Local O2 concentrating boosts the electro-Fenton process for energy-efficient water remediation.

The electro-Fenton process is a state-of-the-art water treatment technology used to remove organic contaminants. However, the low O2 utilization efficiency (OUE, <1%) and high energy consumption remain the biggest obstacles to practical application. Here, we propose a local O2 concentrating (LOC) approach to increase the OUE by over 11-fold compared to the conventional simple O2 diffusion route. Due to the well-designed molecular structure, the LOC approach enables direct extraction of O2 from the bulk solution to the reaction interface; this eliminates the need to pump O2/air to overcome the sluggish O2 mass transfer and results in high Faradaic efficiencies (~50%) even under natural air diffusion conditions. Long-term operation of a flow-through pilot device indicated that the LOC approach saved more than 65% of the electric energy normally consumed in treating actual industrial wastewater, demonstrating the great potential of this system-level design to boost the electro-Fenton process for energy-efficient water remediation.

Aging, generational shifts, and energy consumption in urban China.

China is recognized as the largest energy consumer and is also the country with the largest and fastest-aging population. Ongoing demographic changes may reshape China's household-based energy consumption patterns because of the large gap in consumption behavior between the elderly and the young as well as varying attitudes toward the environment among generations. However, when the impact of China's aging population on energy consumption is projected, the heterogeneous cognitive norms of generations in the process of demographic transition are not well understood. In this study, we assessed the future impact of China's demographic transition on energy consumption using a proposed theoretical framework to distinguish between age and generational effects. Specifically, we used age-period-cohort (APC) detrended analysis to estimate age and generational effects based on China's urban household survey data from 1992 to 2015. The results indicated large differences in energy use propensity across ages and generations. The elderly and younger generations tended to be energy-intensive consumers, resulting in higher energy consumption in this aging society. Our results consequently show that future changes in China's elderly population will result in a substantial increase in energy consumption. By 2050, the changing consumption share of the elderly population will account for ∼17 to 26% of total energy consumption in the residential sector, which is close to 115 million tons of standard coal (Mtce). These findings highlight the need to interlace environmental education policies and demographic transitions to promote energy conservation behavior in children and youth for low-carbon, sustainable development.

Bioinspired zero-energy thermal-management device based on visible and infrared thermochromism for all-season energy saving.

Radiative thermal management provides a zero-energy strategy to reduce the demands of fossil energy for active thermal management. However, whether solar heating or radiative cooling, one-way temperature control will exacerbate all-season energy consumption during hot summers or cold winters. Inspired by the Himalayan rabbit's hair and Mimosa pudica's leaves, we proposed a dual-mode thermal-management device with two differently selective electromagnetic spectrums. The combination of visible and infrared "thermochromism" enables this device to freely switch between solar heating and radiative cooling modes by spontaneously perceiving the temperature without any external energy consumption. Numerical prediction shows that a dual-mode device exhibits an outstanding potential for all-season energy saving in terms of thermal management beyond most static or single-wavelength, range-regulable, temperature-responsive designs. Such a scalable and cost-efficient device represents a more efficient radiative thermal-management strategy toward applying in a practical scenario with dynamic daily and seasonal variations.

Reconfigurable aJ-Level Ferroelectric Transistor-Based Boolean Logic for Logic-in-Memory.

Logic-in-memory (LIM) architecture holds great potential to break the von Neumann bottleneck. Despite the extensive research on novel devices, challenges persist in developing suitable engineering building blocks for such designs. Herein, we propose a reconfigurable strategy for efficient implementation of Boolean logics based on a hafnium oxide-based ferroelectric field effect transistor (HfO2-based FeFET). The logic results are stored within the device itself (in situ) during the computation process, featuring the key characteristics of LIM. The fast switching speed and low power consumption of a HfO2-based FeFET enable the execution of Boolean logics with an ultralow energy of lower than 8 attojoule (aJ). This represents a significant milestone in achieving aJ-level computing energy consumption. Furthermore, the system demonstrates exceptional reliability with computing endurance exceeding 108 cycles and retention properties exceeding 1000 s. These results highlight the remarkable potential of a FeFET for the realization of high performance beyond the von Neumann LIM computing architectures.

