A lack of trust in Energy Service Company (ESCo) is the most critical factor affecting the development of Energy Performance Contracting (EPC) in China compared with other constraints. One cannot easily estimate the energy-saving performance of an EPC project. Under that condition, lack of trust may cause the Energy-Consuming Unit (ECU) to suspect the energy-saving performance promised by the ESCo, thus leaving potentially profitable projects without necessary funding. Currently, specific studies taking an across-projects viewpoint on annual energy-saving performance of EPC projects in multiple subsectors objectively and quantitatively are lacking. This paper studies the regression relationships of annual energy-saving quantity in terms of revamping cost and the regression relationships of annual cost saving in terms of revamping cost. The regression results show that there are statistically significant correlations in the above relationships in the nine subsectors investigated. This is significant for ESCos and ECUs because knowledge on energy-saving performance could contribute to EPC investment decisions and trust relationships between ESCos and ECUs. Then a multiple linear regression model of revamping cost is set up to analyze its influencing factors. The model indicates that the subsector the sample belongs to, financing, registered capital of the ESCo, and contract period have significant effects on revamping cost. Thus, policy implications regarding innovation of EE promotion technology, clarifying ESCos’ exit mechanism, innovation of financing mechanism, and improving the market credit environment for promoting investment in EPC projects are provided.

Clausius’ virial theorem set a basis for relating kinetic energy in a body of independent material particles to its potential energy, pointing to their complementary role with respect to the second law of maximum entropy. In action mechanics, expressing the entropy of ideal gases as a capacity factor for sensible heat or enthalpy plus the configurational work to sustain the relative translational, rotational and vibrational action yields algorithms for estimating chemical reaction rates and positions of equilibrium. All properties of state including entropy, work potential as Helmholtz and Gibbs energies and activated transition state reaction rates can be estimated, using easily accessible molecular properties, such as atomic weights, bond lengths, moments of inertia and vibrational frequencies. Understanding how Clausius’ virial theorem balances the internal kinetic energy with field potential energy justifies partitioning between thermal and statistical properties of entropy, yielding a more complete view of the evolutionary nature of the second law of thermodynamics. The ease of performing these operations is illustrated by three important chemical gas phase reactions, the reversible dissociation of the hydrogen molecules, lysis of water to hydrogen and oxygen and the reversible formation of ammonia from nitrogen and hydrogen. Employing the ergal also introduced by Clausius to define the reversible internal work to overcome molecular interactions plus the configurational internal work of negative Gibbs energy as a function of volume or pressure may provide a practical guide for managing risk in industrial processes and climate change at the global scale.

Poland is the 3^rdproducer of mushrooms in the world. Mushroom production in Poland accounts for nearly 25% of the total production in the EU, and it is still growing. One type of waste generated during mushroom production is mushroom spent compost (MSC), with a 5:1 (MSC: mushrooms) production rate. We investigated valorizing the MSC to produce fuel via torrefaction (‘roasting’, a.k.a. low-temperature pyrolysis). Specifically, we developed models for the MSC torrefaction kinetics using thermogravimetric analyses (TGA) and the effects of torrefaction temperature (200~300 °C) and process duration time (20~60 min) on the resulting biochar (fuel) properties. The estimated activation energy value of MSC torrefaction was 22.3 kJ^.mol^-1. The highest higher heating value(HHV) = 17.9 MJ^.kg^-1d.m. was found for 280 °C (60 min torrefaction time). The temperature of torrefaction significantly (p<0.05) increased the HHVfor constant process duration. The torrefaction duration time significantly (p<0.05) increased the HHVfor 220 °C and decreased HHVfor 300 °C. The highest mass yield 98.5% was found for 220 °C (60 min), while the highest energy yield was found for 280 °C (60 min). In addition, estimations of the value (€132.3·Mg^-1d.m. or 27.7 €·Mg^-1w.m) and quantity of resulting biochar (from torrefied MSC with 65.3% moisture content) were made based on the 280°C (60 min) torrefaction variant, assuming the price of commercially available coal fuel. We have shown a concept for an alternative utilization of abundant biowaste (MSC). The initial economic evaluation showed that MSC torrefaction might be profitable. This research provides a basis for alternative use of an abundant biowaste and can help charting improved, sustainable mushroom production.

The Energy Performance of Buildings Directive 2010 calls for the Nearly Zero Energy Standard for new buildings from 2021 onwards: Buildings using “almost no energy” are powered by renewable sources or energy produced by the building itself. For residential buildings, this ambitious new standard has already been reached. But for other building types this goal is still far away. The potential of these buildings to meet a Nearly Zero Energy Standard was investigated by analyzing ten case studies representing non-residential buildings with different uses. The analysis shows that the primary characteristics common to critical building types are a dense building context with a very high degree of technical installation (such as hospital, research and laboratory buildings). The large primary energy demand of these types of buildings cannot be compensated by building and property-related energy generation including off-site renewables. If the future Nearly Zero Energy Standard were to be defined with lower requirements because of this, the state related properties of Bavaria suggest that the real potential energy savings available in at least 85% of all new buildings would be insufficiently exploited. Therefore, it would be useful to instead individualize the legal energy verification process for new buildings to distinguish critical building types such as laboratories and hospitals.

An off-grid solar energy storage system (ESS) in National Pingtung University of Science and Technology (NPUST) was built and officially operated on Jun. 16th 2022. The system is installed in a 40' general container with PV panels of solar power 8250 W_p on top of the container. The ESS is made by repurposed lithium iron phosphate (LFP) batteries of 20 kWh capacity, where a battery management system (BMS) is adopted to ensured the safety of the battery system. An energy management system (EMS) is built to receive, process, analyse, store, and output the energy information. In this manuscript, a brief engineering report about the system is given.

This paper explores the latest developments in electrolysis technology, a key player in the transition to sustainable energy systems. Electrolysis, despite currently contributing a small share to global hydrogen production, holds immense potential for producing green hydrogen. The study delves into the efficiency of electrolysis systems, emphasizing ongoing efforts to enhance energy conversion rates. It investigates the impact of high-temperature electrolysis on reducing electricity consumption, thus making the process more efficient. The paper discusses the various challenges in the research on water electrolysis and underscores the critical role electrolysis plays in integrating renewable energy sources. The study emphasizes the need for continuous advancements in electrolysis technology to bridge existing gaps, making a compelling case for its pivotal role in the green hydrogen revolution.

Many Caribbean island nations have historically been heavily dependent on imported fossil fuels for both power and transportation, while at the same time being at an enhanced risk from the impacts of climate change, although their emissions represent a very tiny fraction of the global total responsible for climate change. Small island developing states (SIDS) are among the leaders in advocating for the ambitious 1.5°C Paris Agreement target and the transition to 100% sustainable, renewable energy systems. In this work we present three central results. First, we show through GIS mapping of all Caribbean islands the potential for near-coastal deep-water as a resource for Ocean Thermal Energy Conversion (OTEC) and couple these results with an estimate of the countries for which OTEC would be most advantageous due to a lack of other dispatchable renewable power options. Second, hourly data have been utilized to explicitly show the trade-offs between battery storage needs and dispatchable renewable sources such as OTEC in 100% renewable electricity systems, both in technological and economic terms. Finally, the utility of near-shore, open-cycle OTEC with accompanying desalination is shown to enable a higher penetration of renewable energy and lead to lower system levelized costs than those of a conventional fossil fuel system.

This study presents the development and implementation of a remote monitoring system for a dual-axis solar tracker, integrating Industry 4.0 technologies such as IoT, SCADA, and MQTT. The system, which combines a Siemens S7-1200 PLC, an IoT gateway, and a SCADA platform based on Ignition, demonstrated significant increases in solar capture efficiency, with production gains of 25-30% compared to fixed systems, reaching up to 67.65% under ideal conditions. In addition to improving operational management through predictive monitoring and early fault detection, the study identified areas for improvement, such as the need for real-world testing and the integration of weather predictions. In conclusion, the research validates the feasibility and effectiveness of automated IoT and SCADA-based systems to optimize solar trackers, significantly contributing to improved energy efficiency in photovoltaic installations.

The amount of solar energy produced is directly proportional to the surface area of solar panels exposed to sun rays. To increase the productivity of solar panels, a number of techniques are proposed by curving the surface or protruding the panel surface to maximise the surface area, e.g. Protruding panel surfaces with shapes such as pyramidal, cone, spherical cap, sinusoidal wavy curve, etc. These techniques are analysed to determine whether the panel surface area increases. The geometrical design analysis showed that, depending on the chosen surface curving method, the panel can achieve a remarkable increase in surface area.The system advisor model was used to assess a sample of solar cells with standard measurements of 6 by 6 inches that were organised in a zigzag pattern with different angles of inclination (10°, 15°, 20°, 25°, 30°, and 35°). Overall, the maximum power pump and annual AC energy performance increase by 1.4%, 4.2%, 6.8%, 10.8%, 14.9%, and 21.6%, respectively, over a one-year period of productivity. However, by applying the concept of solar panel efficiency degradation due to tilting solar panels at an angle by Mamun et al. (2022), for each 5° increase in tilt angle beyond the ideal 10°, the efficiency decreases by approximately 0.76%. In conclusion, the overall efficiency is greater than that of standard flat solar panels, provided the tilt angle is within a reasonable range.

It’s very well known that the world's attention is currently focused on the energy transition. The energy security, in addition to the drive to reduce greenhouse gas emissions in order to limit global warming, and the generalization of the access to energy, have contributed to adoption of the Moroccan Energy Strategy with a strong focus on Renewable Energies (RE). Morocco is notoriously poor in conventional fossil primary energy resources with an energy dependence on the order of 90%. The energy crisis and that resulted from Covid-19 pandemic and the geopolitical conflicts, combined compounded with steady increase in demand have heavily affected the security and the stability of the country's energy situation. The transition to RE, by strongly engaging in the implementation of several solar, wind and hydro energy projects benefiting from the country's excellent solar and wind energy potential, has made the country the leader in RE in Africa. By 2030, the share of RE in the installed capacity is expected to reach 52%. In this work, an overview of the current situation of RE (particularly solar energy) in Morocco is provided, including, the potentials, obstacles and challenges, and future perspectives. Thanks to its high solar potential location, it’s predictable that Morocco effort will be focused on this field: the Erasmus Plus Innomed Project is a virtuous example of international cooperation, aiming at create a Solar Energy Network, in synergy with EU Partners.

