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Purpose: Advanced footwear technology is prevalent in distance running, with research focusing on these "super shoes" in competitive athletes, with less understanding of their value for slower runners. The aim of this study was to compare physiological and biomechanical variables between a model of super shoes (Saucony Endorphin Speed 2) and regular running shoes (Saucony Cohesion 13) in recreational athletes. Methods: We measured peak oxygen uptake (VO2peak) in 10 runners before testing each subject 4 times in a randomly ordered crossover design (ie, Endorphin shoe or Cohesion shoe, running at 65% or 80% of velocity at VO2peak [vVO2peak]). We recorded video data using a high-speed camera (300 Hz) to calculate vertical and leg stiffnesses. Results: 65% vVO2peak was equivalent to a speed of 9.4 km·h−1 (0.4), whereas 80% vVO2peak was equivalent to 11.5 km·h−1 (0.5). Two-way mixed-design analysis of variance showed that oxygen consumption in the Endorphin shoe was 3.9% lower than in the Cohesion shoe at 65% vVO2peak, with an interaction between shoes and speed (P =.020) meaning an increased difference of 5.0% at 80% vVO2peak. There were small increases in vertical and leg stiffnesses in the Endorphin shoes (P <.001); the Endorphin shoe condition also showed trivial to moderate differences in step length, step rate, contact time, and flight time (P <.001). Conclusions: There was a physiological benefit to running in the super shoes even at the slower speed. There were also spatiotemporal and global stiffness improvements indicating that recreational runners benefit from wearing super shoes. [ABSTRACT FROM AUTHOR]

The main purpose of this study is to present family farms as consumers and producers of renewable energies which provide them with an opportunity to reduce operating costs. The time scope of the study is 2014–2022, and the Farm Accountancy Data Network is used as the data source. The following research methods were employed: comparative and descriptive analysis, intensity indicators, ranking assignment and panel regression. Based on the values of energy output and energy costs, the rankings revealed a strong position of the Netherlands and Germany. As demonstrated by the study, energy production and consumption volumes depend on the farms' economic size, but are not impacted by production type. Another finding is that energy production covers only one-third of its costs. Also, both production volumes and costs were on a growth path on a year-over-year basis, with similar growth ratios. The European Union's leaders in energy consumption and production are the Netherlands, Germany, Belgium, Denmark, Czech Republic, Hungary, Luxembourg, Slovakia and Sweden. The study included the structuring of panel models for energy output and costs and identified their determinants. Energy output depends on total inputs and grows as they grow. Energy costs, in turn, are related to utilized agricultural area, total output and family farm income. An important limitation of this study is that FADN is a provider of high-level data. Hence, it is impossible to tell what specific sources of renewable energy are used by farms, and how they are affected by such exogenous factors as climate, earmarked subsidies or energy policy. The findings from this study are discussed in the context of the European Commission's recommendations laid down in the Bioeconomy Strategy of the EU (2013), the Seventh Environment Action Program, the New Innovation Agenda of the European Union, the Report "Transforming Our World: the United Nations 2030 Agenda for Sustainable Development" and the Circular Economy Action Plan. [ABSTRACT FROM AUTHOR]

Introduction: Running economy (RE) deteriorates during prolonged running, although the effect of measuring energy cost (EC) or oxygen cost (OC) on the magnitude of these changes has not been investigated. Similarly, it is unknown if runners’ performance level may influence the deterioration of RE during prolonged running. The aims of this study were to compare changes in EC and OC measurements of RE during a prolonged run in a large cohort of well-trained male runners, and to compare changes between runners of high- and low-performance standard. Methods: Forty-four male runners (maximal oxygen uptake (V̇O2max) 62.4 mL·kg-1 ·min-1 ; 10-km time: 35:50 ± 4:40 mm:ss) completed an incremental test determining lactate threshold 1 (LT1) and V̇O2max, and on a separate occasion, a 90-min run at LT1. Respiratory gases were collected at 15-min intervals. Subsequently, subgroups of high- (HP; 10-km time: 31:20 ± 01:00 mm:ss) and low-performing (LP; 10-km time: 41:50 ± 01:20 mm:ss) runners were compared. Results: RE deterioration was only fractionally larger when expressed as OC than EC (0.1% greater from 30-90 min; P < 0.001), perhaps due to the small change in respiratory exchange ratio (-0.01) in this study. For the HP group, increases were lower than LP after 90 min in both EC (+2.3% vs +4.3%; P < 0.01) and OC (+2.4% vs +4.5%; P < 0.01). Similarly, at standardized distances, changes were lower for HP versus LP, for example, at 16.7 km + 1.0 versus +3.2% for EC (P < 0.01), and +1.2 vs +3.4% for OC (P < 0.001). Conclusions: The deterioration of RE was dependent on athlete’s performance level, with HP runners displaying superior RE durability. The use of EC or OC had only a fractional influence on RE durability, although this may gain importance with larger shifts in substrate metabolism. [ABSTRACT FROM AUTHOR]

Predictive equations are widely employed for estimating the volume of oxygen consumption (VO2) while walking, which is ultimately employed to determine energy expenditure and tailor exercise prescription. This study aimed to test the agreement between the measured VO2 and estimated VO2 during a walking protocol on a treadmill at 3.5, 4.5, 5.5, and 6.5 km/h. Thirty‐eight young adults (50% women) participated in this cross‐sectional study. The Omnical (Maastricht Instruments, Maastricht, The Netherlands) and K5 (Cosmed, Rome, Italy) metabolic systems were used to measure VO2. To determine the predictive equations, a comprehensive literature search was conducted using the MEDLINE database from May 2022 to July 2023. Seven predictive equations were found and included for estimating VO2 values. We calculated the mean bias (mean difference between measured VO2 and estimated VO2) obtained at each speed using one‐sample t‐tests. We compared the VO2 measured and estimated values using repeated measures analysis of variance and the Bland–Altman method. One‐sample t‐tests showed that all score errors were different from zero (ranging from 1.1 to 5.4 mL/kg/min). Thus, no predictive equation estimated similar VO2 values in comparison with the Omnical and K5 metabolic systems at all intensities. However, the Weyand equation showed the lowest bias across all intensities (score error of 1.1 mL/kg/min). This study showed a lack of agreement between the Omnical and K5 systems compared to diverse predictive equations specially designed to estimate VO2 during walking. Nevertheless, based on our results, the Weyand equation should be the preferred option. Highlights: The estimated VO2 values derived from all predictive equations showed no agreement with VO2 values measured by the Omnical and K5 metabolic systems, highlighting the importance of taking into account the error introduced by VO2 walking predictive equations when estimating VO2.The Weyand equation presented the lowest bias in comparison to the VO2 measured by the Omnical metabolic cart, which is the gold‐standard metabolic cart (i.e., system of reference).These findings may hold practical implications when transitioning from clinically based programs to exercise interventions tailoring or self‐guided exercise programs in young adults. Moreover, these results can contribute to individualize exercise programs by sport scientists using freely available and affordable tools as predictive equations. [ABSTRACT FROM AUTHOR]