Calcium-induced upregulation of energy metabolism heats neurons during neural activity.

Cellular temperature affects every biochemical reaction, underscoring its critical role in cellular functions. In neurons, temperature not only modulates neurotransmission but is also a key determinant of neurodegenerative diseases. Considering that the brain consumes a disproportionately high amount of energy relative to its weight, neural circuits likely generate a lot of heat, which can increase cytosolic temperature. However, the changes in temperature within neurons and the mechanisms of heat generation during neural excitation remain unclear. In this study, we achieved simultaneous imaging of Ca2+ and temperature using the genetically encoded indicators, B-GECO and B-gTEMP. We then compared the spatiotemporal distributions of Ca2+ responses and temperature. Following neural excitation induced by veratridine, an activator of the voltage-gated Na+ channel, we observed an approximately 2 °C increase in cytosolic temperature occurring 30 s after the Ca2+ response. The temperature elevation was observed in the non-nuclear region, while Ca2+ increased throughout the cell body. Moreover, this temperature increase was suppressed under Ca2+-free conditions and by inhibitors of ATP synthesis. These results indicate that Ca2+-induced upregulation of energy metabolism serves as the heat source during neural excitation.

Scaling Supercapacitive Swing Adsorption of CO2 Using Bipolar Electrode Stacks.

Supercapacitive swing adsorption (SSA) modules with bipolar stacks having 2, 4, 8, and 12 electrode pairs made from BPL 4 × 6 activated carbon are constructed and tested for carbon dioxide capture applications. Tests are performed with simulated flue gas (15%CO2 /85%N2) at 2, 4, 8, and 12 V, respectively. Reversible adsorption with sorption capacities (≈58 mmol kg-1) and adsorption rates (≈38 µmol kg-1 s-1) are measured for all stacks. The productivity scales with the number of cells in the module, and increases from 70 to 390 mmol h-1 m-2. The energy efficiency and energy consumption improve with increasing number of bipolar electrodes from 67% to 84%, and 142 to 60 kJ mol-1, respectively. Overall, the results show that SSA modules with bipolar electrodes can be scaled without reducing the adsorptive performance, and with improvement of energetic performance.

Attojoule Hexagonal Boron Nitride-Based Memristor for High-Performance Neuromorphic Computing.

In next-generation neuromorphic computing applications, the primary challenge lies in achieving energy-efficient and reliable memristors while minimizing their energy consumption to a level comparable to that of biological synapses. In this work, hexagonal boron nitride (h-BN)-based metal-insulator-semiconductor (MIS) memristors operating is presented at the attojoule-level tailored for high-performance artificial neural networks. The memristors benefit from a wafer-scale uniform h-BN resistive switching medium grown directly on a highly doped Si wafer using metal-organic chemical vapor deposition (MOCVD), resulting in outstanding reliability and low variability. Notably, the h-BN-based memristors exhibit exceptionally low energy consumption of attojoule levels, coupled with fast switching speed. The switching mechanisms are systematically substantiated by electrical and nano-structural analysis, confirming that the h-BN layer facilitates the resistive switching with extremely low high resistance states (HRS) and the native SiOx on Si contributes to suppressing excessive current, enabling attojoule-level energy consumption. Furthermore, the formation of atomic-scale conductive filaments leads to remarkably fast response times within the nanosecond range, and allows for the attainment of multi-resistance states, making these memristors well-suited for next-generation neuromorphic applications. The h-BN-based MIS memristors hold the potential to revolutionize energy consumption limitations in neuromorphic devices, bridging the gap between artificial and biological synapses.

Reducing energy consumption in musculoskeletal MRI using shorter scan protocols, optimized magnet cooling patterns, and deep learning sequences.

