation, and the potential modifying roles of total daily physical activity and age, remains unclear. Method A total of 493 participants (50–93 years) from the Baltimore Longitudinal Study of Aging underwent measures of energetic cost of usual-paced overground walking (mL/kg/m), energy demand during slow walking (mL/kg/min) on a treadmill (0.67 m/s, 0% grade), and average peak walking energy expenditure (mL/kg/min) during a fast-paced 400-m walk. A ratio of slow walking to peak walking energy expenditure (“cost-to-capacity ratio”) was calculated. Activity fragmentation was quantified as an active-to-sedentary transition probability (ASTP) using Actiheart accelerometer data. Linear regression models with ASTP as the dependent variable were used to test whether poorer energy cost and capacity were associated with higher ASTP and whether the associations differed by daily physical activity or age. Results After adjusting for demographics, body composition, comorbidities, and daily physical activity, every 10% higher cost-to-capacity ratio was associated with 0.4% greater ASTP (p = .005). This association was primarily driven by the least active participants (pinteraction = .023). Peak walking energy expenditure was only associated with ASTP among participants aged ≥70 years. Conclusions Higher cost-to-capacity ratio and lower energy capacity may manifest as more fragmented physical activity, especially among those less active or aged ≥70 years. Future studies should examine whether an increasing cost-to-capacity ratio or declining energy capacity predicts subsequent activity fragmentation.

According to several recent studies, energy is seen as a commodity, due to the fact that energy sector markets are more like commodity markets. Essentially, it serves as an enabler of social and economic development and so cannot be neglected. This study, therefore, estimated the impact of cooking energy cost on energy demand in Nigeria using the ARDL model and quarterly data spanning from 1990-2018. The result from the study showed that in the long-run both liquefied petroleum gas (LPG) price and kerosene price has a negative impact on energy demand. In the short-run, the result remained the same for kerosene while it reversed for LPG. The study, therefore, recommended that government should enact policies that will moderate or minimize the cost of cooking energy and enhance the removal of all forms of barriers in making cooking energy affordable to users in the country.

Cerebral palsy (CP) causes walking disability in children which could lead to profound changes in body composition. This study assessed relationship between body composition and each of dynamic muscle strength, mobility and energy cost of ambulation (ECA) among children with CP. The cross sectional survey, recruited participants from a secondary and a tertiary hospitals in Kano. Body composition was assessed with BMI for age charts and skin fold calipher. Dynamic muscle strength, balance and ECA were assessed with step-up test, time-up-and-go test and physiological cost index respectively. Data was analysed with Pearson Product Moment Correlation and unpaired t test at alpha level of P0.05). It was concluded that about two-thirds of the children with CP in the study are underweight and having low percent body fat. Body composition may not have significant influence on the muscle strength, stability and the energy expended during walking function. Paediatricians and physiotherapists should encourage caregivers of children with CP to feed them with balanced diet in order to avoid diseases associated with malnutrition.

Every women’s and men’s world records from 5 km to the marathon has been broken since the introduction of carbon fibre plate (CFP) shoes in 2016. This step-wise increase in performance coincides with recent advancements in shoe technology that increase the elastic properties of the shoe thereby reducing the energy cost of running. The latest CFP shoes are acknowledged to increase running economy by more than 4%, corresponding to a greater than 2% improvement in performance/run time. The recently modified rules governing competition shoes for elite athletes, announced by World Athletics, that includes sole thickness must not exceed 40 mm and must not contain more than one rigid embedded plate, appear contrary to the true essence and credibility of sport as access to this performance-defining technology becomes the primary differentiator of sporting performance in elite athletes. This is a particular problem in sports such as athletics where the primary sponsor of the athlete is very often a footwear manufacturing company. The postponement of the 2020 Summer Olympics provides a unique opportunity for reflection by the world of sport and time to commission an independent review to evaluate the impact of technology on the integrity of sporting competition. A potential solution to solve this issue can involve the reduction of the stack height of a shoe to 20 mm. This simple and practical solution would prevent shoe technology from having too large an impact on the energy cost of running and, therefore, determining the performance outcome. Electronic supplementary material The online version of this article (10.1007/s40279-020-01420-7) contains supplementary material, which is available to authorized users.