The aim of the study was to assess the influence of year-long training of race walkers on physiological cost and total energy center of mass (CoM). The assessment performed was based on indicating the differences between the resulting energy cost in a group of elite race walkers walking at technical, threshold, and racing speeds calculated by physiological and biomechanical methods before beginning and after finishing a year-long training cycle. The study involved 12 competitive race walkers who had achieved champion or international champion level. Their aerobic endurance was determined by means of a direct method, applying an incremental exercise test on the treadmill. The gait of the participants was recorded using the 3D Vicon analysis system. Changes in mechanical energy amounted to the value of the total external work of the muscles needed to accelerate and lift the center of mass during a normalized gait cycle. The highest influence on the total external work increase for increasing speeds of gait in both examinations was attributed to the changes in the kinetic energy resulting from the center of mass movement. A statistically significant decrease of the mean value of total external work for racing speed was observed in the second examination (p < 0.001). An approx. 8% decrease (NS) of EE energy cost, standardized by body mass and distance covered, was found between the first and second examinations. The energy cost and total external work were significantly differentiated by the walkers' gait speeds (p < 0.05–0.001). The energy cost significantly differed from the total external work at p < 0.001. [ABSTRACT FROM AUTHOR]

Studies on advanced footwear technology (AFT) often investigate potential performance benefits for constraint populations, and high running speeds. This research compared running biomechanics, running economy and perception between males and females, when wearing three different AFT conditions at recreational running speeds. An innovation shoe sample (IM) at confirmation stage in the product creation process was compared to two commercial running shoes (MM, MF). Gender and shoe variable means were compared for main and interaction effects (p < 0.05) by a mixed 2 × 3 repeated measures analysis of variance (RM ANOVA), and effect size estimation. A main effect was seen for shoe condition, both the IM and MF showed higher vertical loading rates than MM, and higher peak vertical force 1. IM had less frontal plane rearfoot motion than both the MM and MF. At the MTPJ, IM had lower maximum dorsiflexion angle, dorsiflexion velocity leading to lower negative power and negative work than both the MM and MF. IM and MF showed significantly lower oxygen consumption than the MM. Perception measurements showed IM and MF to be significantly softer, responsive and had better propulsion than the MM. A main effect was seen for gender, females exhibited higher vertical loading rates, reduced frontal plane ankle motion and lower MTPJ motion, and lower oxygen consumption compared to males. There was no gender effect for perception. Despite biomechanical differences, both IM and MF showed improved performance compared to the MM. Males and females exhibit different biomechanics when wearing AFT, however this did not lead to differences in subjective perception. It is concluded that the specific AFT applied for IM samples in this research functions for both groups largely similarly. [ABSTRACT FROM AUTHOR]

This study examines the photovoltaic (PV) energy output and levelized cost of energy (LCOE) in seven regions of Tanzania across five different tilt adjustments of 1 MW PV systems. The one-diode model equations and the PVsyst 7.2 software were used in the simulation. The results reveal variations in energy output and LCOE among the regions and tilt adjustments indicating a strong correlation between PV energy output and solar irradiance incident on the PV panel. For horizontal mounting, the annual energy output ranges from 1229 MWh/year in Kilimanjaro to 1977 MWh/year in Iringa. Among the three optimal tilt adjustments, annually, monthly and seasonal, the last two are predicted to yield larger energy outputs, whereas the two axis tracking configuration consistently provides the maximal energy output in all regions, ranging from 1533 MWh/year in Kilimanjaro to 2762 MWh/year in Iringa. The LCOE analysis demonstrates the cost-effectiveness of solar PV systems compared to grid-connected and isolated mini-grid tariffs. The LCOE values across the regions and tilt adjustments range from $0.07/kWh to $0.16/kWh. In comparison, the tariff for grid-connected solar PV is $0.165/kWh, while for isolated mini-grids; it is $0.181/kWh. The monthly optimal tilt configuration proves to be the most cost-effective option for energy generation in multiple regions, as it consistently exhibits the lowest energy cost compared to the other four configurations. The results provide valuable insights into the performance and economic feasibility of various system setups. Through meticulous simulation and data analysis, we have gained a comprehensive understanding of the factors influencing energy generation and costs in the context of solar photovoltaic systems.

Abstract The efficient operation of heating ventilation and air conditioning systems relies on advanced control strategies. However, current control methods are often limited by issues such as uncertain system parameter information and spatial coupling constraints related to the supply rate of the air supply fan. To this end, an energy joint thermal comfort management method for complex environments in multiple regions is proposed. The long-term total cost minimization of the system is established, and then the Lyapunov optimization technology is used to design the distributed control algorithm. Simulation validation shows that the proposed method reduces the energy cost by an average of 11.24% compared to other methods with a thermal discomfort cost coefficient of 0. The average temperature deviation in the area is improved by 0.15 °C and 0.68 °C, respectively. The method saves more than 10% of the total energy cost under different thermal perturbations with an average total temperature deviation of 0.04 °C. The results indicate that the proposed energy joint thermal comfort management method can flexibly balance energy costs and user thermal comfort without knowing any prior information of system parameters, which can also greatly protect user privacy information. This method has application value in the control of heating ventilation and air conditioning systems in complex environments such as commercial buildings.

