Energy Requirements Research Articles

Evaluation of body calcium and phosphorus composition of the Cobb 700 genotype during growth.

1. The amount of calcium and phosphorus in the empty, feather-free bodies of Cobb 700 breed males and females was measured from hatch to 15 weeks of age.2. A four-phase ad libitum feeding programme was used to feed 400 chicks of each sex. Feeds contained commercial levels of calcium and phosphorus which met or exceeded the requirements for energy, protein and amino acids. All birds were weighed weekly. Ten birds per sex were sampled at 0, 7, 14, 28, 42, 56, 70, 84 and 105 d of age. Defeathered birds were minced, freeze-dried and then analysed for protein, ash, calcium and phosphorus content.3. Amounts of Ca in males and females at 105 d averaged 54 and 37 g, respectively, and 105 d P content in males and females averaged 35 and 27 g, respectively. The allometry of ash, Ca and P with empty, feather-free body protein was assessed. Ash was isometric with body protein, while an allometric exponent greater than 1 was established for Ca and P with body protein.4. The allometric models and means for Ca and P relative to body protein were compared with models and means found in the literature. Comparison of the Ca/protein ratios with previous data suggested that modern broilers may not reach their potential bone mineral deposition with current dietary guidelines, even when growth rates were maximised.5. Theoretical allometric relationships between Ca and P in bone and bone-free body and body protein have now been proposed. The allometric relationship between Ca and P and empty, feather-free body protein offers a suitable way to model the growth of these minerals in the broiler body.

Innovative Study on Solar Energy Conversion and Storage Through Malachite Green + Ascorbic Acid + Sodium Lauryl Sulphate For Photogalvanics

Objective: To improve the output of photogalvanics (PG) cell. Methods: The specially designed H shaped PG cell was studied for better electrical outcomes. The PG cell setup consists of two electrode, digital pH meter, resistance key, carbon pot, and microammeter. The system consisting of Malachite Green (MCG), Ascorbic acid (AA), and Sodium Lauryl Sulphate (SLS) was examined in terms of photopotential (PP) and photocurrent (PC). Findings: The measured PC was 391.00 µA, while the observed PP was 926.00 mV. The finest and most dependable renewable energy option to help the world's population meet their energy requirements is solar energy. Novelty: Better results on Photo Galvanic (PG) cells are reported in the present research, helping to achieve the goal providing clean and sustainable energy. The intended electrical outcomes were obtained by using the MCG + AA + SLS, PG cell arrangement. Keywords: Malachite Green, Photogalvanics, Sodium Lauryl Sulphate, Ascorbic acid, Photopotential

Climate Change and Building Renovation: The Impact of Historical, Current, and Future Climatic Files on a School in Central Italy

Climate change significantly affects the operating environment of buildings. These changes impact both energy efficiency and occupants’ comfort and remain crucial even in building restoration, where design decisions typically rely on historical data, yet performance depends on anticipated future scenarios. The present work evaluates the impact of different climate datasets on dynamic energy simulations for an educational building in Central Italy, focusing on estimating heating demands across historical, current, and future climatic scenarios. The assessment considers both the building’s current state and potential energy-efficient retrofits. Initially, various meteorological datasets, including measured and model-generated data, are selected to predict key weather parameters. The analysis reveals the potential and limitations of regional climate models (RCMs) in estimating these variables, with the MM5 dataset emerging as the most reliable. Subsequently, the energy performance of the reference building and its vulnerability to climate change are assessed. Our results show significant differences in energy demand based on construction periods, with the oldest section consuming 29% to 54% more energy monthly than the newer sections. Moreover, using non-representative climatic files can lead to prediction errors of up to 199%. Finally, the building’s energy behaviour is analysed under future climate conditions by generating typical meteorological years (TMYs) for 2030, 2050, and 2070. This analysis evaluates the energy requirements for both existing and retrofitted building configurations. The findings confirm that retrofit interventions with high-performance insulation and upgraded windows significantly enhance the building’s energy efficiency and resilience to future climate conditions, leading to annual energy savings of 50% to 57%.

Nutrition support in children with medical complexity and chronic critical illness: A narrative review.