In the manufacturing industry, the most widely used equipment is equipment that uses electricity. Electricity cost is one of the highest operational production costs after labor cost. So, it is very important to save and optimize the use of electrical equipment. One of the manufacturing industries is Taru Martani, Ltd. This research aims to minimize the energy cost by proposing three hybrid algorithms, namely Palmer-NEH, Gupta-NEH, and Dannenbring-NEH methods. Some scheduling evaluation is done using the Efficiency Index (EI) and Relative Error (RE) parameters. It is concluded that the Palmer-NEH and Gupta-NEH methods are the best methods with the lowest energy cost compared with company's actual method and the Dannenbring-NEH method. Based on the Palmer-NEH and Gupta-NEH methods, both methods can save the makespan up to 399.13 minutes or 6.65 hours compared with the company's actual method. With these methods, the company is also able to save the production cost by Rp. 818,043.00.

In recent years, home energy management systems (HEMS), which enable the automatic control of electrical equipment and home appliances, have been attracting attention as a method for saving electricity at home. HEMS achieve energy saving by visualizing energy consumption at home and controlling energy consuming equipment such as air conditioners. The optimum control law is difficult to attain, owing to uncertainties related to power demand and power supply from the electrical equipment. Deep reinforcement learning has been used to address energy optimization problems for home environments. However, in HEMS, several components such as heating, ventilation, and air conditioning (HVAC) systems, storage batteries, and electric water heaters are simultaneously controlled, and therefore, the action space becomes extremely large. Therefore, it may not be feasible to fully learn the rare experience using traditional deep reinforcement learning methods due to the large size of the state-action space and slow propagation of delayed rewards. In this study, we propose an energy management algorithm that uses the Dual Targeting Algorithm to strongly learn the experience of acquiring high returns using the quick propagation of delayed rewards via multistep returns. The proposed energy management algorithm is applied to a HEMS learning experiment to control a storage battery and an HVAC system, and its performance is compared to that of a Deep Deterministic Policy Gradient-based energy management system. As a result, it is confirmed that the proposed method can reduce the number of hours deviating from the comfort temperature range by about 17% compared to the existing method.

Background Hand-rim wheelchair propulsion is straining and mechanically inefficient, often leading to upper limb complaints. Previous push–pull lever propulsion mechanisms have shown to perform better or equal in efficiency and physiological strain. Propulsion biomechanics have not been evaluated thus far. A novel push–pull central-lever propulsion mechanism is compared to conventional hand-rim wheelchair propulsion, using both physiological and biomechanical outcomes under low-intensity steady-state conditions on a motor driven treadmill. Methods In this 5 day (distributed over a maximum of 21 days) between-group experiment, 30 able-bodied novices performed 60 min (5 × 3 × 4 min) of practice in either the push–pull central lever wheelchair (n = 15) or the hand-rim wheelchair (n = 15). At the first and final sessions cardiopulmonary strain, propulsion kinematics and force production were determined in both instrumented propulsion mechanisms. Repeated measures ANOVA evaluated between (propulsion mechanism type), within (over practice) and interaction effects. Results Over practice, both groups significantly improved on all outcome measures. After practice the peak forces during the push and pull phase of lever propulsion were considerably lower compared to those in the handrim push phase (42 ± 10 & 46 ± 10 vs 63 ± 21N). Concomitantly, energy expenditure was found to be lower as well (263 ± 45 vs 298 ± 59W), on the other hand gross mechanical efficiency (6.4 ± 1.5 vs 5.9 ± 1.3%), heart-rate (97 ± 10 vs 98 ± 10 bpm) and perceived exertion (9 ± 2 vs 10 ± 1) were not significantly different between modes. Conclusion The current study shows the potential benefits of the newly designed push–pull central-lever propulsion mechanism over regular hand rim wheelchair propulsion. The much lower forces and energy expenditure might help to reduce the strain on the upper extremities and thus prevent the development of overuse injury. This proof of concept in a controlled laboratory experiment warrants continued experimental research in wheelchair-users during daily life.

This study examined sclerostin and cytokine responses to an endurance training session in male single sculling rowers. Sixteen highly trained rowers performed a 2-h rowing exercise (distance: 23.8 ± 0.9 km; heart rate: 138 ± 8 beats.min

In Brazil, free consumers must follow the criteria established by Law 9.074/95 and participate in the Free Contracting Environment (ACL), regulated by Decree 5.163/04, together with energy generators, traders, importers and exporters. These free consumers can choose and negotiate their energy purchase contracts (energy volumes, contract terms, prices, flexibilization and financial guarantees) with the other agents connected to the interconnected Brazilian grid. However, free consumers must have 100% of its energy contracted to avoid exposure to the short-term market and possible penalties, among others points. It is noteworthy that free consumers in Brazil are usually large industries and use electricity energy only to manufacture their products. In this sense, they are totally averse to contractual risks and penalties and seek the ACL only to obtain financial reductions with the same contractual security as the regulated market. In this sense, the main objective of this work is to model the mathematical optimization problem for contract flexibility optimization by free consumer in the ACL, minimizing the energy cost to meet its demand.