The promotion of physical activity is important for fostering healthy aging. However, a substantial proportion of older adults remain sedentary. Current metrics assessing the energy cost of physical activity are primarily designed for the general adult population and inadequately account for distinct physiological changes in older individuals-encompassing variations in muscle mass, bone density, metabolism, and overall functional capacity. This study aimed to determine the energy cost of selected physical activities of Filipino older persons. This cross-sectional study conducted in Taguig City involved 19 older adults aged 60-79 yr using the COSMED Fitmate indirect calorimeter for resting metabolic rate determination, as well as the portable COSMED K5 indirect calorimeter for measuring energy cost of different physical activities-including treadmill walking, self-paced walking, a routine based on the DOST-FNRI manual, and multi-gym equipment. The outcomes of the study were presented in percentages and averages. Participants in the study were categorized based on their muscle strength and mass. Analysis revealed a consistent trend where older adults with lower appendicular skeletal muscle mass index and handgrip strength values demonstrated lower metabolic equivalent values across the different exercise routines. Notably, Routine 2 displayed an exception, with individuals above the 50th percentile of ASMI and HGS exhibiting lower METs than those below the 50th percentile. This study contributes insights into the energy cost of specific activities among older adults emphasizing the importance of physical activity in healthy aging and providing valuable information for tailored interventions and a nuanced understanding of energy expenditure in this age group. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to determine associations between running economy (RE) and running sagittal plane kinematic and kinetic parameters. Method: A total of 30 male recreational runners (age: 21.21 ± 1.22 yr, VO2max: 54.61 ± 5.42 mL·kg-1·min-1) participated in two separate test sessions. In the first session, the participant's body composition and RE at 10 and 12 km·h-1 were measured. In the second session, measurements were taken for the sagittal plane of hip, knee, and ankle angles and range of motion (ROM), as well as ground reaction force. Results:Moderate correlations were found between lower energy costs at 12 km·h-1 and smaller hip flexion at toe-off (r = 0.373) as well as smaller peak hip flexion during stance (r = 0.397). During the swing phase, lower energy costs at 10 km·h-1 were moderately correlated with smaller peak knee flexion and smaller knee flexion and extension ROM (r = 0.366-0.443). Lower energy costs at 12 km·h-1 were moderately correlated with smaller peak hip and knee flexion as well as knee extension ROM(r = 0.369-0.427). In terms of kinetics, there was a moderate correlation between higher energy costs at 10 km·h-1 and larger peak active force, as well as larger peak braking and propulsion force (r = -0.470-0.488). Lower energy costs at 12 km·h-1 were moderately to largely correlated with smaller peak impact and braking force (r = 0.486 and -0.500, respectively). Regarding the statistical parametric mapping analysis, most outcomes showed associations with RE at 10 km·h-1, including knee flexion (42.5%-65.5%of the gait cycle), ankle plantarflexion (32.5%-36%of the gait cycle), active force (30.5%-35%of the stance phase), and propulsion force (68%-72.5% of the stance phase). Lower energy costs at 12 km·h-1 were correlated with smaller hip flexion (5.5%-12% and 66.5%-74%) and smaller knee flexion (57%-57.5%) during the running gait cycle. Conclusions: This study indicates that biomechanical factors are associated with RE in recreational runners. To design effective training methods to improve RE, coaches and runners should focus on the sagittal plane kinematics of the hip, knee, and ankle, as well as lower vertical and horizontal kinetic parameters. [ABSTRACT FROM AUTHOR]

Studies have shown that unconventional machining offers advantages when it comes to machining ceramics in the form of higher material removal rate (MRR) and better surface finish. This present study focuses on the experimental investigations using a fibre laser to cut 7 mm thick ceramic plates used as glazed floor tiles. It involved a systematic experimental study to determine the relationships between process parameters and machining characteristics. Based on the experimental results, regression equations are developed to estimate the responses as functions of the laser process parameters and gas pressure. The developed regression equations are then used in a particle swarm optimization (PSO) technique with a MATLAB algorithm to minimize glass formation and taper angle in the cutting region which, in turn, improves productivity and surface finish. The optimal parameters of the process are found based on the minimization of the taper angle with relatively low operating energy cost. [ABSTRACT FROM AUTHOR]

The efficient operation of heating ventilation and air conditioning systems relies on advanced control strategies. However, current control methods are often limited by issues such as uncertain system parameter information and spatial coupling constraints related to the supply rate of the air supply fan. To this end, an energy joint thermal comfort management method for complex environments in multiple regions is proposed. The long-term total cost minimization of the system is established, and then the Lyapunov optimization technology is used to design the distributed control algorithm. Simulation validation shows that the proposed method reduces the energy cost by an average of 11.24% compared to other methods with a thermal discomfort cost coefficient of 0. The average temperature deviation in the area is improved by 0.15 °C and 0.68 °C, respectively. The method saves more than 10% of the total energy cost under different thermal perturbations with an average total temperature deviation of 0.04 °C. The results indicate that the proposed energy joint thermal comfort management method can flexibly balance energy costs and user thermal comfort without knowing any prior information of system parameters, which can also greatly protect user privacy information. This method has application value in the control of heating ventilation and air conditioning systems in complex environments such as commercial buildings. [ABSTRACT FROM AUTHOR]

This research explores the potential of electric field enforcement in dielectric barrier discharge using specially designed pyramid‐shaped μ‐electrodes for a plasma‐assisted nitrogen fixation process. The obtained results are compared under varying conditions, including the presence and absence of titanium dioxide (TiO2 ${TiO_2 }$), different oxygen concentrations in the nitrogen‐feeding gas, and residence time. The results demonstrate that the μ‐electrodes lead to an enhancement of nitrogen oxidation, which is further intensified by TiO2 ${TiO_2 }$. The introduction of 60–70 % oxygen with nitrogen achieves the highest level of NOX ${NO_X }$ production. The synergistic effect of plasma and the catalytic effect of TiO2 ${TiO_2 }$ increase the rate of NOX ${NO_X }$ production by 20 %, resulting in a 23 % increase in energy yield. The introduction of TiO2 ${TiO_2 }$ leads to a sharp increase in NOX ${NO_X }$ production even at lower oxygen concentrations. The crucial role played by ultraviolet light‐induced electron‐hole pairs in TiO2 ${TiO_2 }$ is highlighted to promote nitrogen oxidation. Nevertheless, it is crucial to emphasize that prolonged residence times may cause the photocatalytic effect to generate alternative byproducts rather than NOX ${NO_X }$ , consequence of excessive oxidation that could prove counterproductive. These findings emphasize the potential of plasma‐assisted nitrogen fixation technology in reducing energy costs and meeting the growing demand for sustainable nitrogen‐based fertilizers. [ABSTRACT FROM AUTHOR]

Purpose: To test the safety and feasibility of a challenging wild trekking 5-day experience and its acute effects on anthropometrics and cardiorespiratory and muscular performance in healthy older adults with mountaineering expertise. Methods: Twelve healthy active volunteers in their sixth decade of life of comparable training status, mountaineering experience and age were recruited. Before and after engaging in a 5-day wild trek ("Selvaggio Blu", Sardinia, Italy), participants underwent a comprehensive evaluation of anthropometrics, cardiorespiratory fitness, muscle strength and flexibility, balance, and lipidic profile. Results: The wild trekking was well tolerated by all participants who, however, reported moderate pain at the ankle joint (mean: 59.2 ± 13.1 mm). Following the trek, suprailiac fold decreased both in men (− 21.9%; p = 0.006) and women (− 34.5%; p = 0.007). Fat mass was also significantly reduced (men: − 8.5%; p = 0.001; women: − 6.6%; p = 0.014). Gender-based differences emerged for energy expenditure, with women displaying higher caloric expenditure to complete the trek (women: 12.88 ± 3.37 kcal/h/kg; men: 9.27 ± 0.89 kcal/h/kg). Likewise, VO2 peak increased only in women (+ 12%; p = 0.013). Center of pressure sway area during closed eyes single stance was found increased, i.e., worsened, both in men (+ 251%; p = 0.027) and women (+ 71%; p = 0.043). Conclusions: With all due caution, especially for balance and proprioception, wild trekking routes offer unique opportunities to rapidly improve anthropometrics, cardiorespiratory and muscular performance. For older adults with technical and physical preparedness for this type of demanding activity, wild trekking has the potential to evolve from a niche activity for alpine mountaineers into a safe and feasible recreational activity and leisure pursuit. [ABSTRACT FROM AUTHOR]