The accurate forecasting of solar power output is essential for ensuring the stable and efficient operation of grid-connected photovoltaic (PV) systems, especially when faced with variable weather patterns. This research focuses on the integration of Machine Learning (ML) methodologies and climatic parameters to predict solar panel energy generation, with a specific emphasis on addressing consumption-production imbalances. Leveraging a dataset sourced from the Kaggle platform, the study is conducted in the context of Estonia, aiming to optimize solar energy utilization in this geographic region. The dataset, obtained from Kaggle, encompasses comprehensive information on climatic variables, including sunlight intensity, temperature, and humidity, alongside corresponding solar panel energy output. Leveraging machine learning algorithms, including XGBoost regression and neural networks, our model aims to identify complex patterns and relationships within the datasets. By tailoring the model to Estonia's climatic nuances, we seek to enhance the accuracy of energy production forecasts and, consequently, better manage the challenges associated with consumption-production imbalances. Furthermore, the research investigates the adaptability of the proposed model to diverse climatic conditions, ensuring its applicability for similar endeavors in other geographical locations. The performance of the forecasting model will be evaluated using error metrics like mean absolute error (MAE) and root mean squared error (RMSE). This study leverages a comprehensive dataset from Kaggle and utilizes advanced machine learning techniques to generate valuable insights. These insights can inform the development of sustainable energy policies and practices, ultimately leading to a more efficient and reliable renewable energy infrastructure.

In 2023, residential and commercial sectors together consumed approximately 27.6% of total U.S. energy, equivalent to about 20.6 quadrillion Btu. Factoring in the electrical system energy losses, the residential sector represented approximately 19.7% of total U.S. energy consumption during that time. There were approximately 144 million housing units in the United States in 2023, which is increasing yearly. In this study, information on energy usage in the United States (U.S.) residential sector has been analyzed and then represented as energy intensities to establish benchmark data and to compare energy consumption of varying sizes and locations. First, public sources were identified, and data from these previously published sources were aggregated to determine the energy use of the residential sector within the US. Next, as part of this study, the energy data for seven houses/apartments from five different United States climate zones were collected firsthand. That data was analyzed, and the energy intensity of each home was calculated and then compared with the energy intensities of the other homes in the same states using RECS data. The energy intensity for each facility was calculated based on the actual energy bills. Finally, the study evaluated the carbon footprint associated with residential energy consumption in all 50 states to reinforce the importance of sustainable development initiatives.

This paper investigates the theoretical foundation for developing renewable geothermal resources locally. For this reason, we pay attention to the role of communities in geothermal development. This study presents arguments for a framework that approaches the geothermal resources as an endogenous factor of community development. To analyse it, we create a model that explains the local economic characters of the geothermal exploitation beyond its geological conditions. It aims to conceptualise a community based geothermal development standard referring to the endogeneity principle. Geothermal energy is given attention since the characteristics of this resource determine its use locally. We argue that the role of communities in geothermal exploitation is pivotal in the process of green growth for further expansion of geothermal energy use.

This paper offers a theoretical and experimental examination of the concurrent production of electricity and heat using photovoltaic thermal (PV/T) technology. The efficiency performance of the PV/T system is meticulously analyzed using MATLAB/Simulink software environments. Notably, the proposed PV/T system shows reliable performance, and its validity is confirmed through experimental validation on a test stand with a single PV/T panel positioned at a 45-degree angle to the horizontal and a 0-degree azimuth angle.

Amidst the recent energy crisis, the pivotal role of resource efficiency and renewable energy sources (RES) for sustainable development has become apparent. Transition to sustainability involves decentralized energy solutions empowering local communities to generate, store, and utilize their energy, diminishing reliance on centralized systems and potentially transforming them into power flexibility resources. This is particularly crucial in non-interconnected island systems that primarily rely on imported oil for electricity generation. Such reliance not only implies high production costs but also threatens energy security and adds to the environmental footprint of local economic activities. Addressing the above necessitates, amongst other elements, the adoption of advanced energy management with sophisticated forecasting and demand-side management (DSM) strategies. In response, we introduce a versatile algorithm investigating the impact of DSM at the community scale, designed to maximize the utilization of renewable energy produced from local installations. Integrated as an ancillary module in an advanced energy management platform, the algorithm undergoes testing using datasets collected from end-consumers and a small-scale RES installation on the island of Tilos, Greece. This study not only offers insights for energy stakeholders but also establishes theoretical parameters that can inform subsequent decision-making processes.

We introduce quantum spatio-temporal dynamics (QSD) as modeled by the Nexus Paradigm (NP) of quantum gravity to resolve the problem of energy- momentum localization in a gravitational field. Currently, the gravitational field as described using the language of geometry modeled under General Relativity (GR) fails to provide a generally accepted definition of energy-momentum. Attempts at resolving this problem using geometric methods have resulted in various energy-momentum complexes whose physical meaning remain dubious since the resulting complexes are non-tensorial under a general coordinate transformation. In QSD, the tangential manifold is the affine connection field in which energy-momentum localization is readily defined. We also discover that the positive mass condition is a natural consequence of quantization and that dark energy is a Higgs like field with negative energy density everywhere. Finally, energy-momentum localization in quantum gravity shows that a free falling object will experience large vacuum fluctuations (uncertainties in location) in strong gravity than in weak gravity and that the amplitudes of these oscillations defines the energy of the free falling object.

The growing adoption of distributed energy production technologies, and the potential of energy underutilization when it is produced by non-connected groups, has raised interest in ‘sharing economy’ concepts in the electricity sector. We suggest that mechanisms, such as peer-to-peer (P2P) energy trading, will allow users to exchange their surplus energy for mutual benefits, stimulate the adoption of renewable energy, encourage communities to ‘democratically’ control their own energy supplies for local development, and improved energy efficiency, and create many other benefits This approach is receiving increasing attention across the world, particularly in Germany, the Netherlands and Australia. Nevertheless, the actual development and implementation of these platforms is slow and mostly limited to trial activities. This study investigates the challenges and barriers facing P2P energy trading developments based on previous academic and industry studies. We provide a comprehensive multidimensional barrier analysis through a PESTLE approach to assess the barriers from a variety of perspectives, including the political (P), economic (E), social (S), technological (T), legal (L), and environmental (E) aspects. This approach clarifies the many intersecting problem fields of P2P trading in renewable energy, and the paper identifies a list of such barriers, and discusses the prospects for addressing these issues. We also elaborate on the importance of incentive-based P2P market design.

The surprisingly high catalytic activity of gold has been known to the heterogeneous catalysis community since the mid-1980s. Significant effort has been directed towards improving the reactivity of these surfaces towards important industrial reactions. One such strategy is the introduction of small amounts of other metals to create Au-based surface alloys. In this work, we investigate the synergistic effect of Pt doping of the Au(111) surface towards decreasing the activation barrier of the methanol dehydrogenation elementary step, within first-principles density functional theory. To this aim we construct several models of \ce{Pt}-doped Au(111) surfaces, including a full \ce{Pt} overlayer and monolayer. The effect of \ce{Pt} surface doping is then investigated via the computation of adsorption energies of the various chemical species involved in the catalytic step, and the estimation of activation barriers of methanol dehydrogenation. Both electronic and strain effects induced by \ce{Pt} surface doping concur in substantially lowering the activation energy barrier of this important reaction elementary step. Morever, in the presence of preadsorbed atomic oxygen, \ce{Pt} surface doping can be used to reduce the activation energy for methanol dehydrogenation to as low as 0.1 eV.

The relative proportions between nutrients affects the fate of them for metabolic interconversion, storage and turnover or, essentially for energy, in a process of partition modulated by hormonal and metabolic factors. A basic common chow model was used: ST or standard diet, HF high-fat and HP or high-protein had a common substrate. A CF cafeteria-type diet was added for comparison. Rats (female and male) received the diet for 30d. Nutrient intake and body composition were measured. Plasma glucose, lactate, testosterone (T) and estradiol (E2) were measured. Common groups energy intake, was largely based in carbohydrates CH, yielding 6C units, which were fully oxidized or stored as 2C fragments (fatty acids). Lactate (3C) was partially stored as glycerol of TAG. Accrual of 2C far exceeded about ten-fold that of 3C. Amino acid (AA) catabolism yielded 2C, 3C and 4C-5C fragments, the latter acting as Krebs cycle anaplerotic intermediates (KCAI), that facilitated the oxidation of 2C in detriment of TAG accumulation Lactate levels, were related to lactic dehydrogenase activities in muscle and liver. TAG accrual was maximal in CF, quite differently from HF with similar diet lipid proportion. Maximal rates of lipid storage were found in ST (and CF) groups. Females showed a higher ability to oxidize CH and to store less TAG. T increased N and protein deposition, whilst E2 decreased them favoring AA oxidation and the availability of KCAI. In the rat, an effective energy partition scheme requires that about half of the energy is provided by CH (polysaccharide), and needs enough protein to provide KCAI for a smooth 2C oxidation.

Currently, the district heating (DH) in Poland is facing many challenges. The business model used hitherto was very simple—in most cities, heating plants produced heat, and centralized heating systems supplied the "product" at a price approved annually by the president of the Energy Regulatory Office (URE). However, recent years have brought significant changes on the market. EU regulations force the elimination of old coal-fired plants that were still built in the Polish People's Republic (PRL), moreover, high prices of CO2 emission allowances aggravate the financial situation of companies. In addition, in the heating sector, the trend observed in the power sector is becoming increasingly visible—limiting the role of large sources in favor of energy generated locally, closer to the customer. One of the biggest challenges is achieving the targets set by the EU for the share of renewable energy sources (RES) in the heating sector. The war in Ukraine and problems with the supply of coal and gas are an additional impulse to turn to RES. Thus, the development of sustainable and innovative solutions for energy production and supply at the level of urban networks is currently one of the main technical challenges. The purpose of the paper is to present the current situation and perspectives of development of district heating systems in Poland with a view to the status of district heating in the world, and some deeper insight into European conditions. The review presents energy sources with particular emphasis on renewable energy sources (RES) and their cogeneration for heat production. The examples of existing heating network solutions using renewable energy sources, based on the selected published case studies, are also discussed.