Deep-frying is the century-old and the most common cooking process which is still being used to prepare a variety of food products in industrial and domestic scales. Compared to other cooking processes, frying produces some distinctive flavor characteristics, but other undesirable and unacceptable characteristics to consumers are also originated during frying. Researchers have taken various technical approaches for reducing the oil content of fried products without compromising product quality. This review discusses some recently developed frying techniques which could improve the product quality, and advance frying efficiency, to save energy cost. Some modified method of alternative frying technologies used by the researchers are vacuum frying, microwave frying, microwave-assisted vacuum frying, radiant frying, ultrasound treated frying, air frying or their combinations. In this review, we aim to give a detailed insight into some specific aspects of new deep-frying practices and pretreatments for the quality maintenance of fried products highlighting their novelty and efficiency.

A 30-year financial model and business case is presented for implementing a microgrid at an Ontario school to meet their energy needs and net-zero carbon emissions. The project considers several fa...

Chemical engineers continually strive to produce high purity chemicals and materials with the minimum of inputs. However, many processes currently used in separations require significant energy expenditure and capital intensive processes that require phase transitions. Emerging technologies for liquid–liquid separations that avoid these transitions are desirable from an energy cost perspective. Membranes present an enticing separation technique; nonetheless, like all technologies there is a significant amount of technology vetting and derisking that must occur before adoption. This article reviews opportunities where membranes can be used for liquid separations and discusses the derisking process that must occur for commercial acceptance.

The Headquarters Department of the Army sponsored a study to determine the national impact of deploying the Re-tuning™ (“Re-tuning” is a trademark of the US Department of Energy) methodology in five building types that account for over 40% of the Army’s conditioned building stock. Re-tuning is a systematic process that improves operational efficiency and reduces energy consumption at no or low cost through the building automation system by correcting operational problems that plague buildings. The study relied on successful demonstration of the Re-tuning methodology at four pilot US Army installations that informed a holistic effort, including simulating 12 individual Re-tuning energy efficiency measures (EEMs) and six packages of EEMs in five selected Army building prototype models that represent 311 million ft2 (28.9 million m2) of the Army’s conditioned floor space. Both the baseline buildings and the packages were customized to capture the expected outcomes of Re-tuning a diverse set of buildings. The study highlighted the benefit of individual Re-tuning EEMs and economics of implementing packages of EEMs in applicable Army buildings across 16 climates and two building vintages. The average whole-building energy savings ranged from 10.8 to 40.5% by building type, with the company operations facility building having the highest value proposition from Re-tuning. In addition, the study revealed that all large office buildings in the Army are economical to Re-tuning. The total modeled cost savings potential for Re-tuning the five building types across the US Army is $204/1000 ft2 ($220/100 m2) or $64 M annually. This cost savings represent 5.6% of all the Army’s energy expenditures.

Dependence existing among production parameters can significantly affect energy costs. For material removal processes, processing times and material amounts to be cut have positive dependence, and the dependence can affect energy costs by varying a peak electricity load. Existing methods to model the dependence of production parameters are based on parametric approaches that cannot accurately represent the dependence due to the rigid nature of parametric models. To address this issue, this study proposes a method to quantify dependence among manufacturing parameters through the application of the empirical copula to the dependence between the milling processing time and the amount of volume to be cut. The proposed method is illustrated by a case study of a manufacturing facility consisting of milling machines; a total of 27 scenarios are simulated for energy cost estimations. The case study clearly shows that the proposed method can capture the dependence between the milling parameters more accurately than a conventional dependence measure from parametric correlation models. The findings from this study would be useful to estimate energy costs in that the proposed method provides a better fit to real production data than conventional parametric approaches can.