The purpose of this research is to provide an integrated maintenance model in the petrochemical industry. The current research is applied in terms of purpose and descriptive survey in terms of data collection method. A mixed method (qualitative and quantitative) has been used to conduct the research. The tools used in this research are researcher-made questionnaires (36 Questions), dialog with domestic and foreign professors in the field of maintenance and production, the Delphi technique (41 Maintenance managers), Field investigations (20 internal and 7 overseas petrochemical companies), and experiences and evidence obtained from 12 overhauls during 30 years. The validity was determined through experts' opinions and reliability through Cronbach's alpha evaluation. The results showed that the questionnaire has high validity and reliability. The statistical population includes experts in the field of Maintenance in industry and university, among whom 110 people were selected by targeted sampling. To conduct the research in the first stage, first by using the documentary method and content analysis and interviews with experts, the indicators and dimensions of the strong integrated maintenance and repair model were extracted and given to the experts in the form of a Likert scale for scoring; After conducting the survey, 36 components were selected, and each component of management, manpower, equipment, and knowledge had 9 sub-components. In the next step, the components and sub-components were scored and ranked using the questionnaire and the Analytical hierarchy process method. In this research, the following three results have been obtained: 1. Four main roots (Human, Management, Knowledge, and Equipment) and thirty-six sub-roots of effective maintenance. 2. The essential elements of the formula for measuring the criticality index of equipment. 3. Five indicators for measuring integrated maintenance performance. According to the calculations, the inconsistency between the vectors of each matrix is less than 0.10. Therefore, the constituent vectors of each of the formed matrices are consistent with the three results of the research and the stability of the respective comparisons is acceptable. [ABSTRACT FROM AUTHOR]

This study investigated the application of machine learning to optimise the pumping load shift of a complex dewatering system in a deep-level mine, aiming to reduce energy costs associated with the dewatering process, which consumes an average of 14% of the mine's electricity. Traditional practices, reliant on human control and simulations, often lead to inconsistent savings and occasional losses. The study employed multivariate linear regression (MLR) and extreme gradient boosting (XGBoost) on a mine dewatering system, to identify important parameters influencing the pumping load shift performance. Critical parameters significantly impacting the energy consumption of the dewatering system were identified by the best-performing model, XGBoost. Implementing a pumping schedule based on XGBoost insights resulted in consistent load shifting and enhanced energy cost savings. These findings highlight the potential of machine learning in comprehending and optimising complex systems in deep-level mines, with the case study approach proving effective in quantifying and validating real-world impacts. This approach could offer substantial energy savings through data-driven decision-making. [ABSTRACT FROM AUTHOR]

The purpose of this research is to provide an integrated maintenance model in the petrochemical industry. The current research is applied in terms of purpose and descriptive survey in terms of data collection method. A mixed method (qualitative and quantitative) has been used to conduct the research. The tools used in this research are researcher-made questionnaires (36 Questions), dialog with domestic and foreign professors in the field of maintenance and production, the Delphi technique (41 Maintenance managers), Field investigations (20 internal and 7 overseas petrochemical companies), and experiences and evidence obtained from 12 overhauls during 30 years. The validity was determined through experts' opinions and reliability through Cronbach's alpha evaluation. The results showed that the questionnaire has high validity and reliability. The statistical population includes experts in the field of Maintenance in industry and university, among whom 110 people were selected by targeted sampling. To conduct the research in the first stage, first by using the documentary method and content analysis and interviews with experts, the indicators and dimensions of the strong integrated maintenance and repair model were extracted and given to the experts in the form of a Likert scale for scoring; After conducting the survey, 36 components were selected, and each component of management, manpower, equipment, and knowledge had 9 sub-components. In the next step, the components and sub-components were scored and ranked using the questionnaire and the Analytical hierarchy process method. In this research, the following three results have been obtained: 1. Four main roots (Human, Management, Knowledge, and Equipment) and thirty-six sub-roots of effective maintenance. 2. The essential elements of the formula for measuring the criticality index of equipment. 3. Five indicators for measuring integrated maintenance performance. According to the calculations, the inconsistency between the vectors of each matrix is less than 0.10. Therefore, the constituent vectors of each of the formed matrices are consistent with the three results of the research and the stability of the respective comparisons is acceptable. [ABSTRACT FROM AUTHOR]

This study investigates the impact of insulation on energy consumption and CO2 emissions in high-rise commercial buildings across various climate zones. Through a simulation-based approach using the Hourly Analysis Program (HAP), the effectiveness of insulation in reducing energy demand and carbon emissions are evaluated. The research includes multiple climatic regions of Afghanistan, including arid, semi-arid, and mountainous zones. Methodologically, detailed building characteristics, climatic data, and insulation materials are considered, with energy modeling techniques applied to assess the performance of insulation measures. Results indicate varying degrees of energy savings and CO2 emissions reduction associated with insulation across different climate zones, in cities such as Kabul, Herat, Mazar, and Kandahar. Furthermore, the study calculates CO2 emissions reduction resulting from insulation addition, emphasizing the importance of sustainable building practices in mitigating environmental impacts. By underscoring the scientific value of this research in addressing a pressing global challenge and providing actionable insights for building design and energy policy, this study contributes to the advancement of knowledge in the field of sustainable construction and environmental engineering.

This paper presents an in-depth analysis of a Quantum-inspired Multi-objective Optimization Algorithm (QMOA) applied to a unique problem: maximizing trading profits while minimizing energy costs. Previous investigations have explored the profitability of Bitcoin, yet our research delves into its relationship with energy costs. Regarding the trade-offs, the Pareto analysis reveals that trading profit and energy cost do not strongly inversely correlate. The range of outcomes shows a relatively uniform trading profit (from 1.302,85 to 1.310,22$), but a broader variation in energy costs (from 1.141,66 to 5.657,94$). While the trading profit remains stable, there is a wide array of options for minimizing energy cost, which is influenced by various constraints and market conditions. Solutions tend to cluster more in areas of higher energy costs. However, the variability in energy costs offers Bitcoin miners choices, allowing them to tailor strategies, whether that involves prioritizing energy efficiency, profit maximization or striking a balance.