OBJECTIVES: The unprecedented surge in energy costs in Europe, coupled with the significant energy consumption of MRI scanners in radiology departments, necessitates exploring strategies to optimize energy usage without compromising efficiency or image quality. This study investigates MR energy consumption and identifies strategies for improving energy efficiency, focusing on musculoskeletal MRI. We assess the potential savings achievable through (1) optimizing protocols, (2) incorporating deep learning (DL) accelerated acquisitions, and (3) optimizing the cooling system. MATERIALS AND METHODS: Energy consumption measurements were performed on two MRI scanners (1.5-T Aera, 1.5-T Sola) in practices in Munich, Germany, between December 2022 and March 2023. Three levels of energy reduction measures were implemented and compared to the baseline. Wilcoxon signed-rank test with Bonferroni correction was conducted to evaluate the impact of sequence scan times and energy consumption. RESULTS: Our findings showed significant energy savings by optimizing protocol settings and implementing DL technologies. Across all body regions, the average reduction in energy consumption was 72% with DL and 31% with economic protocols, accompanied by time reductions of 71% (DL) and 18% (economic protocols) compared to baseline. Optimizing the cooling system during the non-scanning time showed a 30% lower energy consumption. CONCLUSION: Implementing energy-saving strategies, including economic protocols, DL accelerated sequences, and optimized magnet cooling, can significantly reduce energy consumption in MRI scanners. Radiology departments and practices should consider adopting these strategies to improve energy efficiency and reduce costs. CLINICAL RELEVANCE STATEMENT: MRI scanner energy consumption can be substantially reduced by incorporating protocol optimization, DL accelerated acquisition, and optimized magnetic cooling into daily practice, thereby cutting costs and environmental impact. KEY POINTS: Optimization of protocol settings reduced energy consumption by 31% and imaging time by 18%. DL technologies led to a 72% reduction in energy consumption of and a 71% reduction in time, compared to the standard MRI protocol. During non-scanning times, activating Eco power mode (EPM) resulted in a 30% reduction in energy consumption, saving 4881 € ($5287) per scanner annually.

Caffeine: a potential mechanism for anti-obesity.

Obesity refers to the excessive accumulation of fat caused by a long-term imbalance between energy intake (EI) and energy expenditure (EE). Over recent years, obesity has become a major public health challenge. Caffeine is a natural product that has been demonstrated to exert anti-obesity effects; however, the mechanisms responsible for the effect of caffeine on weight loss have yet to be fully elucidated. Most obesity-related deaths are due to cardiovascular disease. Recent research has demonstrated that caffeine can reduce the risk of death from cardiovascular disease; thus, it can be hypothesized that caffeine may represent a new therapeutic agent for weight loss. In this review, we synthesize data arising from clinical and animal studies over the last decade and discuss the potential mechanisms by which caffeine may induce weight loss, focusing particularly on increasing energy consumption, suppressing appetite, altering lipid metabolism, and influencing the gut microbiota. Finally, we summarize the major challenges associated with caffeine and anti-obesity research and highlight possible directions for future research and development.

Savings in CT Net Scan Energy Consumption: Assessment Using Dose Report Metrics and Comparison With Savings in Idle State Energy Consumption.