This research deals with a case study of clear water rising pumping main to supply drinking water in Adityapur Municipality, Jharkhand, India. Pipes are important and most cost bearing entity in a water pipeline distribution network. Hence proper selection of pipe is most challenging job to pipeline designers. This study shows about various processes involved in order to get an optimum design in respect to the selection of pipes using WaterGEMS software. A 60 MLD Subarnarekha Water Supply Scheme (WSS) is been considered where two numbers 30 MLD pumps with 40 m rated head have been proposed on the basis of two working and two standby modes to fulfill the demand of drinking water. Mainly cost variation is compared due to change in pipe diameter in relation with energy cost against this WSS. As per the data received, the inputs were incorporated and accordingly the results are interpreted. The whole considered network consists 37 pipes and 10 junctions. Various system outputs are been reflected for steady state simulations. An extended period simulation has also been carried out to compute filling time of all tanks according to their water demands. The pumping energy cost comparison is also reflected when a 1200 mm diameter of pipeline is been replaced with 1000 mm pipeline that runs for 4.173 km. This study is an effort to open up the process of cost optimization in pressure pipeline network for implementation in various water supply schemes.

Increasing the longitudinal bending stiffness of running shoes decreases energy cost until a low point is reached, suggesting an optimal shoe stiffness. Previous research found optimal stiffness va...

The aim of the present study was to evaluate the effectiveness of manual technique of NeuroSensory Posturotherapy (PNS) applied indirectly to vestibulocochlear nerve in the balance regulation of elderly. Across-sectional study, including 53 elderly, with average age 73.5±7.0 years old, evaluated preand postthe application of the PNS on the Cyber-Sabots stabilometric platform, withopened eyes (OE) and closed eyes (CE).For the analysis of the variables obtained pre and posttechniquewith OE and CE,the Wilcoxon test was used. The results showed that after applying the PNS with OE and also CE there was a decrease ofposterior-anterior displacement (p

Maximal aerobic capacity (VO2max) and running economy (RE) are markers of running performance. A valid evaluation of RE may occur through allometric scaling of body mass (alloVO2; ml kg-0.66 min-1), energy cost (EC; kcal kg-1 km-1), or percent of VO2max (%VO2max). Little is known about physiological changes that occur in competitive runners over a marathon training cycle. The VDOT score, incorporating VO2max and RE, enables comparison of race performances under different temperature conditions. This study’s purpose was to determine whether VO2max and measures of RE change with marathon training, and to evaluate the relationship between these variables and VDOT. Eight runners (age 34±2 years; marathon

Energy storage will witness a leap of understanding of new battery chemistries. Considering the safety that cannot be compromised, new aqueous batteries may surface as the solutions to meet the immense market needs, where the growth of renewables is no longer limited by the lack of storage. Aqueous Zn-metal batteries are intriguing candidates to deliver the desirable properties and exhibit competitive levelized energy cost. However, the fact that most commercial Zn batteries are primary batteries states the difficulty of reversibility for the reactions of electrodes in such batteries. This article will highlight the practical needs that guide the development of storage batteries. The causes of irreversibility for both cathode and zinc metal anode are discussed, and the potential solutions for these challenges are summarized. Zn metal batteries may one day address the storage needs, and there exists a vast potential to further improve the properties of reactions in this battery.

This paper addresses a methodology to optimize PV panel cleaning schedule. PV system yield is impacted due to soiling on panel surface. This soiling changes during the system operation as a consequence of environmental conditions. In order to reduce the impact of soiling accumulation, the panel surface must be cleaned. However, cost and frequency of cleaning can affect plant revenue. Therefore, to enhance financial performance, an optimal cleaning strategy must be selected. This strategy depends mostly on energy cost, soiling rate, cleaning costs, and system efficiency. Hence, the model proposed in this work takes into account these variables in order to support the decisions during the assessment of PV yield. The methodology was evaluated through two irradiation profiles with different associated costs. As a result, the methodology made it possible to estimate a cleaning strategy optimizing the incomes under different scenarios.

The worldwide demand for reduction of CO2 pollution, with more penetration of renewable energy sources and an increased number of electric vehicles (EVs), demonstrates the importance of economic dispatch (ED) with taking into account the reduction of CO2 emission. ED is a classical problem in which EVs impose more penetration as a dynamic load, and its impact as vehicle-to-grid (V2G) is the possible future trend with cost minimization. Based on the integration of EVs and hybrid renewable sources concerning both economic dispatch and pollution minimization, the multi-objective function is converted into a single comprehensive objective by using the judgment matrix methodology. In this paper, the investigation involves the minimization of the cost of all three objectives viz. operation cost, pollution cost, and carbon emissions with ED by incorporating V2G technology. The algorithms which include particle swarm optimization, as well as artificial bee colony, are applied under various operation and control strategies. The proposed models are verified and analyzed with different case studies. In terms of operation economics, the simulation results validate the superior performance of EVs based microgrid (MG) model in the coordinated charging and discharging mode. Further, the comparison of both algorithms shows better results with the ABC algorithm in terms of cost minimization of all objectives. ABC is better in V2G based microgrid with coordinated charging and discharging mode while its performance is significant during a large number of EVs (i.e., 700 EVs). Moreover, the load shedding scenarios are integrated which enables the MG system to operate in dual mode (i.e., seamless transition). In this paper, the main contribution involves penetration of EVs as dynamic load and its V2G impact in a coordinated or uncoordinated way, application of ABC algorithm for this particular load problem with improved results, and inclusion of short-term load shedding scenarios.