Children with medical complexity (CMC) and children with chronic critical illness (CCI) represent growing populations with high healthcare use and dependence on specialized care, both in the hospital and community setting. Nutrition assessment and delivery represent critical components of addressing the short-term and long-term health needs for these populations across the care continuum. This article provides a framework and reviews existing literature for the assessment of nutrition status and subsequent delivery of nutrition prescriptions in CMC and children with CCI. The specific aims are to (1) describe the epidemiology of health services experience for CMC and children with CCI, with a focus on their nutrition outcomes; (2) detail how to assess their nutrition status and energy requirements; (3) review methods of delivery of the nutrient prescription; (4) introduce perioperative considerations; (5) highlight examples of special populations of CMC and children with CCI; and (6) propose future research initiatives to improve nutrition and overall outcomes for these populations.

Metabolic modelling reveals distinct roles of sugars and carboxylic acids in stomatal opening and uncovers unexpected carbon fluxes.

Guard cell metabolism is crucial for stomatal dynamics, but a full understanding of its role is hampered by experimental limitations and the flexible nature of the metabolic network. To tackle this challenge, we constructed a time-resolved stoichiometric model of guard cell metabolism that accounts for energy and osmolyte requirements and which is integrated with the mesophyll. The model resolved distinct roles for starch, sugars, and malate in guard cell metabolism and revealed several unexpected flux patterns in central metabolism. During blue light-mediated stomatal opening, starch breakdown was the most efficient way to generate osmolytes with downregulation of glycolysis allowing starch-derived glucose to accumulate as a cytosolic osmolyte. Maltose couldalso accumulate as a cytosolic osmoticum, although this made the metabolic system marginally less efficient. The metabolic energy for stomatal opening was predicted to be derived independently of starch, using nocturnally accumulated citrate which was metabolised in the tricarboxylic acid cycle to malate to provide mitochondrial reducing power for ATP synthesis. In white light-mediated stomatal opening, malate transferred reducing equivalents from guard cell photosynthesis to mitochondria for ATP production. Depending on the capacity for guard cell photosynthesis, glycolysis showed little flux during the day but was crucial for energy metabolism at night. In summary, our analyses have corroborated recent findings in Arabidopsis guard cell research, resolved conflicting observations by highlighting the flexibility of guard cell metabolism, and proposed new metabolic flux modes for further experimental testing.

Advancing irrigation management: integrating technology and sustainability to address global food security.

Irrigation management is essential for addressing global food security challenges under changing climate. This review discusses the integration of advanced irrigation technologies and their roles in enhancing water use efficiency and managing energy demands within agricultural systems. High-efficiency irrigation systems, such as drip and sprinkler systems, have significant potential to reduce water use and increase crop yields. However, their adoption varies worldwide, and the efficiency of existing irrigation practices often remains inadequate, resulting in substantial water losses due to outdated management practices. Emerging technologies and innovative irrigation strategies, including precision agriculture and advanced crop models, provide promising pathways for improving irrigation efficiency. Nonetheless, the widespread integration of these technologies is hindered by high costs, the need for technical expertise, and challenges in adapting existing agricultural systems to new methodologies. Irrigation systems can have substantial energy requirements, particularly those dependent on groundwater. The exploration of the water-environment-energy-food (WEEF) nexus illustrates the importance of a balanced approach to resource management, which is crucial for achieving sustainable agricultural outcomes. Future research should include lowering barriers to technology adoption, enhancing data utilization for precision irrigation, promoting integrated management strategies within the WEEF framework, and strengthening policy support for sustainable practices. This review proposes a multidisciplinary approach to irrigation management that includes technological innovation, strategic policy development, and global cooperation to secure sustainable agricultural practices and ensure global food supply resilience in the face of climate change.

Energy Demand Estimation in Turkey According to Road and Rail Transportation: Walrus Optimizer and White Shark Optimizer Algorithm-Based Model Development and Application

Transport energy demand (TED) forecasting is a crucial issue for countries like Turkey that are dependent on external resources. The accuracy and effectiveness of these forecasts are extremely important, especially for the strategies and plans to be developed. With this in mind, different forms of forecasting models were developed in the present study using the Walrus Optimizer (WO) and White Shark Optimizer (WSO) algorithms to estimate Turkey’s energy consumption related to road and railway transportation modes. Additionally, another objective of this study was to examine the impacts of different transport modes on energy demand. To investigate the effect of demand distribution among transport modes on energy consumption, model parameters such as passenger-kilometers (P-km), freight-kilometers (F-km), carbon dioxide emissions (CO2), gross domestic product (GDP), and population (POP) were utilized in the development of the models. It was found that the WO algorithm outperformed the WSO algorithm and was the most suitable method for energy demand forecasting. All the developed models demonstrated a better performance level than those reported in previous studies, with the best performance achieved by the semi-quadratic model developed with the WO, showing a 0.95% MAPE value. Projections for energy demand up to the year 2035 were established based on two different scenarios: the current demand distribution among transport modes, and a demand shift from road to rail transportation. It is anticipated that the proposed energy demand models will serve as an important guide for effective planning and strategy development. Moreover, the findings suggest that a balanced distribution among transport modes will have a positive impact on transport energy and will result in lower energy requirements.