Energy consumption plays an important role in contemporary economies. Its significance extends beyond utilitarian value, impacting economic robustness, environmental protection, and residents' well-being. The escalating global energy requisites necessitate efficient energy utilization and a shift towards renewable sources to address climate change and strengthen energy independence. Developing accurate predictive models to forecast long-term energy costs and savings remains a complex problem. This paper aims to provide a methodology to identify the influence of building energy performance on real estate market efficiency, focusing on property maintenance costs. Real estate plays a crucial role in human life, serving both as a fundamental need and as a vehicle for achieving personal aspirations and secure financial investments, particularly during times of economic and social instability. Through interdisciplinary methodological architecture, this study addresses three key issues: the impact of rising energy costs on market efficiency, the responsiveness of the real estate market to energy price fluctuations, and the significance of property maintenance costs on market value. The research approach includes creating and applying AI algorithms capable of evaluating extensive datasets pertaining to real estate features. Utilizing machine learning methods, the algorithm determines the importance of energy efficiency measures as well as various other inherent and external attributes of properties. The suggested methodology provides a novel approach to improve the effectiveness of market efficiency analysis. [ABSTRACT FROM AUTHOR]

Plasma-assisted nitrogen fixation has emerged as a promising alternative to conventional nitrogen fixation methods. In this study, we investigate the feasibility of plasma-assisted nitrogen fixation using an AC-driven dielectric barrier discharge generated from the micro-tips of a specially designed fast-modulated pyramid-shaped electrode. The obtained result is compared with the conventional flat electrode. Our results demonstrate that pyramid-shaped micro-tip electrodes can excite more nitrogen molecules than flat electrodes. Thus, pyramid electrodes have 58% more nitrogen oxides yield efficiency at 32% less energy cost. The highest nitrogen fixation is attained at 60% to 70% of oxygen concentration in nitrogen-feeding gas. These findings suggest that discharge through microtip is a promising and viable technology that could play a significant role in reducing the energy cost of the plasma-assisted nitrogen fixation method to meet the growing demand for sustainable nitrogen-based fertilizers. [ABSTRACT FROM AUTHOR]

The available literature emphasizes that by 2040, electric vehicles may constitute up to 50% of the fleet of all passenger vehicles. This process will be one of the elements of the energy transformation and, at the same time, consistent with the idea of sustainable transport. As part of this research, the actual energy consumption and the range of electric vehicles were determined. This research was carried out using a selected group of electric cars from the most popular segments of passenger cars. The calculations were based on three charging scenarios: a home electrical network, a public alternating current (AC) charging station that allows charging with single-phase alternating current or alternating current, and a public direct current (DC) charging station that allows charging with direct current. The obtained results were compared with the results of cars with internal combustion and diesel engines after driving a 100-kilometer section of the route. In a broader scope, this research addresses the entities responsible for the energy transformation and the electromobility development strategy. In a narrower sense, vehicle users are considering the purchase of this type of vehicle for political, economic and technological reasons. [ABSTRACT FROM AUTHOR]

This article concentrates on the fixed‐time synchronization (FTS) and energy cost (EC) problems of delayed coupled neural networks (NNs). A switching controller is proposed and some sufficient conditions are advanced to ensure FTS of delayed coupled NNs based on the comparison theorem. Following that, the required EC is estimated during the control process. The main results of FTS and EC for considered NNs are obtained based on the Lyapunov functions in the sense of vector 1‐norm, 2‐norm, and ∞$$ \infty $$‐norm, respectively. Under the same controller parameters, this article shows that the minimum estimation of settling time and EC are sometimes not in one norm sense. Finally, numerical examples are given to show the effectiveness of theoretical results. [ABSTRACT FROM AUTHOR]

Mobile devices (MDs) are becoming more prevalent and their battery life is optimised by offloading tasks to cloud servers. However, communication costs must be considered when offloading tasks. To make task offloading worthwhile, it is important to measure the energy consumed during communication activities. Thus, a heterogeneous framework is developed to enhance the energy efficiency of smartphones by analysing parameters such as task and non-task offloading, local cloudlets, radio access networks and remote cloud servers. This paper proposes a task offloading framework that uses a novel algorithm, the Hybrid Red Fox Flow Direction-based Ensemble SVM Forest Classifier, to enhance the system parameters and schedule tasks in offloading cloud computing conditions. The multi-objective function aims to improve user satisfaction by maximising resource utilisation and minimising function. The framework was tested in the Cloudsim simulation tool and compared with different techniques, with the results demonstrating its superiority in terms of energy efficiency and system performance. The proposed framework can optimise the energy efficiency of MDs and improve battery life. [ABSTRACT FROM AUTHOR]

Memory Hard Functions (MHFs) have been proposed as an answer to the growing inequality between the computational speed of general purpose CPUs and ASICs. MHFs have seen widespread applications including password hashing, key stretching and proofs of work. Several metrics have been proposed to quantify the memory hardness of a function. Cumulative memory complexity (CMC) quantifies the cost to acquire/build the hardware to evaluate the function repeatedly at a given rate. By contrast, bandwidth hardness quantifies the energy costs of evaluating this function. Ideally, a good MHF would be both bandwidth hard and have high CMC. While the CMC of leading MHF candidates is well understood, little is known about the bandwidth hardness of many prominent MHF candidates. Our contributions are as follows: First, we provide the first reduction proving that, in the parallel random oracle model (pROM), the bandwidth hardness of a data-independent MHF (iMHF) is described by the red-blue pebbling cost of the directed acyclic graph associated with that iMHF. Second, we show that the goals of designing an MHF with high CMC/bandwidth hardness are well aligned. Any function (data-independent or not) with high CMC also has relatively high bandwidth costs. Third, we prove that in the pROM the prominent iMHF candidates such as Argon2i, aATSample and DRSample are maximally bandwidth hard. Fourth, we prove the first unconditional tight lower bound on the bandwidth hardness of a prominent data-dependent MHF called Scrypt in the pROM. Finally, we show the problem of finding the minimum cost red–blue pebbling of a directed acyclic graph is NP-hard. [ABSTRACT FROM AUTHOR]

Exploration of the green flexible job-shop scheduling problem is essential for enterprises aiming for sustainable practices, including energy conservation, emissions reduction, and enhanced economic and social benefits. While existing research has predominantly focused on carbon emissions or energy consumption as green scheduling objectives, this paper addresses the broader scope by incorporating the impact of variable energy prices on energy cost. Through the introduction of an energy cost model based on time-of-use electricity pricing, the study formulates a multi-objective optimization model for green flexible job-shop scheduling. The objectives include minimizing cost, reducing carbon emissions, and maximizing customer satisfaction. To prevent premature convergence and maintain population diversity, an enhanced genetic algorithm is employed for solving. The validation of the algorithm's effectiveness is demonstrated through specific examples, providing decision results for optimal scheduling under various weight combinations. The research outcomes hold substantial practical value as they can significantly reduce energy expenses, lower carbon emissions, and elevate customer satisfaction while safeguarding production efficiency. This contributes to enhancing the market competitiveness and green brand image of businesses. [ABSTRACT FROM AUTHOR]