The connectivity restoration has significance for Industrial IoTs (IIoTs). If the connectivity is compromised, mobile data collectors can be deployed to restore the connectivity. The aggregation ratio, which is the proportion of data successfully delivered to the sink over all data, is considered as a crucial index. However, previous works only consider the travel distance, the load balance, the latency and the energy cost over the aggregation ratio. In this paper, a machine learning based connectivity restoration strategy CRrbf, that utilizes a Radial Basis Function Neural Network (RBFNN) along with an Unscented Kalman Filter (UKF), is proposed to maximize the aggregation ratio meanwhile reduce the energy cost. The theoretical analysis and simulation results indicate that CRrbf outperforms both distance based strategies and terrain based strategies in the aggregation ratio, the network latency and the network throughput. And the energy cost of CRrbf is less than that of distance based strategies.

Edge computing helps break through the resource limitations of the terminal, providing powerful computing power and improving the user experience. Time cost and energy cost are the main considerati...

Oxygen uptake (V̇O2), heart rate (HR), energy cost (EC) and oxygen pulse are lower during downhill compared to level or uphill locomotion. However, a change in oxygen pulse and EC during prolonged grade exercise is not well documented. This study investigated changes in cardiorespiratory responses and EC during 45-min grade exercises. Nine male healthy volunteers randomly ran at 75% HR reserve during 45-min exercise in a level (+1%), uphill (+15%) or downhill (−15%) condition. V̇O2 , minute ventilation (V̇E ) and end-tidal carbon dioxide (PetCO2) were recorded continuously with 5-min averaging between the 10th and 15th min (T1) and 40th and 45th min (T2). For a similar HR (157±3 bpm), V̇O2 , V̇E , and PetCO2 were lower during downhill compared to level and uphill conditions (p

Light influences private and working life. Smart lighting systems make it possible to adjust the available light to the behavior and preferences of the user, which increases productivity and user well-being and contributes to lowering energy cost. The benefits of smart lighting systems have frequently been discussed for private households, office buildings, and for public streets; their potential for supporting industrial processes has, in contrast, not attracted much attention so far. The article at hand gives an overview of smart lighting systems and the potential benefits associated with them. It then presents a few use cases to highlight how smart lighting could lower energy costs and improve operational processes in industrial companies.

Backpacks are essential for travel but carrying a load during a long journey can easily cause muscle fatigue and joint injuries. Previous studies have suggested that suspended backpacks can effectively reduce the energy cost while carrying loads. Researchers have found that adjusting the stiffness of a suspended backpack can optimize its performance. Therefore, this paper proposes a stiffness-adjustable suspended backpack; the system stiffness can be adjusted to suitable values at different speeds. The stiffness of the suspended backpack with a 5-kg load was designed to be 690 N/m for a speed of 4.5 km/h, and it was adjusted to 870 and 1050 N/m at speeds of 5.5 and 6.5 km/h, respectively. The goal of this study was to determine how carrying a stiffness-adjustable suspended backpack affected performance while carrying a load. Six healthy participants participated in experiments where they wore two backpacks under three conditions: the adjustable-stiffness suspended backpack condition (S_A), the unadjustable-stiffness suspended backpack condition (S_UA), and the ordinary backpack condition (ORB). Our results showed that the peak accelerations, muscle activities, and peak ground reaction forces in the S_A condition were reduced effectively by adjusting the stiffness to adapt to different walking speeds; this adjustment decreased the metabolic cost by 4.21 ± 1.21% and 2.68 ± 0.88% at 5.5 km/h and 4.27 ± 1.35% and 3.38 ± 1.31% at 6.5 km/h compared to the ORB and S_UA, respectively.