Well-intentioned regulations to protect Canada’s most productive farmland restrict large-scale so-lar photovoltaic (PV) development. The recent innovation of agrivoltaics, which is the co-development of land for both PV and agriculture, makes these regulations obsolete. Burgeoning agrivoltaics research has shown agricultural benefits including increased yield for a wide range of crops, plant protection from excess solar energy and hail, improved water conservation while maintaining agricultural employment and local food supplies. In addition, the renewable electricity generation decreases greenhouse gas emissions while increasing farm revenue. As Canada in general, and Ontario in particular, is at a strategic disadvantage in agricultural without agrivoltaics, this study investigates the policy changes necessary to capitalize on the benefits of using agrivoltaics in Ontario. Land use policies in Ontario are reviewed. Then, three case studies (peppers, sweet corn and winter wheat) are analyzed for agrivoltaic potential in Ontario. These results are analyzed in conjunction with potential policies that would continue to protect the green-belt of the Golden Horseshoe, while enabling agrivoltaics in Ontario. Four agrivoltaic policy areas are discussed: increased research and development, enhanced education/public awareness, mechanisms to support Canada’s farmers converting to agrivoltaics and using agrivoltaics as a potential source of trade surplus with the U.S.

The energy potential of long-period oscillations is estimated by comparing it with watercourse power. The relaxation time of long-period waves is chosen for the estimation time interval, during which their amplitude decreases e (Euler's number) times from the initial one. According to calculations, the amount of energy produced during this time by the watercourse is 9.35–18.71 million kW×h, while the amount of energy of long-period oscillations is 3–6 times less – 1.60–5.48 million kW×h. The components of the economic factor of using long-period waves and currents for electricity production are the predictability of their magnitudes and location of maxima, long-term availability, concentration.

Microgrid is one of the promising green transition technologies that will provide enormous benefit to the seaport, as a solution to the major concerns in this sector, namely energy crisis, economical and environmental pollution. However, finest design of the microgrid is a challenging task considering different objectives, constraints and uncertainties involved. To ensure the optimal operation of the system, determining the right configuration framework and size for each component in the seaport microgrid at the minimum cost is a vital decision at the design stage. This paper aims to design a hybrid system of seaport microgrid with optimally sized component .The selected case study is the Port of Aalborg, Denmark. The proposed grid-connected structure consists of renewable energy sources (photovoltaic system and wind turbines), an energy storage system and cold ironing as seaport’ loads. The architecture is then optimized by utilizing HOMER to meet the maximum load demand by considering a few parameters such as solar global horizontal irradiance, temperature and wind resources. Then, the best configuration framework is analyzed in terms of economic feasibility, energy reliability and environmental impact.

The last half of the 20th century was characterized by the most impactful ecosystem changes throughout regulations and guidelines minimalizing environmental harms. Many of them emphasize the importance of enterprise sustainability for renewable energy policy. When dealing with numerous alternatives for the implementation of renewables-based policy, decision-makers need to analyze their impacts on environmental, economic, and social dimensions from a long-term perspective. The aim of this paper is to highlight a challenge to apply the multi-criteria sustainability decision-making framework (MDCA) to mainstream energy policy. The integrative framework covers an approach for the needs of analyzing factors influencing the energy technology selection. In this study, the MDCA-approach combines lifecycle-based methods, Analytical Hierarchy Process, PESTEL (Political, Economic, Social, Technological, Environment and Legal). To demonstrate the applicability and usability of the method three photovoltaic technologies are assessed. The results showed that string ribbon technology is the most sustainable along its life cycle, with a 0.503 sustainability score. The study highlighted the need to embody robust methodologies assessing sustainability-oriented technologies, not used anymore for supporting energy policies. This challenge regarding example evidence can give energy decision-makers a tool to realize their energy policy and in consequence, enhance enterprise sustainability.

The concept of DC power distribution has gained interest within the research community in the past years; especially due to rapid prevalence of solar PVs as a tool for distributed generation in DC microgrids. Various efficiency analyses have been presented for the DC distribution paradigm, in comparison to the AC counterpart, considering a variety of scenarios. However, even after a number of such comparative efficiency studies, there seems to be a disparity in the results of research efforts - wherein a definite verdict is still unavailable: 'Is DC distribution a more efficient choice as compared to the conventional AC system?' A final verdict is absent primarily due to conflicting results. In this regard, system modeling and the assumptions made in different studies play a significant role in affecting the results of the study. The current paper is an attempt to critically observe the modeling and assumptions used in the efficiency studies related to the DC distribution system. Several research efforts will be analyzed for their approach towards the system upon which they have performed efficiency studies. Subsequently, the paper aims to propose a model that may alleviate the shortcomings in earlier research efforts and be able to give a definite verdict regarding the comparative efficiency of DC and AC networks for residential power distribution.

Large office buildings are responsible for a substantial portion of energy consumption in urban districts. However, thorough assessments regarding the Nordic countries are still lacking. In this paper we analyse the largest dataset to date for a Nordic office building, by considering a case study located in Stockholm, Sweden, that is occupied by nearly a thousand employees.Distinguishing the lighting and occupants’ appliances energy use from heating and cooling, we can estimate the impact of occupancy without any schedule data. A standard frequentist analysis is compared with Bayesian inference, and the according regression formulas are listed in tables that are easy to implement into building performance simulations (BPS). Monthly as well as seasonal correlations are addressed, showing the critical importance of occupancy.A simple method, grounded on the power drain measurements aimed at generating boundary conditions for the BPS, is also introduced; it shows how, for this type of data and number of occupants, no more complexities are needed in order to obtain reliable predictions. For an average year, we overestimate the measured cumulative consumption by only 4.7%. The model can be easily generalised to a variety of datasets.

Almost fifty years after the first installations, I identify the main lessons learned from fighting drought and poverty in Africa with direct solar-powered pumps thanks to Father Bernard Verspieren and Mali Aqua Viva. Six main findings and three main recommendations emerge from the present analysis. They are of direct relevance to all Africa’s countries whose population has gone from 438 million in 1977 to 1,308 million in 2019, with about 600 million still having no access to electricity. In place of “awareness campaigns” and extraordinary courses held by international organizations, I recommend to establish national solar energy institutes whose task will include the education of solar energy professionals giving practice-oriented workshops on solar-powered drip irrigation and rainwater harvesting throughout each Africa’s country. Said education will critically include the economic and social aspects of distributed “generation” of energy and water from sunlight and rainfall.

Over the last two decades, residential buildings have accounted for nearly 50 percent of total energy use in New Zealand. In order to reduce household energy use, the factors that influence energy use should be continuously monitored and managed. Building researchers and professionals have made efforts to investigate the factors that affect energy use. However, few have concentrated on the association between household energy use and the cost of residential buildings. This study examined the correlation between household energy use and residential building cost. Analysis of the correlation between energy use data and residential building cost indicated that residential building cost in the construction phase and energy use in the operation stage were significantly correlated. These findings suggest that correct monitoring of building costs can help to identify trends in energy use. Therefore, this study proposes a time series model for forecasting residential building costs of five categories of residential building (one-story house, two-story house, townhouse, apartment, retirement village) in New Zealand. The primary contribution of this paper is the identification of the close correlation between household energy use and residential building costs and provide a new area for optimize energy management.

Although many devices have recently been proposed for pressure regulation and energy harvesting in water distribution and transport networks, very few applications are still documented in the scientific literature. A new in-line Banki turbine with positive outflow pressure and a mobile regulating flap, named PRS, was installed and tested in a real water transport network for pressure and discharge regulation. The PRS turbine was directly connected to a 55 kW asynchronous generator with variable rotational velocity, coupled to an inverter. The start-up tests showed how automatic adjustment of the flap position and the impeller velocity variation are able to change the characteristic curve of the PRS according to the flow delivered by the water manager or to the pressure set-point assigned downstream or upstream of the system, still keeping good efficiency values in hydropower production.

Solar green roofs, namely rooftops functionalized with properly selected living vegetation and photovoltaic modules, achieve an ideal symbiotic relationship in which promotion of biodiversity and onsite renewable energy production are both enhanced whereas the roof provides a wide range of environmental, health, aesthetic and economic benefits. This study provides a unified outlook of this eminent sustainable technology at the dawn of its uptake across the world, especially in polluted urban areas.

Considering the need to reduce greenhouse gas emissions, onshore wind energy is certain to play a major role in future energy systems. This topic has received significant attention from the research community, producing many estimations of Europe's onshore wind potential for capacity and generation. Despite this focus, previous estimates have relied on distribution assumptions and simulation schemes that summarily under predict both the amount of available future wind capacity as well as its performance. Foremost in this regard is the common use of contemporary, or at least near-future, turbine designs which are not fitting for a far-future context. To fulfill this role, an improved, transparent, and fully reproducible work flow is presented for determining European onshore wind potential. Within a scenario of turbine cost and design in 2050, 13.5 TWof capacity is found to be available, allowing for 34.4 PWh of generation. By sorting the explicitly-placed potential generation locations by their expected generation cost, national relations between turbine cost and performance versus a desired capacity are exposed. In this way, it is shown that all countries possess some potential for onshore wind energy generation below 4 €_ct kWh^-1. and, furthermore, that it is unlikely for these costs to exceed 6 €_ct kWh^-1.

The research field of energy system analysis is dealing with increasingly complex energy systems and their respective challenges. Moreover, the requirement for open science has become a focal point of public interest. Both drivers have triggered the development of a broad range of (open) energy models and frameworks in recent years. However, there are hardly any approaches on how to evaluate these tools in terms of their capabilities to tackle energy system modelling challenges. This paper describes a first step towards a flexible evaluation of software to model energy systems. We propose a qualitative approach as an useful supplementary to existing model fact sheets and transparency checklists. We demonstrate the applicability by evaluating the newly developed “Open Energy Modelling Framework” with respect to existing challenges in energy system modelling. The case study results highlight that challenges related to complexity and scientific standards can be tackled to a large extent while the challenges of model utilization and interdisciplinary modelling are only tackled partially. However, the challenge of uncertainty remains for the most part unaddressed at present. Advantages of the evaluation approach lie in its simplicity, flexibility and transferability to other tools. Disadvantages mostly stem from its qualitative nature. Our analysis reveals that some challenges in the field of energy system modelling cannot be addressed by a software as they are on meta level like model result communication and interdisciplinary modelling.