BACKGROUND. CT scanners' net scan state (i.e., image acquisition period) represents a potential target for energy savings through protocol adjustments. However, gauging CT energy savings is difficult without installing costly energy monitors. OBJECTIVE. The purpose of this article was to assess correlations between CT dose report metrics and energy consumption during the system net scan state and to compare theoretic energy savings from matching percentage reductions in energy consumption during net scan and idle system states. METHODS. Current sensors were installed on a single CT scanner. A phantom was scanned at varying kilovoltage settings and effective tube current-rotation time settings. A retrospective assessment was performed in 32 patients (mean age, 61.2 ± 17.9 [SD] years; 17 men, 15 women) who underwent 32 single-energy noncontrast abdominopelvic CT examinations from September 22, 2021, to September 27, 2021, on the same scanner. Correlations between dose report metrics and net scan energy consumption were assessed in the phantom and clinical scans, and equations were generated to derive net scan energy consumption from DLP. An additional retrospective assessment was performed in 1355 patients (mean age, 59.3 ± 16.9 years; 663 men, 692 women) who underwent 1728 single-energy noncontrast abdominopelvic CT examinations from January 1, 2021, through December 31, 2021, on the same scanner to estimate net scan energy consumption per examination. This information was integrated with literature-derived values to compare estimated annual national energy savings resulting from 20% reductions in net scan and idle state energy consumption. RESULTS. Net scan energy consumption in the phantom scans showed high linear correlation with DLP (R2 = 0.87), and, in the clinical scans, high linear correlation with CTDIvol (R2 = 0.89) and very high linear correlation with DLP (R2 = 0.92). When combining mean DLP in examinations performed in the 1-year interval, an equation relating DLP and net scan energy consumption and literature values estimated that annual national energy savings was 14.9 times greater (40,437,870 kWh/2,704,000 kWh) by targeting the idle state rather than net scan state. CONCLUSION. CT net scan energy savings can be inferred from reductions in dose report metrics. However, targeting net scan energy consumption has modest impact relative to targeting idle state energy consumption. CLINICAL IMPACT. Environmental sustainability efforts should target the idle state energy consumption of CT.

Interventional Imaging Systems in Radiology, Cardiology, and Urology: Energy Consumption, Carbon Emissions, and Electricity Costs.

BACKGROUND. The energy demand of interventional imaging systems has historically been estimated using manufacturer-provided specifications rather than directly measured. OBJECTIVE. The purpose of this study was to investigate the energy consumption of interventional imaging systems and estimate potential savings in the carbon emissions and electricity costs of such systems through hypothetical operational adjustments. METHODS. An interventional radiology suite, neurointerventional suite, radiology fluoroscopy unit, two cardiology laboratories, and two urology fluoroscopy units were equipped with power sensors. Power measurement logs were extracted for a single 4-week period for each radiology and cardiology system (all between June 1, 2022, and November 28, 2022) and for the 2-week period from July 31, 2023, to August 13, 2023, for each urology system. Power statuses, procedure time stamps, and fluoroscopy times were extracted from various sources. System activity was divided into off, idle (no patient in room), active (patient in room for procedure), and net-imaging (active fluoroscopic image acquisition) states. Projected annual energy consumption was calculated. Potential annual savings in carbon emissions and electricity costs through hypothetical operational adjustments were estimated using published values for Switzerland. RESULTS. Across the seven systems, the mean power draw was 0.3-1.1, 0.7-7.4, 0.9-7.6, and 1.9-12.5 kW in the off, idle, active, and net-imaging states, respectively. Across systems, the off state, in comparison with the idle state, showed a decrease in the mean power draw of 0.2-6.9 kW (relative decrease, 22.2-93.2%). The systems had a combined projected annual energy consumption of 115,684 kWh (range, 3646-26,576 kWh per system). The systems' combined projected energy consumption occurring outside the net-imaging state accounted for 93.3% (107,978/115,684 kWh) of projected total energy consumption (range, 89.2-99.4% per system). A hypothetical operational adjustment whereby all systems would be switched from the idle state to the off state overnight and on weekends (versus being operated in idle mode 24 hours a day, 7 days a week) would yield the following potential annual savings: for energy consumption, 144,640 kWh; for carbon emissions, 18.6 metric tons of CO2 equivalent; and for electricity costs, US$37,896. CONCLUSION. Interventional imaging systems are energy intensive, having high consumption outside of image acquisition periods. CLINICAL IMPACT. Strategic operational adjustments (e.g., powering down idle systems) can substantially decrease the carbon emissions and electricity costs of interventional imaging systems.

Cerium-MOF-Derived Composite Hierarchical Catalyst Enables Energy-Efficient and Green Amine Regeneration for CO2 Capture.