Over the past 20 years, net-zero energy house (NZEH) construction costs have steadily decreased because of many reasons, such as technical progress, energy-saving design obligations, and dramatic cost reductions in renewable energy systems, especially solar power systems. Currently, the costs of NZEH are estimated to be about 5% higher than similar-sized houses. These additional costs are mainly for installing PV systems, which can be offset by energy saving costs. This study assessed energy performance and load matching through remote monitoring systems, and energy costs were analyzed for two-family houses. The two houses were all-electric houses and different in both size and location. A 6 kWp grid-connected PV system and 16 kW air source heat pump for space heating and domestic hot water were equally implemented. After data analysis, 100% of the energies were supplied through the PV system for 3 years, thus achieving net-zero energy. According to the Korean residential electricity tariff system, the annual electricity charges were, on average, between USD 105.1 and USD 121.4 after adding demand charges and value-added tax for import electricity charges. The energy cost reduction rate, compared to the same house without a PV system, was about 95%, and the simple payback period of the 6 kW PV system in NZEH was about 6 years. In addition, the annual load cover factor and supply cover factor as load-match indices between electricity generation and the load were in a range of 0.39–0.49 and 0.37–0.42, respectively.

The effect of economic and population growth rapidly contributes to the energy usage of buildings increasing to high levels. To minimize the electrical energy consumption (EC), thermal insulation of wall has significant impact to minimizing the EC of building. The aim of this paper is to define the influence of wall on reducing EC of residential building with different wall characteristics. In this case, two different kinds of building characteristics were evaluated, namely: building-1 applied an innovative Cellular Lightweight Concrete (inCLC) brick and building-2 with wood applied to create the walls. Under numerical optimization, a mathematical model was developed to define the EC of air conditioning (AC). Based on the result of research indicated the EC of building-1 (IDR 25,365) was cheaper than building-2 (IDR 29,350). Consequently, the energy cost reduction (ECR) can be achieved to be IDR 3,985 (13.57%).

This paper presents an analysis and optimization of an isolated hybrid renewable power system to operate in the Alrashda village in the Dakhla Oasis, which is situated in the New Valley Governorate in Egypt. The proposed hybrid system is designed to integrate a biomass system with a photovoltaic (PV), wind turbine (WT) and battery storage system (Bat). Four different cases are proposed and compared for analyzing and optimizing. The first case is a configuration of PV and WT with a biomass system and battery bank. The second case is the integration of PV with a biomass system and battery bank. The third case is WT integrated with biomass and a battery bank, and the fourth case is a conventional PV, WT, and battery bank as the main storage unit. The optimization is designed to reduce component oversizing and ensure the dependable control of power supplies with the objective function of reducing the levelized cost of energy and loss of power supply probability. Four optimization algorithms, namely Heap-based optimizer (HBO), Franklin’s and Coulomb’s algorithm (CFA), the Sooty Tern Optimization Algorithm (STOA), and Grey Wolf Optimizer (GWO) are utilized and compared with each other to ensure that all load demand is met at the lowest energy cost (COE) for the proposed hybrid system. The obtained results revealed that the HBO has achieved the best optimal solution for the suggested hybrid system for case one and two, with the minimum COE 0.121171 and 0.1311804 $/kWh, respectively, and with net present cost (NPC) of $3,559,143 and $3,853,160, respectively. Conversely, STOA has achieved the best optimal solution for case three and four, with a COE of 0.105673 and 0.332497 $/kWh, and an NPC of $3,103,938 and $9,766,441, respectively.

openaire: EC/H2020/856602/EU//FINEST TWINS Espoo has set a goal to abandon the use of coal in its district heating system by the year 2025. The local district heating operator is producing a major share of Espoo's heat demand with combined heat and power units, but a large share of that thermal capacity will be closed by 2025. The plan is to replace the closed down capacity with renewable fuels, heat pumps and waste heat utilisation. The goal of this paper is to simulate the impacts of these emission reductive acts on the production costs and CO2 emissions of the system. The possibility of utilising waste heat from data centres in the district heating system is evaluated. The results show that abandoning coal in the city's heating system leads to a significant reduction of CO2 emissions with a small increase of annual production costs. Waste heat enables emission reductions even further, and the increase of production costs can be prevented.

Human population is increasingly getting contained in closed office or residential spaces with minimal natural ventilation. Air pollutants that get generated internally or coming in from outside tends to get trapped inside these closed spaces long enough to pose health hazards. Also with these spaces being artificially controlled using power hungry HVAC equipment leading to heavy load on the public electric infrastructure along with inflated electric bills eating into operating budgets. This paper presents a LoRaWAN based smart room monitoring solution to monitor vital room environmental parameters along with a automatic load control scheme that could potentially save up to 30 percent in energy cost along with proportional reduction in greenhouse gas emissions.