In 2018, Iran witnessed approximately 21,000 fatalities resulting from road accidents, ranking it as the fifth leading cause of death across all age groups. These incidents carry substantial economic and social burden for the nation, claiming more than 5% of its GDP. Human behavior emerges as a significant contributing factor to high-risk driving offenses. It has been proposed that by influencing general deterrence, a rigorous defense can be established against such violations. Various theories posit that by reinforcing or diminishing influential factors, general deterrence perception can be molded, presenting a potential avenue for an effective deterrent against traffic infractions. This study examines deterrence perceptions prevailing among the public in Iran regarding the enforcement of traffic laws. Employing Structural Equation Modeling (SEM), we delve into the intricate relationships between variables, allowing for a comprehensive exploration of the factors influencing general deterrence. The study draws on the data derived from a survey comprising 548 questionnaires for modeling purposes. An innovative concept, private sector enforcement, is introduced and incorporated into the questioning and modeling process. The findings reveal that socioeconomic status (p-value&lt;0.01), police enforcement (p-value&lt;0.05), private sector enforcement (p-value&lt;0.05), specific deterrence (p-value&lt;0.01), and the use of technology (p-value&lt;0.01) have direct and indirect impacts on the general deterrence perception of drivers.

A class of semi-linear elliptic equations with critical Hardy-Sobolev exponent has been considered. This model is widely used in hydrodynamics and glaciology, gas combustion in thermodynamics, quantum field theory and statistical mechanics, as well as gravity balance problems in galaxies. The $\left( PS\right) _{c}$ sequence of energy functional has been investigated, and then the mountain pass lemma was used to prove the existence of at least one nontrivial solution. Also a multiplicity result has been obtained. Some known results have been generalized.

Heat waves represents a major concern for the tourism industry in the Mediterranean area. Therefore, it is necessary to deepen the study of the influence of high temperatures and their effects on tourist behavior. This research aims to develop a structural model that allows measuring how heat waves affect the behavior of external tourist demand in coastal destinations. The results are useful for the design by tourist destinations of adaptation measures to climate change. The proposed hypotheses have been contrasted using non-linear structural equations (SEM), estimated with data from the National Institute of Statistics on external demand in Spain. The results confirm lower tourist flows with the increase in high temperatures to the coasts of the Spanish Mediterranean area from traditional source markets, such as the United Kingdom. Furthermore, the tourist flow to the Balearic Islands decreases with high temperatures.

This paper is a study of a generalization of the quantum Riemannian Hamiltonian evolution, previously analyzed by us in our work [6], in the geometrization of quantum mechanical evolution in a Finsler geometry. We find results with dynamical equations governing the evolution of the trajectories defined by the expectation values of position. The analysis appears to provide an underlying geometry described by a geodesic equation, with connection form with a second term which is an essentially quantum effect. These dynamical equations provide a new geometric approach to the quantum evolution where we suggest a definition for "local instability" in the quantum theory.

Although the empirical Kepler’s laws can be proven by applying Newton’s laws to the dynamics of two particles attracted due to the gravitational interaction, there is no explicit formula for the motion as a function of time. In this paper, a quasi-analytical solution for this problem is proposed. It approximates the real behavior of celestial bodies with an acceptable degree of accuracy. All calculations involved require a low computational cost. This problem is closely related to Kepler’s equation, since, the solution for the equations of motion as a function of time gives us the solution to Kepler’s equation as well. The results are presented for each planet of the solar system (including Pluto), and the solution is compared against the real orbits.

This study investigates how customers’ technological readiness affects service quality and the adoption of self-service banking by developing an empirical model. The model was proposed to explore the relationships between technology readiness, self-service quality, and customer satisfaction. The hypotheses and stability of the model were tested using structural equation modeling. The findings revealed that technology readiness, including the optimism, innovation, and insecurity dimensions, had a significant positive impact on self-service quality. In addition, service quality fully mediated the relationship between technological readiness and customer satisfaction. These results suggest that when customers are ready to embrace and use new technology, their evaluation of service quality is high. Thus, bank managers should drive customer perceptions of the quality of self-service banking by improving their technological readiness through various measures. Furthermore, based on the mediating effect of self-service quality, banks must be aware that improving service quality can enhance customer satisfaction and maintain a competitive advantage.

This manuscript presents a novel approach to estimating the potential within Schrödinger equations, with a particular focus on applications to the Navier-Stokes problem in fluid dynamics. By establishing new theoretical estimates, we delve into the intricate dynamics of fluid flow, aiming to unveil previously obscured aspects of the Navier-Stokes equations. Through a rigorous mathematical framework, we explore how these new potential estimates can provide a fresh perspective on fluid mechanics, contributing to the ongoing quest to solve some of its most persistent challenges.

In this paper, a class of semi-linear elliptic equations involving Hardy-Sobolev critical exponents has been investigated. This problem comes from the consideration of standing waves in the anisotropic Schr\"{o}dinger equation, also it is very important in the field of hydrodynamics, glaciology, quantum field theory and statistical mechanics. By a detailed estimation for the extremum function and using Mountain Pass Lemma with $\left( PS\right) _{c}$ conditions, the existence of positive solutions has been obtained. On the other hand, by establishing Pohozaev-type identity and using the properties of Bessel function, the nonexistence of positive solution also has been obtained. These results are extensions of E. Jannelli's research (\cite[Theorem 1.A-1.C]{EJ}).

The aim of the study is to explore how sharing status updated and receiving Likes on Facebook, as a form of positive social feedback, correlates with current and perceived changes in Quality of Life (QoL) Sample consisted of 1577 adult Facebook users (76.3% females; 65.9% aged 18-24, 21.9% aged 25-30, 12.3% aged &gt; 30 years old). The study employed a longitudinal approach, collecting Facebook data from adult users over a 12-month period using the Graph API. Data were divided into 12 monthly segments. Two monthly indicators were calculated: the percentage of textual status updates and the average number of Likes per post. Current and perceived changes in Quality of Life (QoL) were administered as self-report measures. The findings indicated a positive correlation between the frequency of textual Facebook posts and the average received Likes. Furthermore, receivign more Likes was positively associated with a higher current QoL, and perceived improvements in QoL correlated with an increase in Likes over time. The study suggests that online positive social feedback, measured through Likes on Facebook, is associated with both current QoL and perceived improvements in QoL among adult Facebook users. This highlights the potential impact of online social interactions on individual well-being.

This study derives space travel pricing by Walrasian Equilibrium, which is logical reasoning from the general relativity theory (GRT), the accounting equation, and economic supply and demand functions. The Cobb-Douglas functions embed the endogenous space factor as new capital to form the space travel firm's production function, which is also transformed into the consumer's utility function. Thus, the market equilibrium occurs at the equivalence of supply and demand functions, like the GRT presents the equivalence between the spatial geometric tensor and the energy-momentum tensor, which explains the principles of gravity and the motion of space matter in the spacetime framework. The mathematical axiomatic set theory of the accounting equation explains the equity premium effect that causes a short-term accounting equation inequality, then reaches the equivalence by suppliers' incremental equity through the closing accounts process of the accounting cycle. On the demand side, the consumption of space travel can be assumed as a value at risk (VaR) investment to attain the specific spacetime curvature in an expected orbit. Spacetime market equilibrium is then achieved to construct the space travel pricing model. The methodology of econophysics and analogy method was applied to infer the space travel pricing by the model of profit maximization, single-minded, and envy-free pricing in unit-demand markets. A case study with simulation was conducted for empirical verification of the math models and algorithm. Results show that space travel pricing remains the principle of market equilibrium but needs to be extended to the spacetime tensor of GRT.

This research provides a computationally efficient numerical tool for predicting 3-D turbulent flows over hydrofoils. It addresses a gap in existing numerical methods by extending the capabilities of the laminar VIScous Vorticity Equation (VISVE) solver to handle 3-D turbulent flow scenarios. The implementation integrates the k − ω SST model into the 3-D VISVE solver using the Finite Volume Method (FVM), extending its capability to handle turbulent flows. The turbulence model is also parallelized to improve computational efficiency. The application of the newly developed model to 3-D hydrofoil cases expands its scope and serves as preparatory work for future rotational propeller applications. Rigorous testing includes a convergence analysis concerning grid numbers and time step sizes, and validation against a Reynolds-Averaged Navier-Stokes (RANS) solver ensures the reliability and accuracy of the enhanced VISVE solver for turbulent flow simulations. The turbulent VISVE solver offers advantages such as reduced computational domain and costs through a vorticity-based approach. Turbulence concentration within boundary layers and free shear flows does not compromise the advantages of the small computational domain. The simplified meshing process, automatically generated by denoting the number of panels on the hydrofoil, makes the solver accessible for researchers and engineers.

A mathematical model that comprehensively captures the real behavior of riverbed deformation, encompassing all pertinent effects, is developed. The underwater slope reformation process, with the generatrix aligned along the flow velocity in the model, is considered. A numerical model is introduced to calculate the flow involving a deformable bottom, and the model's validation is established through rigorous analysis of experimental findings. The research firmly confirms the suitability of the proposed mathematical and numerical model for describing deformations in uneven and unsteady river flows, including the movement of dredging slots and channel quarries. The model's minimal equation count and reliance on empirical constants demonstrate the model's efficiency. The model's predictions align strongly with experimental data, although optimal values of empirical coefficients vary slightly across different experiments. Hence, there is a call for further investigation to derive more universally applicable closure relationships for the model. The importance of validating the model with reliable field data and its potential extension to accommodate hydraulically diverse soils is emphasized. Such an extension is feasible due to the concentration transfer equation, enabling independent calculations for particle fractions of varying sizes as long as the total particle concentration in the stream remains within reasonable limits. This dedicated research contributes significantly to understanding riverbed deformations and advancing accurate modeling and management of riverine environments.

We discuss the optimal control formulation for enhancement and denoising of satellite multiband images and propose to take it in the form of an L1-control problem for quasi-linear parabolic equation with non-local p[u]-Laplacian and with a cost functional of a tracking type. The main characteristic feature of the considered class of parabolic problems is the fact that the variable exponent p(t,x) and the anisotropic diffusion tensor D(t,x) are not well predefined a priori, but instead these characteristic non-locally depend on a solution of this problem, i.e., pu=p(t,x,u) and Du=D(t,x,u). We prove the existence of optimal pairs with sparse L1-controls using for that the indirect approach and a special family of approximation problems.