Graphite-enhanced PCMs in Gypsum Boards for Reduced Building Energy Requirements

Graphite-enhanced PCMs in Gypsum Boards for Reduced Building Energy Requirements

Advancing Nanopulsed Plasma Bubbles for the Degradation of Organic Pollutants in Water: From Lab to Pilot Scale

The transition from lab-scale studies to pilot-scale applications is a critical step in advancing water remediation technologies. While laboratory experiments provide valuable insights into the underlying mechanisms and method effectiveness, pilot-scale studies are essential for evaluating their practical feasibility and scalability. This progression addresses challenges related to operational conditions, effectiveness and energy requirements in real-world scenarios. In this study, the potential of nanopulsed plasma bubbles, when scaled up from a lab environment, was explored by investigating critical experimental parameters, such as plasma gas, pulse voltage, and pulse repetition rate, while also analyzing plasma-treated water composition. To validate the broad effectiveness of this method, various classes of highly toxic organic pollutants were examined in terms of pollutant degradation efficiency and energy requirements. The pilot-scale plasma bubble reactor generated a high concentration of short-lived reactive species with minimal production of long-lived species. Additionally, successful degradation of all pollutants was achieved in both lab- and pilot-scale setups, with even lower electrical energy-per-order (EEO) values at the pilot scale, 2–3 orders of magnitude lower compared to other advanced oxidation processes. This study aimed to bridge the gap between lab-scale plasma bubbles and upscaled systems, supporting the rapid, effective, and energy-efficient destruction of organic pollutants in water.

Onboard amino acid salt-based CO2 integrated absorption and mineralization: Kinetics, mechanism, economics and life cycle

The International Maritime Organization's ambitious greenhouse gas reduction strategy is driving efforts to capture carbon from marine engine exhaust gas. Onboard carbon capture and storage (OCCS) faced significant challenges, particularly due to the substantial thermal energy requirements during the capture process and the complexities of transporting captured CO2 to storage facilities. The integrated CO2 absorption and mineralization (IAM) process, a thermodynamically downhill process, offered a potential solution for rapidly absorbing and sequestering CO2 in-situ. In this study, a single-step amino acid salt-based IAM process was employed to address carbon emissions from ships. Under optimized conditions, over 85 % of the CO2 in simulated marine engine exhaust gas was captured and completely converted to calcium carbonate using a potassium glycinate/ calcium hydroxide blend absorption slurry. This approach tackled the key challenges of effectively capturing CO2 from ships, while minimizing energy consumption, and ensuring the safe storage of the captured CO2. A case study on a 1700 TEU container ship evaluated the economic benefits and global warming potential of the OCCS system, indicating that capturing CO2 from ships could be profitable (87.2 $/ton CO2) and calcium carbonate could be a commercial product. Despite high-carbon-intensity absorbents (such as calcium hydroxide) partially offset the carbon reduction effort, resulting in a decline of carbon capture efficiency from 85 % to 44 %. The proposed amino acid salt-based IAM method could be considered a promising technique for reducing carbon emissions from ships, providing a feasible technical means for achieving the International Maritime Organization's ambition strategy for zero-carbon shipping.

Inertial microfluidic mixer for biological CubeSat missions

Nanosatellites of CubeSat type due to, i.a., minimized costs of space missions, as well as the potential large application area, have become a significant part of the space economy sector recently. The opportunity to apply miniaturized microsystem (MEMS) tools in satellite space missions further accelerates both the space and the MEMS markets, which in the coming years are considered to become inseparable. As a response to the aforementioned perspectives, this paper presents a microfluidic mixer system for biological research to be conducted onboard CubeSat nanosatellites. As a high complexity of the space systems is not desired due to the need for failure-free and remotely controlled operation, the principal concept of the work was to design an entirely passive micromixer, based on lab-on-chip technologies. For the first time, the microfluidic mixer that uses inertial force generated by rocket engines during launch to the orbit is proposed to provide an appropriate mixing of liquid samples. Such a solution not only saves the space occupied by standard pumping systems, but also reduces the energy requirements, ultimately minimizing the number of battery modules and the whole CubeSat size. The structures of the microfluidic mixers were fabricated entirely out of biocompatible resins using MultiJet 3D printing technology. To verify the functionality of the passive mixing system, optical detection consisting of the array of blue LEDs and phototransistors was applied successfully. The performance of the device was tested utilizing an experimental rocket, as a part of the Spaceport America Cup 2023 competition.Graphical abstract