A compressed air system (CAS) is one of the most common and energy-consuming systems in manufacturing. To practice more economically and environmentally sustainable manufacturing, manufacturers need ways to reduce the energy costs and carbon footprint, resulting from a CAS in their production systems. While preliminary energy studies on a CAS and on machining processes are available separately, existing research studies rarely analyze energy costs using a tool that considers both a CAS and production systems. Therefore, in this study, we propose an energy simulation tool that combines a CAS and a production system to evaluate the effects of a CAS and production parameters on energy consumption and costs at a factory level. In particular, we develop a time-discretized algorithm for simulating a CAS to accurately consider the dynamics of CAS parameters such as pressure and flow rate. From 48 simulation case studies, we show that changes in a CAS such as proper HP sizing, a reduction in compressed air leaks, and a decrease in the discharge pressure can increase productivity and reduce energy costs by up to 11%. The simulation analysis from this study suggests a way to help manufacturers and researchers find more sustainable ways to achieve energy-efficient configurations for production systems including a CAS.

Accurate prediction from electricity demand models is helpful in controlling and optimizing building energy performance. The application of machine learning techniques to adjust the electrical consumption of buildings has been a growing trend in recent years. Battery management systems through the machine learning models allow a control of the supply, adapting the building demand to the possible changes that take place during the day, increasing the users’ comfort, and ensuring greenhouse gas emission reduction and an economic benefit. Thus, an intelligent system that defines whether the storage system should be charged according to the electrical needs of that moment and the prediction of the subsequent periods of time is defined. Favoring consumption in the building in periods when energy prices are cheaper or the renewable origin is preferable. The aim of this study was to obtain a building electrical energy demand model in order to be combined with storage devices with the purpose of reducing electricity expenses. Specifically, multilayer perceptron neural network models were applied, and the battery usage optimization is obtained through mathematical modelling. This approach was applied to a public office building located in Bangkok, Thailand.

Purpose: To compare the accuracy and precision of a hip-worn accelerometer to predict energy cost during structured activities across motor performance and disease conditions. Methods: 118 adults self-identifying as healthy (n = 44) and those with arthritis (n = 23), multiple sclerosis (n = 18), Parkinson’s disease (n = 17), and stroke (n = 18) underwent measures of motor performance and were categorized into groups: Group 1, usual; Group 2, moderate impairment; and Group 3, severe impairment. The participants completed structured activities while wearing an accelerometer and a portable metabolic measurement system. Accelerometer-predicted energy cost (metabolic equivalent of tasks [METs]) were compared with measured METs and evaluated across functional impairment and disease conditions. Statistical significance was assessed using linear mixed effect models and Bayesian information criteria to assess model fit. Results: All activities’ accelerometer counts per minute (CPM) were 29.5–72.6% less for those with disease compared with those who were healthy. The predicted MET bias was similar across disease, −0.49 (−0.71, −0.27) for arthritis, −0.38 (−0.53, −0.22) for healthy, −0.44 (−0.68, −0.20) for MS, −0.34 (−0.58, −0.09) for Parkinson’s, and −0.30 (−0.54, −0.06) for stroke. For functional impairment, there was a graded reduction in CPM for all activities: Group 1, 1,215 CPM (1,129, 1,301); Group 2, 789 CPM (695, 884); and Group 3, 343 CPM (220, 466). The predicted MET bias revealed similar results across the Group 1, −0.37 METs (−0.52, −0.23); Group 2, −0.44 METs (−0.60, −0.28); and Group 3, −0.33 METs (−0.55, −0.13). The Bayesian information criteria showed a better model fit for functional impairment compared with disease condition. Conclusion: Using functionality to improve accelerometer calibration could decrease variability and warrants further exploration to improve accelerometer prediction of physical activity.