Background: Prior studies investigated selected discrete sagittal‐plane outcomes (e.g., peak knee flexion) in relation to running economy, hereby discarding the potential relevance of running technique parameters during noninvestigated phases of the gait cycle and in other movement planes. Purpose: Investigate which components of running technique distinguish groups of runners with better and poorer economy and higher and lower weekly running distance using an artificial neural network (ANN) approach with layer‐wise relevance propagation. Methods: Forty‐one participants (22 males and 19 females) ran at 2.78 m∙s−1 while three‐dimensional kinematics and gas exchange data were collected. Two groups were created that differed in running economy or weekly training distance. The three‐dimensional kinematic data were used as input to an ANN to predict group allocations. Layer‐wise relevance propagation was used to determine the relevance of three‐dimensional kinematics for group classification. Results: The ANN classified runners in the correct economy or distance group with accuracies of up to 62% and 71%, respectively. Knee, hip, and ankle flexion were most relevant to both classifications. Runners with poorer running economy showed higher knee flexion during swing, more hip flexion during early stance, and more ankle extension after toe‐off. Runners with higher running distance showed less trunk rotation during swing. Conclusion: The ANN accuracy was moderate when predicting whether runners had better, or poorer running economy, or had a higher or lower weekly training distance based on their running technique. The kinematic components that contributed the most to the classification may nevertheless inform future research and training. [ABSTRACT FROM AUTHOR]

Abstract Background Walking speed and energy economy tend to decline with age. Lower-limb exoskeletons have demonstrated potential to improve either measure, but primarily in studies conducted on healthy younger adults. Promising techniques like optimization of exoskeleton assistance have yet to be tested with older populations, while speed and energy consumption have yet to be simultaneously optimized for any population. Methods We investigated the effectiveness of human-in-the-loop optimization of ankle exoskeletons with older adults. Ten healthy adults > 65 years of age (5 females; mean age: 72 ± 3 yrs) participated in approximately 240 min of training and optimization with tethered ankle exoskeletons on a self-paced treadmill. Multi-objective human-in-the-loop optimization was used to identify assistive ankle plantarflexion torque patterns that simultaneously improved self-selected walking speed and metabolic rate. The effects of optimized exoskeleton assistance were evaluated in separate trials. Results Optimized exoskeleton assistance improved walking performance for older adults. Both objectives were simultaneously improved; self-selected walking speed increased by 8% (0.10 m/s; p = 0.001) and metabolic rate decreased by 19% (p = 0.007), resulting in a 25% decrease in energetic cost of transport (p = 8e-4) compared to walking with exoskeletons applying zero torque. Compared to younger participants in studies optimizing a single objective, our participants required lower exoskeleton torques, experienced smaller improvements in energy use, and required more time for motor adaptation. Conclusions Our results confirm that exoskeleton assistance can improve walking performance for older adults and show that multiple objectives can be simultaneously addressed through human-in-the-loop optimization.

The demand response and peak power limiting could potentially reduce the peak power and energy demand. This study examines the effect of rule-based demand response and peak power limiting on the peak power and energy demand of heating. Study was conducted as a co-simulation where buildings and district heating production were simulated separately but both inclusively. Results indicate that demand response provides 2.8–4.7% energy saving and 2.3–3.4% total district heating cost saving potential. Moreover, according to the simulations, demand response provides 32% emission reduction in district heating production in contrast to the reference case. Peak power limiting provides significant reduction in the peak power and district heating base cost. However, its ability to provide additional reduction in the energy demand and emissions is confined compared to the demand response due to the effective time of the limit. Chosen acceptable temperature range can be maintained decently.

The main purpose of this study is to present family farms as consumers and producers of renewable energies which provide them with an opportunity to reduce operating costs. The time scope of the study is 2014–2022, and the Farm Accountancy Data Network is used as the data source. The following research methods were employed: comparative and descriptive analysis, intensity indicators, ranking assignment and panel regression. Based on the values of energy output and energy costs, the rankings revealed a strong position of the Netherlands and Germany. As demonstrated by the study, energy production and consumption volumes depend on the farms’ economic size, but are not impacted by production type. Another finding is that energy production covers only one-third of its costs. Also, both production volumes and costs were on a growth path on a year-over-year basis, with similar growth ratios. The European Union’s leaders in energy consumption and production are the Netherlands, Germany, Belgium, Denmark, Czech Republic, Hungary, Luxembourg, Slovakia and Sweden. The study included the structuring of panel models for energy output and costs and identified their determinants. Energy output depends on total inputs and grows as they grow. Energy costs, in turn, are related to utilized agricultural area, total output and family farm income. An important limitation of this study is that FADN is a provider of high-level data. Hence, it is impossible to tell what specific sources of renewable energy are used by farms, and how they are affected by such exogenous factors as climate, earmarked subsidies or energy policy. The findings from this study are discussed in the context of the European Commission’s recommendations laid down in the Bioeconomy Strategy of the EU (2013), the Seventh Environment Action Program, the New Innovation Agenda of the European Union, the Report “Transforming Our World: the United Nations 2030 Agenda for Sustainable Development” and the Circular Economy Action Plan.

The aim of the study was to assess the influence of year-long training of race walkers on physiological cost and total energy center of mass (CoM). The assessment performed was based on indicating the differences between the resulting energy cost in a group of elite race walkers walking at technical, threshold, and racing speeds calculated by physiological and biomechanical methods before beginning and after finishing a year-long training cycle. The study involved 12 competitive race walkers who had achieved champion or international champion level. Their aerobic endurance was determined by means of a direct method, applying an incremental exercise test on the treadmill. The gait of the participants was recorded using the 3D Vicon analysis system. Changes in mechanical energy amounted to the value of the total external work of the muscles needed to accelerate and lift the center of mass during a normalized gait cycle. The highest influence on the total external work increase for increasing speeds of gait in both examinations was attributed to the changes in the kinetic energy resulting from the center of mass movement. A statistically significant decrease of the mean value of total external work for racing speed was observed in the second examination (p < 0.001). An approx. 8% decrease (NS) of EE energy cost, standardized by body mass and distance covered, was found between the first and second examinations. The energy cost and total external work were significantly differentiated by the walkers’ gait speeds (p < 0.05–0.001). The energy cost significantly differed from the total external work at p < 0.001.