An Overview of Different Water Electrolyzer Types for Hydrogen Production

While fossil fuels continue to be used and to increase air pollution across the world, hydrogen gas has been proposed as an alternative energy source and a carrier for the future by scientists. Water electrolysis is a renewable and sustainable chemical energy production method among other hydrogen production methods. Hydrogen production via water electrolysis is a popular and expensive method that meets the high energy requirements of most industrial electrolyzers. Scientists are investigating how to reduce the price of water electrolytes with different methods and materials. The electrolysis structure, equations and thermodynamics are first explored in this paper. Water electrolysis systems are mainly classified as high- and low-temperature electrolysis systems. Alkaline, PEM-type and solid oxide electrolyzers are well known today. These electrolyzer materials for electrode types, electrolyte solutions and membrane systems are investigated in this research. This research aims to shed light on the water electrolysis process and materials developments.

Feeding twin-bearing Merino ewes above the metabolisable energy requirements for maintenance during late gestation increases the duration of parturition of the first-born lamb

Context In Australia, approximately 53% of lamb deaths are caused by dystocia. One of the main welfare concerns in the sheep industry is under- and overfeeding ewes, which may be contributing to cases of dystocia. Aims This pilot study aimed to investigate how increasing energy intake affects the duration of parturition and predictors of lamb survival. Methods On Day 100 of gestation (dG), 20 twin-bearing and 10 singleton Merino ewes were selected and allocated to three treatment groups; (1) singleton ewes fed at 1.0× maintenance levels (n = 10); (2) twin-bearing ewes fed at 1.0× maintenance levels (n = 10) or (3) twin-bearing ewes fed at 1.25× maintenance (n = 10). Ewes were housed indoors in individual pens. Urine and blood were sampled from ewes on dG 130, 140, then daily from dG 145 through to parturition, and blood was sampled at the onset of parturition and 30 min post-partum. Urine was analysed for pH and blood was analysed for metabolic parameters, mineral concentration and acid–base balance. Predictors of lamb survival from birth to 24 h consisted of weight, rectal temperature, blood glucose and lactate, and body morphology. Key results Serum calcium in late gestation and blood base excess pre-parturition were higher in Singletons 1M compared with Twins 1M (P < 0.05). The Twins 1.25M group took longer to give birth to the first-born lamb (104.4 ± 21.1 min) compared with the Twins 1M group (44.1 ± 6.6 min; P = 0.015). There were no differences in the predictors of lamb survival measures between the twin-bearing groups (P > 0.05). Conclusions Ewes from the Twins 1.25M group took significantly longer to give birth to the first-born lamb. There were no other significant findings between the twin-bearing groups, including lamb liveweight, however, lambs born to ewes from the Twins 1.25 group were numerically heavier, which may explain the increase in parturition length. Implications Feeding ewes above maintenance did not provide any production benefits to metabolic health or any other physiological parameters. Producers should avoid overfeeding ewes during late gestation.

Comparative analysis of direct coupling and MPPT control in standalone PV systems for solar energy optimization to meet sustainable building energy demands

Solar energy, a prominent renewable source, has reached an installed capacity of 71.78 GW in India. This research explored the load demands of the computer center at an engineering college in Tanjore, Tamil Nadu, India. The computer center at the engineering college has an annual energy requirement of 260,552 kWh/Year. Consequently, the research focused on the planning and implementation of a standalone photovoltaic (SAPV) system, assessing it against the institution's total annual energy consumption. The performance ratio and losses of the SAPV system with both direct coupling and an MPPT charge controller was compared. This comparative analysis aimed to evaluate the efficacy of two solar photovoltaic control methods—SAPV direct coupling and Maximum Power Point Tracking control—in optimizing energy harvesting from solar panels.

Nutritional intervention during a teleprehabilitation pilot study in high-risk patients with colorectal cancer: adherence, motivators, and barriers.