A shorter joint moment arm (MA) may help maintain the necessary muscle force when muscle contractions are repeated. This beneficial effect may contribute to reducing the energy cost during running. In this study, we examined the correlation between patellar tendon MA and running performance in endurance runners. The patellar tendon MA and quadriceps femoris muscle volume (MV) in 42 male endurance runners and 14 body size‐matched male untrained participants were measured using a 1.5‐T magnetic resonance system. The patellar tendon MA was significantly shorter in endurance runners than in untrained participants (p = 0.034, d = 0.65). In endurance runners, shorter patellar tendon MA correlated significantly with better personal best 5000‐m race rime (r = 0.322, p = 0.034). A trend toward such a significant correlation was obtained between quadriceps femoris MV and personal best 5000‐m race time (r = 0.303, p = 0.051). Although the correlation between patellar tendon MA and personal best 5000‐m race time did not remain significant after adjusting for the quadriceps femoris MV (partial r = 0.247, p = 0.120), a stepwise multiple regression analysis (conducted with body height, body mass, patellar tendon MA, and quadriceps femoris MV) selected the patellar tendon MA (β = 0.322) as only a predictive variable for the personal best 5000‐m race time (adjusted R 2 = 0.081, p = 0.038). These findings suggest that the shorter patellar tendon MA, partially accorded with the smaller quadriceps femoris size, may be a favorable morphological variable for better running performance in endurance runners., This study examined the relationship between patellar tendon moment arm (MA) and running performance in endurance runners. A shorter patellar tendon MA was correlated with a better personal best 5000‐m race rime in endurance runners. The shorter patellar tendon MA may be a favorable morphological variable for superior running performance in endurance runners.

Introduction: Women have been shown to experience less neuromuscular fatigue than men in knee extensors (KE) and less peripheral fatigue in plantar flexors (PF) after ultratrail running, but it is unknown if these differences exist for shorter trail running races and whether this may impact running economy. The purpose of this study was to characterize sex differences in fatigability over a range of running distances and to examine possible differences in the postrace alteration of the cost of running (Cr). Methods: Eighteen pairs of men and women were matched by performance after completing different races ranging from 40 to 171 km, divided into SHORT versus LONG races (100 km, respectively). Neuromuscular function and Cr were tested before and after each race. Neuromuscular function was evaluated on both KE and PF with voluntary and evoked contractions using electrical nerve (KE and PF) and transcranial magnetic (KE) stimulation. Oxygen uptake, respiratory exchange ratio, and ventilation were measured on a treadmill and used to calculate Cr. Results: Compared with men, women displayed a smaller decrease in maximal strength in KE (−36% vs −27%, respectively, P < 0.01), independent of race distance. In SHORT only, women displayed less peripheral fatigue in PF compared with men (Δ peak twitch: −10% vs −24%, respectively, P < 0.05). Cr increased similarly in men and women. Conclusions: Women experience less neuromuscular fatigue than men after both “classic” and “extreme” prolonged running exercises but this does not impact the degradation of the energy Cr. Refereed/Peer-reviewed

Nowadays, off-grid systems, which do not require grid connection investment instead of grid connected systems, have become quite feasible. In this study, a feasibility analysis was carried out for a hybrid energy system using solar and wind energy sources to supply to uninterrupted electricity demand of a region with 100 villas in Izmir, Turkey. It has been shown that how changes cost of the hybrid energy system sizing according to the control strategies by using the HOMER software. In the paper, two different control strategies are determined as Cycle Charging (CC) and Load Following (LF), and then the control strategies are compared. According to the results obtained as a result of the simulations, it has been revealed that the research region to operate with CC can supply to the electrical energy demand with lower capacity system architecture. The CC was found to be more suitable for the research region than LF in terms of both Cost of Energy (COE) and Net Preset Cost (NPC).

The aim of this study was to assess and compare by numerical simulations and analytical models the resistive forces, mechanical power and energy cost using two different types of road helmets (standard vs aero road helmet). An elite cyclist was scanned on the racing bicycle, wearing his competition gear and helmets. Numerical simulations by Computational Fluid Dynamics were carried-out at 11.11 m/s (40 km/h) and 20.83 m/s (75 km/) to extract the drag force. The mechanical power and energy cost were estimated by analytical procedures. The drag force were between 9.93 N and 66.96 N across the selected speeds and helmets. The power to overcome drag were 182.19 W and 1121.40 W. The total power lower and higher values were 271.05 W and 1558.02 W. The energy cost estimation was between 106.89 J/m and 381.40 J/m across the different speeds and helmets. The standard helmet imposed higher drag and demanded more power.

Capturing carbon dioxide from flue gases can enable the use of inexpensive and energy-dense fossil fuels with lessened or no environmental harm. However, the materials and systems used in post-combustion carbon capture add significant energy and monetary costs, impeding their adoption. Recently in Cell Reports Physical Science, Sadiq et al. (2020) reported the design of a low energy cost nanocomposite sorbent for efficient carbon capture based on magnetic induction swing adsorption.