The excessive energy consumed restricts the application of traditional postcombustion CO2 capture technology and limits the achievement of carbon-neutrality goals. Catalytic-rich CO2 amine regeneration has the potential to accelerate proton transfer and increase the energy efficiency in the CO2 separation process. Herein, we reported a Ce-metal-organic framework (MOF)-derived composite catalyst named HZ-Ni@UiO-66 with a hierarchical structure, which can increase the CO2 desorbed amount by 57.7% and decrease the relative heat duty by 36.5% in comparison with the noncatalytic monoethanolamine (MEA) regeneration process. The composite catalyst of the CeO2 coating from the UiO-66 precursor on the HZ-Ni carrier shows excellent stability with a long lifespan. The HZ-Ni@UiO-66 catalyst also shows a universal catalytic effect in typical blended amine systems with a large cyclic capacity. The HZ-Ni@UiO-66 catalyst effectively decreases the energy barrier of the CO2 desorption reaction to reduce the time required to reach thermodynamics, consequently saving the energy consumption generated by water evaporation. This research provides a new avenue for advancing amine regeneration with less heat duty at low temperatures.

Mixing due to Solution Switch Limits the Performance of Electrosorption for Desalination.

Electrosorption (ES) is a research frontier in electrochemical separation, with proven potential applications in desalination, wastewater treatment, and selective resource extraction. However, due to the limited adsorption capacity of film electrodes, ES requires short circuiting or circuit reversal, accompanied by a solution switch between the feed solution and receiving solution, to sustain desalination over many charge-discharge cycles. In previously reported studies, solution switches have been commonly ignored to simplify experimental procedures, and their impacts on separation performance are thus not well understood. This study aims to provide a quantitative analysis of the impacts of mixing due to a solution switch on the performance of ES-based desalination. A numerical model of ES has been employed to evaluate the adverse effects of the solution switch on the desalination performance in three commonly used operation modes. The analysis reveals that the impacts of mixing due to solution-switch are more severe with a larger concentration difference between the desalinated water and the brine and provides insights into the effectiveness of increasing electrode loading or specific capacity in mitigating the detrimental impacts of mixing. Even with state-of-the-art systems, producing freshwater from seawater or even brackish water with medium-to-high salinity is practically challenging due to the presence of solution switch.

Moderating AC Usage Can Reduce Thermal Disparity between Indoor and Outdoor Environments.

In the context of escalating urban heat events due to climate change, air conditioning (AC) has become a critical factor in maintaining indoor thermal comfort. Yet the usage of AC can also exacerbate outdoor heat stress and burden the electricity system, and there is little scientific knowledge regarding how to balance these conflicting goals. To address this issue, we established a coupled modeling approach, integrating the Weather Research and Forecasting model with the building energy model (WRF_BEP + BEM), and designed multiple AC usage scenarios. We selected Chongqing, China's fourth-largest megacity, as our study area due to its significant socioeconomic importance, the severity of extreme heat events, and the uniqueness of its energy infrastructure. Our analysis reveals that AC systems can substantially reduce indoor temperatures by up to 18 °C; however, it also identifies substantial nighttime warming (2-2.5 °C) and a decline in thermal comfort. Particularly for high-density neighborhoods, when we increase 2 °C indoors, the outdoor temperature can be alleviated by up to 1 °C. Besides, despite the limited capacity to regulate peak electricity demand, we identified that reducing the spatial cooled fraction, increasing targeted indoor temperature by 2 °C, and implementing temporal AC schedules can effectively lower energy consumption in high-density neighborhoods, especially the reduction of spatial cooled fraction (up to 50%). Considering the substantial demand for cooling energy, it is imperative to carefully assess the adequacy and continuity of backup energy sources. The study underscores the urgency of reassessing energy resilience and advocates for addressing the thermal equity between indoor and outdoor environments, contributing to the development of a sustainable and just urban climate strategy in an era of intensifying heat events.

Coupling of Electric and Flow Fields to Enhance Ion Transport for Energy-Efficient Electrochemical Tap-Water Softening.