Top marine predators, such as odontocetes, pinnipeds, and seabirds, are known to forage around fishing boats as fishermen aggregate and/or discard their prey. Recently, incidents of humpback whales interacting with fishing boats have been reported. However, whether humpback whales utilise discard fish as a food source and how they forage around fishing boats is unknown. This study reports, for the first time, the foraging behaviour of a humpback whale around fishing boats. Three whales were tagged using a suction‐cup tag containing a video camera, and a behavioural data logger in the coastal area of Tromsø, Norway. Video data from one tagged whale showed that the whale remained in close vicinity of fishing boats for 43 min, and revealed the presence of large numbers of dead fish, fish‐eating killer whales, fishing boats, and fishing gear. In waters with large numbers of dead fish, the whale raised its upper jaw, a motion associated with engulfing discard fish from fishing boats, and this feeding behaviour differed markedly from lunge‐feeding observed in two other whales in the same area. This behaviour was defined as "pick‐up feeding". No lunge feeding was seen on the data logger when the whale foraged around fishing boats. This study highlights a novel humpback whale foraging strategy: low energy gain from scattered prey but also low energy costs as high‐energy lunge feeding is not required. [ABSTRACT FROM AUTHOR]

Automatic guided vehicles (AGVs) in the horizontal area play a crucial role in determining the operational efficiency of automated container terminals (ACTs). To improve the operational efficiency of an ACT, it is essential to decrease the impact of battery capacity limitations on AGV scheduling. To address this problem, this paper introduces battery swapping and opportunity charging modes into the AGV system and proposes a new AGV scheduling problem considering the hybrid mode. Firstly, this study describes the AGV scheduling problem of the automated container terminals considering both loading and unloading tasks under the hybrid mode of battery swapping and charging. Thereafter, a mixed-integer programming model is established to minimize the sum of energy costs and delay costs. Secondly, an effective adaptive large neighborhood search algorithm is proposed to solve the problem, in which the initial solution construction, destroy operators, and repair operators are designed according to the hybrid mode. Finally, numerical experiments are conducted to analyze the effectiveness of the model and the optimization performance of the algorithm. The results demonstrate that the hybrid mode of battery swapping and charging can effectively reduce the number of battery swapping times and scheduling costs compared to the existing mode. [ABSTRACT FROM AUTHOR]

The hydrogen fuel cell vehicle is rapidly developing in China for carbon reduction and neutrality. This paper evaluated the life-cycle cost and carbon emission of hydrogen energy via lots of field surveys, including hydrogen production and packing in chlor-alkali plants, transport by tube trailers, storage and refueling in hydrogen refueling stations (HRSs), and application for use in two different cities. It also conducted a comparative study for battery electric vehicles (BEVs) and internal combustion engine vehicles (ICEVs). The result indicates that hydrogen fuel cell vehicle (FCV) has the best environmental performance but the highest energy cost. However, a sufficient hydrogen supply can significantly reduce the carbon intensity and FCV energy cost of the current system. The carbon emission for FCV application has the potential to decrease by 73.1% in City A and 43.8% in City B. It only takes 11.0%–20.1% of the BEV emission and 8.2%–9.8% of the ICEV emission. The cost of FCV driving can be reduced by 39.1% in City A. Further improvement can be obtained with an economical and "greener" hydrogen production pathway. [ABSTRACT FROM AUTHOR]

Background: Walking speed and energy economy tend to decline with age. Lower-limb exoskeletons have demonstrated potential to improve either measure, but primarily in studies conducted on healthy younger adults. Promising techniques like optimization of exoskeleton assistance have yet to be tested with older populations, while speed and energy consumption have yet to be simultaneously optimized for any population. Methods: We investigated the effectiveness of human-in-the-loop optimization of ankle exoskeletons with older adults. Ten healthy adults > 65 years of age (5 females; mean age: 72 ± 3 yrs) participated in approximately 240 min of training and optimization with tethered ankle exoskeletons on a self-paced treadmill. Multi-objective human-in-the-loop optimization was used to identify assistive ankle plantarflexion torque patterns that simultaneously improved self-selected walking speed and metabolic rate. The effects of optimized exoskeleton assistance were evaluated in separate trials. Results: Optimized exoskeleton assistance improved walking performance for older adults. Both objectives were simultaneously improved; self-selected walking speed increased by 8% (0.10 m/s; p = 0.001) and metabolic rate decreased by 19% (p = 0.007), resulting in a 25% decrease in energetic cost of transport (p = 8e-4) compared to walking with exoskeletons applying zero torque. Compared to younger participants in studies optimizing a single objective, our participants required lower exoskeleton torques, experienced smaller improvements in energy use, and required more time for motor adaptation. Conclusions: Our results confirm that exoskeleton assistance can improve walking performance for older adults and show that multiple objectives can be simultaneously addressed through human-in-the-loop optimization. [ABSTRACT FROM AUTHOR]

This study presents insights into the use of activated Al2O3 ${\text{Al}}_{2}{{\rm{O}}}_{3}$ catalysts to improve the energy efficiency of NOx ${\text{NO}}_{x}$ production in atmospheric pressure air plasma. The introduction of catalysts in the direct current glow discharge system reduces the energy cost of NOx ${\text{NO}}_{x}$ production by up to 45% at low gas flow rates. Notably, even when positioned away from the plasma zone, the catalyst enhanced NOx ${\text{NO}}_{x}$ production, suggesting a significant role for the catalytic activation of downstream neutral species. The study also introduced a novel approach involving an air plasma jet infused with floating catalyst powder. This method significantly increased energy efficiency at higher discharge currents, with an associated energy cost of 2.9 MJ/mol for NOx ${\text{NO}}_{x}$ production. [ABSTRACT FROM AUTHOR]

The demand response and peak power limiting could potentially reduce the peak power and energy demand. This study examines the effect of rule-based demand response and peak power limiting on the peak power and energy demand of heating. Study was conducted as a co-simulation where buildings and district heating production were simulated separately but both inclusively. Results indicate that demand response provides 2.8–4.7% energy saving and 2.3–3.4% total district heating cost saving potential. Moreover, according to the simulations, demand response provides 32% emission reduction in district heating production in contrast to the reference case. Peak power limiting provides significant reduction in the peak power and district heating base cost. However, its ability to provide additional reduction in the energy demand and emissions is confined compared to the demand response due to the effective time of the limit. Chosen acceptable temperature range can be maintained decently. [ABSTRACT FROM AUTHOR]