TThis paper delves into the extension and characterization of radial positive definite functions into non-integer dimensions. We provide a thorough investigation by employing the Riemann-Liouville fractional integral and fractional Caputo derivatives, enabling a comprehensive understanding of these functions. Additionally, we introduce a secondary characterization based on the Bernstein characterization of completely monotone functions. The practical significance of our study is showcased through an examination of the positivity of the fundamental solution of the space-fractional Bessel diffusion equation, highlighting the real-world applicability of the developed concepts. Through this work, we contribute to the broader understanding of radial positive definite functions and their utility in diverse mathematical and applied contexts.

This study uses machine learning to predict the convergence results of the Duffing equation with and without damping. The Duffing equation represents a nonlinear second-order differential equation with interesting behavior in undamped free vibration and forced vibration with damping. Convergence alternates randomly between 1 and -1 in undamped free vibration, depending on initial conditions. For forced vibration with damping, multiple factors influence vibration patterns. We utilize the fourth-order Runge-Kutta method to collect convergence results for both conditions. Machine learning techniques, specifically the long short term memory (LSTM) and LSTM-Neural Network (LSTM-NN) method, are employed to predict these convergence values. The LSTM-NN model is a hybrid approach that combines the LSTM method with the addition of hidden layers of neurons. Both the LSTM and LSTM-NN models are thoroughly explored and analyzed in this research. The research process involves three stages: data preprocessing, training, and verification. The results show that the LSTM-NN model becomes more adept at predicting binary datasets, boasting an impressive accuracy of up to 98%. However, when it comes to predicting multiple solutions, the traditional LSTM method outperforms the LSTM-NN approach.

A family of singularly perturbed q-difference-differential equations under the action of a small complex perturbation parameter is studied. The action of the formal monodromy around the origin is present in the equation, which suggests the construction of holomorphic solutions holding logarithmic terms in both, the formal and the analytic level. We provide both solutions and describe the asymptotic behavior relating them by means of q-gevrey asymptotic expansions of some positive order, with respect to the perturbation parameter. On the way, the development of a space product of Banach spaces in the Borel plane is needed to provide a fixed point for a coupled system of equations.

We consider the propagation of electromagnetic waves in the Friedman – Lemaître – Robertson – Walker metric. The exact solutions for plane and spherical wave are written down. The corresponding redshift, amplitude change, and dispersion are discussed. We also speculate about the connection of the electromagnetic wave equation to the Klein–Gordon equation.

The Chebyshev collocation method (ChC) implemented as Chebfun is used in order to solve a class of second order one-dimensional singular and genuinely nonlinear boundary value problems. Efforts to solve these problems with conventional ChC have generally failed, and the outcomes obtained by finite differences or finite elements are seldom satisfactory. We try to fix this situation using the new Chebfun programming environment. However, for toughest problems we have to loosen the default Chebfun tolerance in Newton's solver as the ChC runs into trouble with ill-conditioning of the spectral differentiation matrices. Although in such cases the convergence is not quadratic the Newton updates decrease monotonically. This fact, along with the decreasing behaviour of Chebyshev coefficients of solutions, suggests that the outcomes are trustworthy, i.e., the collocation method has exponential (geometric) rate of convergence or at least an algebraic rate. We consider first a set of problems that have exact solutions or prime integrals and then another set of benchmark problems that do not possess these properties. Actually, for each test problem carried out we have determined how Chebfun solution converges, its length, the accuracy of the Newton method and especially how well the numerical results overlap with the analytical ones (existence and uniqueness).

Inverse problems of recovering surface fluxes on the boundary of a domain from pointwise observations are considered. Sharp conditions on the data ensuring existence and uniqueness of solutions in Sobolev classes are exposed. They are smoothness conditions on the data, geometric conditions on the location of measurement points, and the boundary of a domain. The proof relies on asymptotics of fundamental solutions to the corresponding elliptic problems and the Laplace transform. The problem is reduced to a linear algebraic system with a nondegerate matrix.

In this paper after introducing a model of binary data matrix (BDM) for physical parameters of an evolving system (of particles), we develop a Hilbert space as an ambient space to derive induced metric tensor on embedded parametric manifold identified by associated joint probabilities of particles observables (parameters). Parameter manifold assumed as space-like hypersurface evolving along time axis, an approach that resembles 3+1 formalism of ADM and numerical relativity. We show the relation of endowed metric with related density matrix. Identification of system density matrix by this metric tensor, leads to the equivalence of quantum Liouville equation and metric compatibility condition while covariant derivative of metric tensor has been calculated respect to Wick rotated time or spatial coordinates. After deriving a formula for expected energy per particles, we prove the equality of this expected energy with local scalar curvature of related manifold. We show the compatibility of BDM model with Hamilton-Jacobi formalism and canonical forms. On the basis of the model, I derive the Ricci flow like dynamics as the governing dynamics and subsequently derive the action of BDM model and Einstein field equations. Given examples clarify the compatibility of the results with well-known principles such as equipartition energy principle and Landauer’s principle. This model provides a background for geometrization of quantum mechanics compatible with curved manifolds and information geometry. Finally, we conclude a “bit density principle” which predicts the Planck equation, De Broglie wave particle relation, , Beckenstein bound and Bremermann limit.

The nonlocal boundary value problem, dtρu(t)+Au(t)=f(t) (0&lt;ρ&lt;1, 0&lt;t≤T), u(ξ)=αu(0)+φ (α is a constant and 0&lt;ξ≤T), in an arbitrary separable Hilbert space H with the strongly positive selfadjoint operator A, is considered. The operator dt on the left hand side of the equation expresses either the Caputo derivative or the Riemann-Liouville derivative; naturally, in the case of the Riemann - Liouville derivatives, the nonlocal boundary condition should be slightly changed. Existence and uniqueness theorems for solutions of the problems under consideration are proved. The influence of the constant α on the existence of a solution to problems is investigated. Inequalities of coercivity type are obtained and it is shown that these inequalities differ depending on the considered type of fractional derivatives. The inverse problems of determining the right-hand side of the equation and the function φ in the boundary conditions are investigated.

The purpose of this paper is to find the time optimal control to a target set for semilinear stochastic functional differential equations involving time delays or memories under general conditions on a target set and nonlinear terms even though the equations contain unbounded principal operators. Our research approach is construct a fundamental solution for corresponding linear systems and establish variations of constant formula of solutions for given stochastic equations. The existence result of time optimal controls for one point target set governed by the given semilinear stochastic equation is also established.

The rapid growth of the organic food market in Italy and in other developed countries has drawn the attention of researchers and practitioners. The diffusion of pro-environmental concerns and sustainable lifestyles among consumers are often cited as two of the main drivers of the increase in demand for organic food products. Consequently, unveiling the factors that influence consumers’ demand of, and preference for organic food is essential for all the actors involved in the supply chain. This paper presents the results of a research model which relates organic food purchase intention to consumers’ green consciousness, health motivations, food safety concerns, organic product knowledge, family and social context and perception of the intrinsic quality of food. A questionnaire, based on the Theory of Planned Behavior (TPB) and the extant literature on organic food choice, was developed and presented to a sample of 600 Italian consumers. Causal relations among variables were then tested using Structural Equation Modelling. The results suggest that, besides the existence of green consciousness, other variables may affect consumers’ preference for organic food: among these, specific and closely interlinked elements, such as food safety concerns and perceived quality heavily affected the intention to buy organic food products.

In this article, we present a comparative study between the Adomian Decomposition Method (ADM) and Variational Iteration Method (VIM). The study outlines the significant features of the two methods, for solving nonlinear Volterra-Fredholm integro-differential equations. From the computational viewpoint, the VIM is more efficient, convenient and easy to use. Moreover, we proved the existence and uniqueness results and convergence of the solution. Finally, an example is included to demonstrate the validity and applicability of the proposed techniques.

This paper inquires on the options pricing modeling using Artificial Neural Networks to price Apple(AAPL) European Call Options. Our model is based on the premise that Artificial Neural Networks can be used as functional approximators and can be used as an alternative to the numerical methods to some extent, for a faster and an efficient solution. This paper provides a neural network solution for two financial models, the BlackScholes-Merton model, and the calibrated-Heston Stochastic Volatility Model, we evaluate our predictions using the existing numerical solutions for the same, the analytic solution for the Black-Scholes equation, COS-Model for Heston’s Stochastic Volatility Model and Standard Heston-Quasi analytic formula. The aim of this study is to find a viable time-efficient alternative to existing quantitative models for option pricing.

Abstract: The article proposes to consider the possibility of connecting the problems of engineering synthesis of frequency control systems for asynchronous electric drives with the basic provisions of the theory of identification of asynchronous electric motors based on the equations of a generalized AC electric machine.The article presents the results of experimental studies of load parrying processes in asynchronous electric drives with vector and scalar controls. These results indicate the absence of fundamental advantages as processes in a drive with vector control. This advantage should have manifested itself in a more efficient formation of the moment and fast transients. It is suggested that the reason for this is in too significant errors, assumptions and simplifications of the equations adopted in the derivation of vector control and which are its theoretical basis. A method is proposed for describing asynchronous electric motors by nonlinear transfer functions, which made it possible to formulate the principle of correction of electric drives and a method for assessing their efficiency.The article shows. that the correction based on the proposed nonlinear transfer functions of the induction motor is much more efficient than the traditional vector control, which was confirmed by detailed experiments and modeling. The results of the most important of which are given in the article. An assumption was made. that the advantage in efficiency is due to a more accurate identification of the dynamics of an asynchronous electric motor with a gear function instead of vector equations.

The purpose of this study was to assess the extent to which self-esteem and depression mediated the influence of internalized stigma on life satisfaction among Korean out-of-school youths. Cross-sectional data on 318 youths provided information on perceived stigma, self-esteem, depression, life satisfaction, and personal characteristics. A multinomial logistic regression analysis was followed by structured path analysis to investigate the mediation effects. Internalized stigma was negatively associated with life satisfaction. Self-esteem significantly mediated the influence of stigma on depression and the influence of depression on life satisfaction. Further, stigma directly and significantly influenced depression. This study demonstrated that self-esteem and depression were important to the relationship between internalized stigma and life satisfaction. Implications for possible policies and programs with the aim of helping out-of-school youths to integrate and lead successful satisfying lives are discussed.