Electrochemical-induced precipitation is a sustainable approach for tap-water softening, but the hardness removal performance and energy efficiency are vastly limited by the ultraslow ion transport and the superlow local HCO3-/Ca2+ ratio compared to the industrial scenarios. To tackle the challenges, we herein report an energy-efficient electrochemical tap-water softening strategy by utilizing an integrated cathode-anode-cathode (CAC) reactor in which the direction of the electric field is reversed to that of the flow field in the upstream cell, while the same in the downstream cell. As a result, the transport of ions, especially HCO3-, is significantly accelerated in the downstream cell under a flow field. The local HCO3-/Ca2+ ratio is increased by 1.5 times, as revealed by the finite element numerical simulation and in situ imaging. In addition, a continuous flow electrochemical system with an integrated CAC reactor is operated for 240 h to soften tap water. Experiments show that a much lower cell voltage (9.24 V decreased) and energy consumption (28% decreased) are obtained. The proposed ion-transport enhancement strategy by coupled electric and flow fields provides a new perspective on developing electrochemical technologies to meet the flexible and economic demand for tap-water softening.

Reducing Chloride Ion Permeation during Seawater Electrolysis Using Double-Polyamide Thin-Film Composite Membranes.

Low-cost polyamide thin-film composite membranes are being explored as alternatives to expensive cation exchange membranes for seawater electrolysis. However, transport of chloride from seawater to the anode chamber must be reduced to minimize the production of chlorine gas. A double-polyamide composite structure was created that reduced the level of chloride transport. Adding five polyamide layers on the back of a conventional polyamide composite membrane reduced the chloride ion transport by 53% and did not increase the applied voltage. Decreased chloride permeation was attributed to enhanced electrostatic and steric repulsion created by the new polyamide layers. Charge was balanced through increased sodium ion transport (52%) from the anolyte to the catholyte rather than through a change in the transport of protons and hydroxides. As a result, the Nernstian loss arising from the pH difference between the anolyte and catholyte remained relatively constant during electrolysis despite membrane modifications. This lack of a change in pH showed that transport of protons and hydroxides during electrolysis was independent of salt ion transport. Therefore, only sodium ion transport could compensate for the reduction of chloride flux to maintain the set current. Overall, these results prove the feasibility of using a double-polyamide structure to control chloride permeation during seawater electrolysis without sacrificing energy consumption.

Using green nanocomposite containing eggshell in the electroperoxone process in a baffled reactor to remove the emerging tetracycline pollutant.

This study examined the eradication of Tetracycline hydrochloride (TCH) antibiotic, an emerging pollutant, by utilizing eggshell membrane activated carbon (EMAC) and magnetite (Fe3O4) nanocomposite in conjunction with the electroperoxone process employing the One Factor at a Time method (OFAT) in a baffled reactor. The nanocomposite was synthesized through the hydrothermal method using an autoclave, and its properties were assessed via XRD, FTIR, FESEM, EDAX Mapping, BET, and VSM analyses. The findings revealed that under optimal conditions (including a pollutant concentration of 300 mg/L, a natural pH of 6.2, an ozone consumption rate of 0.28 g/h, a nanocomposite concentration of 0.2 g/L, a flow intensity of 0.5 A, a wastewater recirculation flow rate of 8 L/h, and a 0.1 M Na2SO4 electrolyte concentration), 95.9%, 76.4%, and 53.4% of pollutants, COD, and TOC were respectively eliminated after 90 min. Additionally, the reusability of the nanocomposite was evaluated over five usage periods, during which the process efficiency decreased from 95.9% to 83.1%. In short, this study proved that EMAC/Fe3O4 nanocomposites are promising electroperoxone catalysts due to their low cost, excellent stability and reusability, environmental compatibility, and superior catalytic activity for TCH antibiotics removal.

Optimization-enabled deep learning model for disease detection in IoT platform.