The preoperative period provides a window of opportunity to improve modifiable risk factors for treatment complications such as malnutrition, the so-called prehabilitation. Identifying factors related to adherence to nutritional interventions is essential for optimizing prehabilitation programs. The aim of this study is to evaluate a nutritional support module as part of a teleprehabilitation program in high-risk patients with colorectal cancer (CRC). A secondary analysis with a mixed method design of the nutritional support module of a pre-post teleprehabilitation pilot study was performed. Change in weight, complaints with intake, motivation, and subjective and objective adherence were evaluated. Eleven patients were included. Subjectively, six patients (55%) were able to adhere to the nutritional advice. Despite that, nine of eleven (82%) patients experienced difficulties with the amount of food that was advised by the dietician. Six of eleven (55%) patients gained weight during the prehabilitation program. After prehabilitation, nine of eleven (82%) were able to reach 100% of their energy requirement and six of eleven (55%) were able to reach 100% of their protein requirement. Differences between patients in motivation and/or having complaints did not seem to be associated with protein and energy intake. This secondary analysis of a pilot study provides insights into understanding patients' experiences with a nutritional support module as part of a teleprehabilitation program. With 82% of patients who were able to reach 100% of their energy requirement, teleprehabilitation seems to be feasible, while there is still room for improvement with respect to protein intake as only 55% of patients reached a sufficient intake.

An Integrated Artificial Intelligence Approach for Building Energy Demand Forecasting

Buildings are complex assets, characterized by environments and uses that change over time, variable occupancies, and long life cycles. They have high operational costs, mostly due to their energy requirements, and account for 30% to 40% of global greenhouse gas emissions. Consequently, substantial effort has been made to forecast their energy needs, with the scope of optimizing their economic and environmental impact. In this regard, the available literature focuses mainly on short-term modeling through the implementation of sets of physics-based equations (i.e., white-box), functional relationships between input and output variables (i.e., black-box), or a combination of both (i.e., grey-box). On the other hand, more research is required on long-term forecast models with the aim of reducing the energy needs. Within this context, this article presents an original automatic procedure for forecasting the energy needs of buildings in short- and long-term time horizons. This is accomplished by scaling an unknown facility from a similar facility that is already known and by executing a black-box approach based on machine learning algorithms. The proposed method is implemented in real case studies in Italy, predicting the energy needs (i.e., heating, cooling, and electricity) of Sant’Anna Hospital in Ferrara using the historical data of Ca’ Foncello Hospital in Treviso. The results show an adjusted coefficient of determination above 0.7 and an average error below 10% for all the energy vectors, demonstrating a feasible forecast performance with a low training set-to-test set ratio.

Energy requirements in liver cirrhosis

Energy requirements in liver cirrhosis

Comparative thermoeconomic analysis of integrated hybrid multigeneration systems with hydrogen production for waste heat recovery in cement plants

The cement industry is a widely used and energy-consuming sector, making it one of the largest CO2 emitters, primarily to meet its energy demands. Therefore, this research aims to evaluate the waste heat recovery process from a cement factory to fulfill a portion of its energy requirements. In this study, four scenarios have been evaluated, including power production scenarios, hydrogen production scenarios, methanation production process evaluation scenarios, blending hydrogen with natural gas, oxy-fuel combustion scenarios, and scenarios for producing the required freshwater for the factory and the water electrolysis process. The results show that the steam Rankine cycle with the reheating process and the organic Rankine cycle with methanol working fluid with a production capacity of 24.35 MW, and a payback period of 2.4 years with levelized cost of energy being 0.005809 $/kWh, is the most favorable scenario for the power generation cycle. Also, the process of alkaline electrolysis with a hydrogen production rate of 0.1648 kg/s, and a payback period of 5.816 years, and also with the levelized cost of hydrogen being 1.001 $/kg, happened to be the most suitable hydrogen production scenario compared to other electrolysis scenarios such as PEM and SOEC. Moreover, the process of water desalination by reverse osmosis with the energy consumption of 2.7 MW of power is capable of supplying all the required water of the factory and the water electrolysis process, and it was determined as the most suitable scenario for supplying the required water.

Energy and protein requirements are met after a 12-week dietary treatment in primary care clients with (risk of) malnutrition: Preliminary results from practice-based research

Energy and protein requirements are met after a 12-week dietary treatment in primary care clients with (risk of) malnutrition: Preliminary results from practice-based research

Estimating energy requirements in patients with breast cancer and survivors

Estimating energy requirements in patients with breast cancer and survivors