The aim of this study is to investigate the performance of advanced electrocoagulation (EC) process for the treatment of olive mill wastewater. In EC process, iron plates were used as electrodes, and peroxydisulfate (PS) and peroxymonosulfate (PMS) were added as oxidants. The effects of the initial pH value, current density, oxidant dose, and electrolysis time were optimized for pollutant removal from olive mill wastewater by EC‐PS and EC‐PMS processes. Control experiments showed that addition of oxidants to the conventional EC process increased the pollutant removal efficiency. Classical optimization method was used to determine optimum conditions, which were initial pH 4, current density 40 mA/cm2, oxidant dose 5 g/L, and electrolysis time 30 min for both processes. Under these conditions, EC‐PS and EC‐PMS processes achieved 50.5% and 48.9% chemical oxygen demand (COD), 93.8% and 89.3% total phenol, 87.7% and 83% UV254, and 74.5% and 64.1% total suspended solid removal efficiencies. Quenching experiments were performed to determine the dominant radical species participating in the processes. It was observed that hydroxyl and sulfate radicals were involved in both processes but hydroxyl radicals were more active. Specific energy consumption was calculated as 5.90 kWh/kg COD for EC process, 4.95 kWh/kg COD for EC‐PS process, and 5.20 kWh/kg COD for EC‐PMS process. The organic removal/sludge ratio of EC‐PS process was found to be higher with 17.5 g/L value. Although the application of EC‐PS and EC‐PMS processes alone is insufficient to meet the discharge limits, they have been found to be effective in olive mill wastewater treatment. Practitioner Points: Peroxydisulfate (PS) and peroxymonosulfate (PMS)‐based advanced electrocoagulation (EC) was used in olive mill wastewater treatment.50.5% chemical oxygen demand (COD), 93.8% TP, 87.7% UV254, and 74.5% TSS removals were achieved by EC‐PS.48.9% COD, 89.3% TP, 83% UV254, and 64.1% TSS removals were obtained by EC‐PMS.Hydroxyl and sulfate radicals were involved in both processes. [ABSTRACT FROM AUTHOR]

Node capture attacks compromise the integrity and confidentiality of networks by capturing nodes within them and obtaining cryptographic keys through wireless sensor network links. Adversarial modelling research is being conducted in order to develop efficient solutions for WSN security. Based on random key distribution scheme, an optimal graph-based technique is used to imitate node capture attack. The approach to estimating destructiveness is referred after evaluation of the relationships between keys to paths and nodes that uses graph-based modelling. The most destructiveness among all captured nodes is then secured through an optimal dominant graph (ODG), that simultaneously enhances attacking efficiency and speeds up execution. To examine the functionality of ODG with regard to the effectiveness within network, we created optimal attacking graphs, especially the optimal key graph (OKG) and optimal crossover graph (OCG). Proposed model multi objective optimization dominating algorithm (MOODA) in order to produce a path vulnerability matrix with the best possible accuracy using different objective functions that consist of multiple objectives, including dominating set of nodes, node contribution, key contribution, cost and crossover edges, to determine optimal node. The proposed matrix-based attack model by taking advantage of multiple vulnerabilities in the networks. We control a variety of processes to monitor system performance. Results show that MOODA obtain better result in increases attacking performance, decreases the total rounds, reduces accessing time, and saves cost of energy than other state of the art methods. [ABSTRACT FROM AUTHOR]

Air conditioning (AC) is a key driver to produce electricity consumption, particularly in residential buildings. In Indonesia, the electricity bill during pandemic covid-19 has increased to a high level on hot days. This is because during these periods many consumers applied their AC for a long time at the same time. It is therefore essential to develop an innovative model to control the electricity peak price and keep a comfortable room during hot days. Many previous studies have confirmed that applied evaporative cooling or other technologies can minimize the whole consumption and cost. This research aims to design a pre-cooling model (PM) for AC to avoid high electricity prices at midday during hot days. To achieve this goal a mathematical model was developed to define the energy cost (EC) and total cost (TC) for AC during the hot season. Under numerical optimization, the EC can be minimized when a spike may occur due to increased temperature at midday for a half hour (0.5 h) and one hour (1 h) spike cases. To justify this model, a PM was applied for two different building characteristics. As a result, the benefits of a PM if a spike occurs for 0.5 h and 1 h were achieved, such as IDR 10,061 (30.43 %) and IDR 10,693 (24.44 %) for building-1; IDR 12,071 (37.40 %) and IDR 14,844 (34.97 %) for building-2. In addition, the TC considering the probability of a spike of 0.5 h and 1 h if the spike occurs every five minutes were IDR 45,247 and IDR 38,287 for building-1 and building-2, respectively.

Abstract Buildings are responsible for about one-third of industrialised countries’ overall energy consumption and greenhouse gas emissions. As if this was not enough, recently, energy prices significantly increased and affected all economic areas. Making buildings more efficient and effective is the step needed toward cost reductions. Key enablers of cost-effectiveness are leveraging batteries, awareness of and adaptability to energy prices, and integrating powerful reasoning techniques to optimally and flexibly operate buildings. Researchers have tackled many of these aspects using a variety of approaches. Whereas a less investigated one is that of AI planning to coordinate actions and save energy in buildings. However, generating plans based on signals of energy prices and leveraging batteries is still an open research problem. To address this high-potential aspect, we engineer an AI planning system for improving the energy-cost effectiveness in buildings by coordinating the building’s operation based on day-ahead prices and the use of a battery, all without sacrificing the comfort of building occupants. We propose to exploit temporal planning due to its powerful modelling and reasoning features, especially in explicitly addressing time. We evaluate the effectiveness of the system in several scenarios with varying building environmental conditions. We compare the energy cost from using our planning system to a baseline cost, where we record a reduction of 43rage in favour of our system.

In parallel and distributed computing, cloud computing is progressively replacing the traditional computing paradigm. The cloud is made up of a set of virtualized resources in a data center that can be configured according to users’ needs. In other words, cloud computing faces the problem of a huge number of users requesting unlimited jobs for execution on a limited number of resources, which increases energy consumption and the network cost of the system. This study provides a complete analysis of classic scheduling techniques specifically for handling data-intensive workloads to see the effectiveness of the energy and network costs of the system. The workload is selected from a real-world data center. Moreover, this study offers the pros and cons of several classical heuristics-based job scheduling techniques that take into account the time and cost of transferring data from multiple sources. This study is useful for selecting appropriate scheduling techniques for appropriate environments.

Purpose: To investigate the acute effect of repeated-sprint activity (RSA) on change-of-direction economy (assessed using shuttle running economy [SRE]) in soccer players and explore neuromuscular and cardiorespiratory characteristics that may modulate this effect. Methods: Eleven young elite male soccer players (18.5 [1.4] y old) were tested on 2 different days during a 2-week period in their preseason. On day 1, lower-body stiffness, power and force were assessed via countermovement jumps, followed by an incremental treadmill test to exhaustion to measure maximal aerobic capacity. On day 2, 2 SRE tests were performed before and after a repeated-sprint protocol with heart rate, minute ventilation, and blood lactate measured. Results: Pooled group analysis indicated no significant changes for SRE following RSA due to variability in individual responses, with a potentiation or impairment effect of up to 4.5% evident across soccer players. The SRE responses to RSA were significantly and largely correlated to players' lower-body stiffness (r =.670; P =.024), and moderately (but not significantly) correlated to players' force production (r = −.455; P =.237) and blood lactate after RSA (r =.327; P =.326). Conclusions: In summary, SRE response to RSA in elite male soccer players appears to be highly individual. Higher lower-body stiffness appears as a relevant physical contributor to preserve or improve SRE following RSA. [ABSTRACT FROM AUTHOR]