Nowadays, Internet of things (IoT) and IoT platforms are extensively utilized in several healthcare applications. The IoT devices produce a huge amount of data in healthcare field that can be inspected on an IoT platform. In this paper, a novel algorithm, named artificial flora optimization-based chameleon swarm algorithm (AFO-based CSA), is developed for optimal path finding. Here, data are collected by the sensors and transmitted to the base station (BS) using the proposed AFO-based CSA, which is derived by integrating artificial flora optimization (AFO) in chameleon swarm algorithm (CSA). This integration refers to the AFO-based CSA model enhancing the strengths and features of both AFO and CSA for optimal routing of medical data in IoT. Moreover, the proposed AFO-based CSA algorithm considers factors such as energy, delay, and distance for the effectual routing of data. At BS, prediction is conducted, followed by stages, like pre-processing, feature dimension reduction, adopting Pearson's correlation, and disease detection, done by recurrent neural network, which is trained by the proposed AFO-based CSA. Experimental result exhibited that the performance of the proposed AFO-based CSA is superior to competitive approaches based on the energy consumption (0.538 J), accuracy (0.950), sensitivity (0.965), and specificity (0.937).

Energy and time-aware scheduling in diverse virtualized cloud computing environments using optimized self-attention progressive generative adversarial network.

The rapid growth of cloud computing has led to the widespread adoption of heterogeneous virtualized environments, offering scalable and flexible resources to meet diverse user demands. However, the increasing complexity and variability in workload characteristics pose significant challenges in optimizing energy consumption. Many scheduling algorithms have been suggested to address this. Therefore, a self-attention-based progressive generative adversarial network optimized with Dwarf Mongoose algorithm adopted Energy and Deadline Aware Scheduling in heterogeneous virtualized cloud computing (SAPGAN-DMA-DAS-HVCC) is proposed in this paper. Here, a self-attention based progressive generative adversarial network (SAPGAN) is proposed to schedule activities in a cloud environment with an objective function of makespan and energy consumption. Then Dwarf Mongoose algorithm is proposed to optimize the weight parameters of SAPGAN. Outcome of proposed approach SAPGAN-DMA-DAS-HVCC contains 32.77%, 34.83% and 35.76% higher right skewed makespan, 31.52%, 33.28% and 29.14% lower cost when analysed to the existing models, like task scheduling in heterogeneous cloud environment utilizing mean grey wolf optimization approach, energy and performance-efficient task scheduling in heterogeneous virtualized Energy and Performance Efficient Task Scheduling Algorithm, energy and make span aware scheduling of deadline sensitive tasks on the cloud environment, respectively.

The German version of the Pregnancy Physical Activity Questionnaire: a translation, cross-cultural adaptation, reliability and validity assessment.

BACKGROUND: Validated and internationally standardised measurement instruments are a prerequisite for ensuring that physical activity during pregnancy is comparable and for deriving physical activity recommendations. In Germany, there has been no adapted version of the internationally used Pregnancy Physical Activity Questionnaire (PPAQ) until now. This study's aim centred around translating the original English version into German (PPAQ-G) and determining its reliability as well as validity in a German population. METHODS: The PPAQ was translated into German using the forward-backwards technique. Its reliability and validity were tested. Thirty-four correctly completed questionnaires were analysed. The test-retest reliability was presented using the intraclass correlation coefficient (ICC) and Spearman correlation coefficient. Validity was tested by using accelerometer (n = 23) and determined by Spearman correlation coefficient. RESULTS: In the transcultural adjustment, two questions were amended to describe intensity more precisely, and two other questions were adapted to reflect the units of measurement used in Germany. The ICC indicated a reliability of r = 0.79 for total activity (without sitting), and the intensity subcategories ranged from r = 0.70 (moderate-intensity activities) to r = 0.90 (sitting). Although, validity assessment showed no significant correlation for sedentary, moderate or vigorous intensity, there were significant correlations for total activity (light and above; r = 0.49; p < 0.05) and for light activity (r = 0.65; p < 0.01). CONCLUSIONS: The PPAQ-G showed good reliability for use on pregnant German women and a moderately accurate measurement of physical activity. It can be used nationally for epidemiological studies, and it also enables international comparisons of physical activity during pregnancy. TRIAL REGISTRATION: DRKS00023426; Registration date 20 May 2021.