This document focuses attention on the fundamental solution of an autonomous linear retarded functional differential equation (RFDE) along with its supporting cast of actors: kernel matrix, characteristic matrix, resolvent matrix, and the Laplace transform. The fundamental solution is presented in a form of the convolutional powers of the kernel matrix in the manner of a convolutional exponential matrix function. The fundamental solution combined with a solution representation gives an exact expression in explicit form for the solution of a RFDE. Algebraic graph theory is applied to the RFDE in the form of a weighted loop-digraph to illuminate the system structure and system dynamics and to identify the strong and weak components. Examples are provided in the document to elucidate the behavior of the fundamental solution. The paper introduces fundamental solutions of other functional differential equations.

Hot deformation at elevated temperature is essential to densify the particle reinforced Aluminum matrix composites (AMCs) and improve their performance. However, hot deformation behavior of the AMCs is sensitive to the variation of hot processing parameters. In this paper, optimal processing parameters of the dual-scale SiCp/A356 composites was determined to explore the control strategy of the microstructure. Hot compression tests were conducted at the temperature ranging from 460 to 520℃ under strain rates from 0.01 to 5 s−1. Constitutive equation and processing maps were presented to determine the hot processing parameters. Microstructure evolution of the dual-scale SiCp/A356 composites was analyzed. The strain rate of 0.62 ~ 5s-1 and deformation temperature of 495 ~ 518℃ is suitable for the hot processing. The number of DRX grains in the “safe” domains is larger and the dislocation density is lower compared to those of instability domains. DRX particles mainly occurred around SiC particles. The presence of SiC particles can promote effectively the DRX nucleation, which result in that the dynamic softening mechanism of the dual-scale SiCp/A356 composites is dominated DRX.

Understanding the stability limit of crystalline materials under variable tensile stress conditions is of capital interest for their technological applications. In this study, we present results from first-principles density functional theory calculations that quantitatively account for the response of selected covalent and layered materials to general stress conditions. In particular, we have evaluated the ideal strength along the main crystallographic directions of 3C and 2H polytypes of SiC, hexagonal ABA stacking of graphite and 2H-MoS2. Transverse superimposed stress on the tensile stress was taken into account in order to evaluate how the critical strength is affected by these multi-load conditions. In general, increasing transverse stress from negative to positive values leads to the expected decreasing of the critical strength. Few exceptions found in the compressive stress region correlate with the trends in the density of bonds along the directions with the unexpected behavior. In addition, we propose a modified spinodal equation of state able to accurately describe the calculated stress-strain curves. This analytical function is of general use and can also be applied to experimental data anticipating critical strengths and strains values and providing informattion on the energy stored in tensile stress processes.

In this paper, we analyze the Hawking radiation phenomenon for types of Banados-Teitelboim-Zanelli-like (BTZ-like) black holes. For this purpose, using the Hamilton-Jacobi method, we consider semi-classical WKB approximation to calculate the tunneling probabilities of massive boson particles. For these particles, we use the equation of motion for the Glashow-Weinberg-Salam model. Using quantum tunneling process of charged massive bossons, we compute the corresponding Hawking temperatures. Furthermore, we discuss the effects of rotation parameter on tunneling probability and temperature.

We propose a generalization of Nambu-Hamilton equation in superspace $\mathbb R^{3|2}$ with three real and two Grassmann coordinates. We construct the even degree vector field in the superspace $\mathbb R^{3|2}$ by means of the right-hand sides of proposed generalization of Nambu-Hamilton equation and show that this vector field is divergenceless in superspace. Then we show that our generalization of Nambu-Hamilton equation in superspace leads to family of ternary brackets of even degree functions defined with the help of Berezinian. This family of ternary brackets is parametrized by the infinite dimensional group of invertible second order matrices, whose entries are differentiable functions on the space $\mathbb R^{3}$. We study the structure of ternary bracket in a more general case of a superspace $\mathbb R^{n|2}$ with $n$ real and two Grassmann coordinates and show that for any invertible second order functional matrix it splits into the sum of two ternary brackets, where one is usual Nambu-Poisson bracket, extended in a natural way to even degree functions in a superspace $\mathbb R^{n|2}$, and the second is a new ternary bracket, which we call $\Psi$-bracket, where $\Psi$ can be identified with invertible second order functional matrix. We prove that ternary $\Psi$-bracket as well as the whole ternary bracket (the sum of $\Psi$-bracket with usual Nambu-Poisson bracket) is totally skew-symmetric, satisfies the Leibniz rule and the Filippov-Jacobi identity (Fundamental Identity).

The ordinary continuity equation relating the current and density of a system is extended to incorporate systems with dual (longitudinal and transverse) currents. Such a system of equations is found to have the same mathematical structure as that of Maxwell equations. The horizontal and transverse currents and the densities associated with them are found to be coupled to each other. Each of these quantities are found to obey a wave equation traveling at the velocity of light in vacuum. London's equations of super-conductivity are shown to emerge from some sort of continuity equations. The new London's equations are symmetric and are shown to be dual to each other. It is shown that London's equations are Maxwell's equations with massive electromagnetic field (photon). These equations preserve the gauge invariance that is broken in other massive electrodynamics. The duality invariance may allow magnetic monopoles to be present inside superconductors. The new duality is called the comprehensive duality transformation.

There is need to accurately design pipelines to transport the expected increase of CO₂ captured from industrial processes after the signing of the Paris Climate Agreement in 2016. This paper reviews several aspects of CO₂ pipeline design with emphasis on pressure drop and models for the calculation of pipeline diameter. Two categories of pipeline equations were identified. The first category is independent of pipeline length and has two different equations. This category is used to specify adequate pipeline diameter for the volume of fluid transported. The optimum economic pipe diameter equation (Eq. 17) with nearly uniform resultant velocity values at different flow rates performed better than the standard velocity flow equation (Eq. 20). The second category has four different equations and is used to calculate pipeline pressure drop or pipeline distance for the installation of booster stations after specifying minimum and maximum pipeline pressures. The hydraulic equation is preferred because it gave better resultant velocity values and the closest diameter value obtained using Aspen HYSYS (V.10) simulation. The effect of impurities on the pressure behaviour and optimal pipeline diameter and pressure loss due to acceleration were ignored in the development of the models. Further work is ongoing to incorporate these effects into the models.

This paper describes the development of a two-dimensional water quality model that solves hydrodynamic equations tied to transport equations with reactions mechanisms inherent in the processes. This enable us to perform an accurate assessment of the pollution in a coastal ecosystem. The model was developed with data drawn from the ecosystem found in Mexico's southeast state of Tabasco. The coastal ecosystem consists of the interaction of El Yucateco lagoon with the Chicozapote and Tonalá rivers, that connect the lagoon with the Gulf of Mexico. We present the results of pollutants transport simulation in the coastal ecosystem, focusing on toxic parameters for two hydrodynamic scenarios: wet and dry seasons. As it of interest in the zone, we study the transport of four metals: Cadmium, Chromium, Nickel and Lead. In order to address our objectives we solved numerically a self-posed mathematical problem,which is based on the measured data. The performed simulations show to characterise metal transport within the acceptable range of accuracy and in accordance with the measured data. The performed simulations show to characterise metals transport with an acceptable accuracy, agreeing well with measured data in total concentrations in four control points along the water body. Although for the accurate implementation of the hydrodynamic-based water quality model herein presented, boundary (geometry, tides, wind, etc.) and initial (concentrations measurements) conditions are required, it poses as an excellent option when the distribution of solutes with high accuracy is required, easing environmental, economic and social management of coastal ecosystems.

Restoration experience is a positive response against the ever-increasing problem of stress. It is recovery of attentional capacity, clearing random thoughts and feelings of relaxation and calmness. Although there is a body of research on investigating the impact of open green space characteristics on psycho- logical restoration through attention restoration theory and supportive environment theory, there is little knowledge on how the interaction among these characteristics could promote restorative outcomes. To address this problem, using Perceived Sensory Dimension (PSD) for open green space qualities and Perceived Restorativeness (PR) as the property of restorative environment, this study assessed the extent to which the PSD and PR impact on restoration experience. Using 444 screened surveys, a Partial Least Square Structural Equation Model (PLS-SEM) was developed and the validity and reliability of it, was demonstrated. Extensive analysis of the results showed how environmental qualities can promote restoration experience using a sample of university students. These results provide information for landscape architecture and planning researchers to promote the development of open spaces as a resource of psychological restoration and stress relief.

In this paper, we consider a fourth-order suspension bridge equation with nonlinear damping term |u_t|^m-2u_t and source term |u|^p-2u. We give necessary and sufficient condition for global existence and energy decay results without considering the relation between m and p. Moreover, when p>m, we give sufficient condition for finite time blow-up of solutions. The lower bound of the blow-up time T_max is also established. It worth to mention that our obtained results extend the recent results of Wang (J. Math. Anal. Appl., 2014) to the nonlinear damping case.

Biohydrogen is a versatile energy carrier for the generation of electric energy from renewable sources. Hydrogenases can be used in enzymatic fuel cells to oxidize dihydrogen. The rate of electron transfer (ET) at the anodic side between the [NiFe]-hydrogenase enzyme distal iron-sulfur cluster and the electrode surface can be described by the Marcus equation. All parameters for the Marcus equation are accessible from DFT calculations. The distal cubane FeS-cluster has a three cysteine and one histidine coordination [Fe₄S₄](His)(Cys)₃ first ligation sphere. The reorganization energy (inner- and outer-sphere) is almost unchanged upon a histidine-to-cysteine substitution. Differences in rates of electron transfer between the wild-type enzyme and the all-cysteine mutant can be rationalized by a diminished electronic coupling between the donor and acceptor molecules in the [Fe₄S₄](Cys)₄ case. The fast and efficient electron transfer from the distal iron-sulfur cluster is realized by a fine-tuned protein environment which facilitates the flow of electrons. This study enables the design and control of electron transfer rates and pathways by protein engineering.

In the present study, we derive a new B-spline technique namely trigonometric B-spline collocation algorithm to solve some initial boundary value problems for the nonlinear Klein-Gordon equation. In order to carry out the time integration with Crank-Nicolson implicit method, the order of the equation is reduced to give a coupled system of nonlinear partial differential equations. The collocation approximation based on trigonometric cubic B-splines for spatial discretization is followed by the linearization of the nonlinear term. The efficiency and accuracy of the present method are validated by measuring the error between the numerical and analytical solutions when exist. The conservation laws representing momentum and energy are also computed for all problems.

This paper proposes an optimization method for the scheduling of a multi-energy virtual power plant supply-demand balance in the power market environment of Jiangxi Province. The objective of this method is to enhance the operational efficiency of the power grid, reduce energy costs, and facilitate economical and efficient energy distribution in the power market. The method comprehensively considers the characteristics and uncertainties of renewable energy sources such as solar and wind energy, and incorporates advanced multi-objective optimization algorithms. Additionally, real-time market price feedback is integrated to achieve accurate allocation of power supply and demand. Through a case study of a multi-energy virtual power plant in Jiangxi Province, this paper examines the optimal combination model for various energy sources within VPP, and analyzes the impact of different market environments on supply-demand balance. The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. Compared with traditional power supply models, it reduces average electricity costs by 15% and increases renewable energy utilization efficiency by 20%.

Electrifying off-grid and isolated islands in the Philippines remains one of the challenges that hinders community development. One of the solutions seen to ensure energy security, expand energy access and promote a low carbon future in this isolated islands is the use of renewable energy sources. This study wishes to determine the nearshore wave energy resource during monsoon seasons in Cuyo Island using a 40-year wave hindcast and 9-year on-site wind speed data to develop high resolution wave energy model using SWAN wave model, and assessed its annual energy production through matching with wave energy devices. Results shows that average significant wave height (Hs), peak period (Tp) and wave power density (Pd) during northeast monsoon are Hs = 1.35 m, Tp = 4.79 s and Pd = 4.05 kW/m respectively, while southwest monsoon which is sheltered by the mainland resulted to a lesser outcome, Hs = 0.52 m, Tp = 3.37 s and Pd = 0.34 kW/m. While the simulated model was observed to overestimate the wave energy resource (Bias = 0.398, RMSE = 0.54 and SI = 1.34), it has a strong relationship with the observed values (average r = 0.9). Its annual energy production is highest at Station 5, with AEPWaveBouy = 43.761 MWh, AEP-Pelamis = 216.786 MWh and AEPWave Dragon = 2462.66 MWh. At present, the minimum requirement for a wave energy development to be feasible is 5 kW/m, which in this case, Cuyo Island falls short, but with the continuous evolution of wave energy converters, applications on milder re-sources will soon materialized.

The article examines the evolution and resilience of the Spanish desalination industry in response to changing market conditions and technological challenges. Initially focused on domestic projects, Spanish companies leveraged the A.G.U.A. Program to gain expertise, which later facilitated their successful international expansion as local demand diminished. The industry has adapted to varying international regulations and local conditions, demonstrating flexibility and competitiveness. In recent years, there has been a growing emphasis on integrating renewable energy into desalination processes to address rising energy costs and environmental concerns. This shift not only reduces CO2 emissions but also stabilizes operational costs, highlighting the sector’s ongoing innovation and adaptability.

This paper examines the determinants of CO2 emissions in Oman from 1990 to 2022, focusing on the impacts of energy consumption, economic growth, urbanization, financial development, and foreign direct investment. Utilizing stepwise regression, robust least squares, Fully Modified Least Squares (FMOLS), Canonical Cointegrating Regression (CCR), and various cointegration tests including the Johansen cointegration test, Engle-Granger cointegration test, and Vector Error Correction (VEC) model, the study reveals several key findings. Energy use per capita (ENGY) and real GDP per capita (RGDPC) are consistently significant positive predictors of CO2 emissions. Urbanization (URB) also significantly contributes to higher emissions. Conversely, Financial Development Index (FDX) and foreign direct investment (FDI) do not show significant effects on CO2 levels. The high R-squared values across models indicate that these variables explain a substantial portion of the variation in emissions. Cointegration tests confirm long-term equilibrium relationships among the variables, with the Johansen test identifying two cointegrating equations and the Engle-Granger test showing significant tau-statistics for FDX, ENGY, and URB. The VEC model further highlights the short-term dynamics and adjustment mechanisms. These findings underscore the importance of energy policy, economic development, and urban planning in Oman's efforts towards sustainable development and decarbonization.

A platform for indoor monitoring inside buildings, integrating both conventional and environmentally friendly devices with energy-harvesting sources, is proposed. Biomaterials such as gelatin and chitosan, derived from renewable resources, have been utilized to fabricate hydrogel and active layers for sensors and supercapacitors. These devices enhance the environmental profile of the proposed solution by employing sustainable materials and optimizing energy consumption. The developed electronic board prototype provides a versatile platform for testing various sensor configurations while accommodating different energy-harvesting sources. The article details the design of an energy harvesting system for indoor monitoring, covering various aspects regarding energy sources, power management circuits, and low-power microcontroller units. It examines energy storage devices and sensors, including both eco-friendly and commercial ones, as well as radio transceivers with different communication technologies. Additionally, an energy analysis to evaluate the performance and energy efficiency of the platform is presented.

This study uses the Scopus and Web of Science databases to review the forecast of electricity consumption from 2015 to 2024. Based on the keywords used in the article title, which are associated with electricity consumption forecasts, the study retrieved 821 docu-ments for additional analysis using various techniques. For frequency analysis, we used Mi-crosoft Excel; for data visualisation, we used VOSviewer; and for citation metrics and analysis, we used Harzing's Publish or Perish. Standard bibliometric variables, including publication growth, authorship patterns, collaboration, prolific authors, national contribution, most active institutions, favourite journals, and highly cited articles, are used in this study's reporting of the findings. Our analysis indicates that over ten years, starting in 2015, publications on the forecasting of electricity consumption have continued to increase. China was the country that contributed the most to research on electricity consumption. Most of the research publications on electricity consumption were published in the Journal of Energy.

This Paper delves into a thorough analysis of the DC-DC buck converter tailored for renewable energy applications. Given the prevalent utilization of renewable resources producing DC voltages, this converter plays a pivotal role in stepping down high-level DC voltages to more manageable levels. The research focuses on varying the duty cycle to assess its impact on the converter's output voltage performance. Simulations conducted using PSIM are meticulously compared with hardware implementation results, demonstrating the converter's efficacy in generating significantly reduced output voltages. The findings underscore the practical applicability of this converter in renewable energy scenarios, offering a succinct yet insightful perspective on its performance and adaptability.

Energy harvesting is an emerging topic recently. This harvested energy is used to operate wireless sensors for different industrial monitoring and automation. To maximize the harvested energy in spinning systems, the harvester should vibrate at resonance for different spinning frequencies which can be achieved by active fitting. In this research, a novel methodology was developed by actively customizing the length of vibrating element beam to manipulate its natural frequency according to the spinning frequency. Different models were investigated numerically and experimentally to verify the proposed methodology. COMSOL Multiphysics software V5.1 was used to develop the numerical model, then and tip deformation and voltage difference results were benchmarked. The numerical model was verified experimentally by attaching a piezoelectric MIDE PPA 1021 which its vibrating length was varied by changing the supporting length from 0 mm to 12 mm to a spinning object having variable frequency from 0-200 Hz. It is found that the MIDE PPA 1021 beam vibrated at its resonance throughout the specified spinning frequencies. The proposed harvester can be applied in battery-free sensors being used in automotives, wind-mills blades, and rotating machinery.

Greenflation or inflation for green energy transition in Europe, it becomes a structural problem of new scarcity and poverty, because the Green Deal and its fiscal and monetary policies. In this paper, it is paid attention to the Green financial bubble and the European greenflation paradox: in order to achieve greater future social wellbeing, due to a looming climate risk, present wellbeing and wealth is reduced, causing a real and ongoing risk of social impoverishment. According to the European Union data, it is going to show the relations between green transition (emissions, tax, debt, credit boom, etc.), GDP and inflation. As many emissions are reduced, there is a decrease of GDP (once deflated) and GDP per capita, evidencing social deflation, which in turn means more widespread poverty and a reduction of middle-class. Also, there is a risk of a green-bubble, like in the Great Recession of 2008 (but this time supported by the European Union) and possible stagflation. To analyze this problem, it is used here some econometric tools, but under the theoretical support of heterodox approaches, especially the Austrian Economics and the New-Institutional Schools.

A large share of the reinforced concrete (RC) building stock in Mediterranean countries faces a dual challenge of seismic vulnerability and energy inefficiency, calling for urgent renovation efforts. While energy upgrades have been the focus of previous renovation policies, recent research highlights the critical need for integrated retrofitting solutions that address both structural integrity and energy performance. Multi-criteria decision-making (MCDM) approaches are a promising tool for optimizing the combined choice of these integrated interventions, considering various decision variables (DVs) of economic, social, environmental, and technical nature. To understand the impact of climate and seismic hazard conditions on multi-criteria-based retrofitting assessment, a case-study RC school building is selected and assumed to be located in three distinct climate conditions, cold, mild, and warm, and three seismic hazard levels, low, medium and high. Moreover, given the complexity and challenges of quantifying seismic performance metrics for practitioners, an available simplified (practice-oriented) approach is compared herein with a more thorough research-based one for quantifying the seismic performance of RC buildings within the MCDM framework. Both approaches are applied to the case-study building, considering twelve possible combinations of energy and seismic interventions. The accuracy of the practice-oriented approach and its impact on the retrofitting rankings is evaluated, emphasizing the importance of accessible and efficient evaluation methods in facilitating informed decision-making for building renovation

The article aims to present an alternative perspective on the relativistic expression of energy. This perspective is based on the virtual use of a Dempster mass spectrometer. In this spectrometer, it is possible to simulate Alfred Bucherer's experiment and conclude, using Lienard's relativistic equation, that the classical expression of energy predicted by Special Relativity is a more complete expression than the one presented by high school and college physics textbooks.

Greenhouses are instrumental in the advancement of regions globally. The geometric arrangement of these structures plays a pivotal role in governing sunlight distribution, facilitating ventilation, and managing condensation. The roof's shape significantly affects energy efficiency and the accumulation of condensation water, which, when dripping onto crops, can induce diseases and diminish production. This study introduces a Matlab program designed for defining and analyzing greenhouse roof geometry, adaptable to both single-span and multi-span structures. Various roof shapes are examined, determining angles along their length to facilitate condensation droplet runoff. Furthermore, the greenhouse's energy efficiency is evaluated by analyzing diverse roof models, accounting for surface area and internal air volume. The results aim to aid in selecting the optimal greenhouse type based on climate and latitude. This study offers a valuable decision-making tool for the planning and design of agricultural structures, providing insights to enhance overall sustainability and performance in diverse environmental contexts.

The accumulation of waste polymer in ecosystems is a problem that affects the environment on a global scale. This paper presents the design of Pwave+, a microwave pyrolysis system that has been optimized to recycle waste polymer into valuable hydrocarbon fuels and chemicals. Heating in a microwave oven is both volumetric and rapid, which improves the effectiveness of pyrolysis and the quality of the product. The production of waste polymer oil and gas products was boosted to its full potential by a continuous microwave vortex reactor. The product gases allowed for complete independence in terms of energy production. Modeling, simulation, and experimentation with advanced technology are used to optimize the pyrolysis parameters and the performance of the reactor. As a result, simulation and programming are solutions to problems. The results of this study demonstrated both the technical viability and the long-term viability of continuous microwave pyrolysis as a method for recycling mixed polymer waste streams. The Pwave+ continuous microwave vortex reactor is described in this study. It is capable of converting various polymer waste streams into hydrocarbon products as well as energy. The use of microwaves to assist in the pyrolysis process has the potential to cut down on plastic pollution and the amount of waste that is dumped in landfills. This could provide valuable insights for the design and commercialization of similar systems.

The surging electricity demand driven by a growing global population, coupled with the increasing electrification of industries, transportation, and power-intensive appliances, poses a substantial challenge to electricity systems worldwide. This challenge is further compounded by the pressing issue of climate change. To address climate change and mitigate the environmental consequences of fossil fuel use, renewable energy sources are expected to play a pivotal role. However, certain renewable sources, such as wind and solar, exhibit stochastic behavior, resulting in unpredictable power output and significant fluctuations. This intermittency presents a challenge in maintaining a stable and reliable power supply. To overcome this challenge and ensure a balanced electricity grid, the strategic deployment of energy storage devices throughout the power system becomes critically important. Energy storage technologies play a vital role in mitigating the mismatch between renewable power generation and consumption. Additionally, they enable the storage of surplus energy generated from renewable sources during periods of high production for later use during periods of low or no generation. Each technology possesses unique characteristics and applications, providing flexibility and diversity in energy storage solutions. This work provides an overview of different energy storage technologies and explores their role in establishing a sustainable power system.

A substantial body of phenomenological and theoretical work over the last few years strengthens the possibility that the vacuum energy density (VED) of the universe is dynamical, and in particular that it adopts the `running vacuum model' (RVM) form, in which the VED evolves mildly as $\delta \rho_{\rm vac}(H)\sim \nu_{\rm eff} m_{\rm Pl}^2{\cal O}\left(H^2\right)$, where $H$ is the Hubble rate and $\nu_{\rm eff}$ is a (small) free parameter. This dynamical scenario is grounded on recent studies of quantum field theory (QFT) in curved spacetime and also on string theory. It turns out that what we call the `cosmological constant', $\Lambda$, is no longer a rigid parameter but the nearly sustained value of $8\pi G(H)\rho_{\rm vac}(H)$ around (any) given epoch $H(t)$, where $G(H)$ is the gravitational coupling, which can also be very mildly running (logarithmically). Of particular interest is the possibility suggested in past works that such a running may help to cure the cosmological tensions afflicting the $\Lambda$CDM. In the current study, we reanalyze it in full and we find it becomes further buttressed. Using the modern cosmological data, namely a compilation of the latest SNIa+BAO+$H(z)$+LSS+CMB observations, we probe to which extent the RVM provides a quality fit better than the concordance $\Lambda$CDM model, paying particular emphasis on its impact on the $\sigma_8$ and $H_0$ tensions. We utilize the Einstein-Boltzmann system solver \texttt{CLASS} and the Monte Carlo sampler \texttt{MontePython} for the statistical analysis, as well as the statistical DIC criterion to compare the running vacuum against the rigid vacuum ($\nu_{\rm eff} = 0$). On fundamental grounds, $\nu_{\rm eff}$ receives contributions from all the quantized matter fields in FLRW spacetime. We show that with a tiny amount of vacuum dynamics ($|\nu_{\rm eff}|\ll 1$) the global fit can improve significantly with respect to the $\CC$CDM and the mentioned tensions may subside to inconspicuous levels.

Climate change, the scarcity of fossil fuels, technical advances in clean energy, and the volatility of crude oil prices are just a few of the factors that have prompted the world to recognize clean energy as a viable alternative to dirty energy. As part of the Paris Climate Accord of 2015, many countries agreed to change their economies to be more sensitive to climate change. Due to this Accord, which increased interest from investors and decision-makers, investments in clean energy companies have benefited [1,2]. Clean energy stocks, which are a part of the larger world of tradable reserves, might experience pricing inefficiencies. In this paper, we investigate the multifractal scaling behavior and efficiency of green finance markets, as well as traditional markets like gold, crude oil, and natural gas between January 1, 2018, and March 9, 2023, which covers periods of low volatility and financial instability (2020 and 2022 events). To test the serial dependency (autocorrelation) and the efficient market hypothesis, in its weak form, we employed the Lo and Mackinlay test and the DFA method. The empirical findings demonstrated that both periods exhibit severe multifractal and significant asymmetry, indicating that the price indices under study are not at all efficient.

This paper describes a stochastic clustering architecture that is used in the paper for making predictions over energy data. The design is discrete, localised optimisations based on similarity, followed by a global aggregating layer, which can be compared with the recent random neural network designs, for example. The topic relates to the IDEAS Smart Home Energy Project, where a client-side Artificial Intelligence component can predict energy consumption for appliances. The proposed data model is essentially a look-up table of the key energy bands that each appliance would use. Each band represents a level of consumption by the appliance. This table can replace disaggregation from more complicated methods, usually constructed from probability theory, for example. Results show that the table can accurately disaggregate a single source to a set of appliances, because each appliance has quite a unique energy footprint. As part of predicting energy consumption, the model could possibly reduce costs by 50% and more than that if the proposed schedules are also included. The hyper-grid has been changed to consider rows as single units, making it more tractable. A second case study considers wind power patterns, where the grid optimises over the dataset columns in a self-similar way to the rows, allowing for some level of feature analysis.

Glycine in its neutral form can exist in the gas phase while its zwitterion form is more stable in water solution.But how many waters are actually necessary to stabilize the zwitterionic structure in the gas phase? Are the intramolecular isotropic spin spin coupling constants sensitive enough to accuse the change in the environment? or the conformer observed? These and related questions have been investigated by a computational study at the level of density functional theory employing the B3LYP functional and the 6-31++G**-J basis set. We found that at least two water molecules explicitly accounted in the super-molecule structure are necessary to stabilize both conformers of glycine within a water polarizable continuum model. At least half of the SSCC’s of both conformers are very stable to changes in the environment and at least four of them differ significantly between Neutral and Zwitterion conformation.

Evidence is growing that mankind must learn from nature, a self-sufficient and self-organized system that adopts all the opportunities to develop life and ingeniously makes the most of whatever energy source. Attempting to satisfy the requirements of our energy-consuming world, we cannot afford to disregard any available source of energy, mainly those characterized by zero-CO₂ emissions. In this context an alternative scenario could be opened by the use of the nuclear radiations emitted from naturally occurring or artificially produced radionuclides. Abandoned mines of U, Th and Rare Earths , as well as storage areas of artificially produced isotopes all over the globe are available and affordable sources of radiations that can be converted in electrical power. The transition from laboratory-scale nuclear batteries to large-area converting modules would allow to safely re-use a big amount of already existing radionuclides, converting a trouble into a resource.

The decarbonization of the electrical energy sector is in progress for contrasting the climate changes, with a relevant increase of the Renewable Energy Sources (RES) power plants, mostly in Dispersed Generation (DG). The adequacy and the security of power systems, with a huge penetration of RES in DG is possible with a suitable integration of energy storage. In fact, energy storages are able to provide many different services for long-term adequacy and real time security. In this framework the present paper deals with a Thermal Energy Storage (TES) proposed for power system services. The technology presented is made up of modules containing a bed of fluidizable solid particles, which can store thermal energy from waste heat, process heat and/or from electricity. Stored thermal energy can be released, e.g. as superheated steam, for thermal uses or converted into electricity, by means of steam turbines. Some possible applications are then reported explaining advantages and limits.

It has been recognized for some time that even for perfect conductors, the interaction Casimir entropy, due to quantum/thermal fluctuations, can be negative. This result was not considered problematic because it was thought that the self-entropies of the bodies would cancel this negative interaction entropy, yielding a total entropy that was positive. In fact, this cancellation seems not to occur. The positive self entropy of a perfectly conducting sphere does indeed just cancel the negative interaction entropy of a system consisting of a perfectly conducting sphere and plate, but a model with weaker coupling in general possesses a regime where negative self-entropy appears. The physical meaning of this surprising result remains obscure. In this paper we re-examine these issues, using improved physical and mathematical techniques, partly based on the Abel-Plana formula, and present numerical results for arbitrary temperatures and couplings, which exhibit the same remarkable features.

Three typhoons (Rammasun, Kalmaegi, and Sarika) travelled through the deployed stations in the northern South China Sea from 2014–2016. During the passage of typhoons, strong winds and vigorous currents resulted in horizontal displacement of buoy over 2000 m, vertical displacement of ropes on buoys as much as 200 m. The rectification can correct the warm anomaly to cool anomaly of temperature. These movements lead to biases of raw data, with temperature bias as much as 4°C, salinity as much as 0.05 psu, velocity bias as much as 0.4 m/s. The crosscheck of current velocity from different instruments shows that the bias of overlapping velocity and correlation coefficient after depth rectification obviously enhances. The observation shows that temperature cools 1.5 °C, and 0.1 psu saltier in maximum, the near-inertial current increases to 0.4 m/s in the upper layer. The inertial kinetic energy propagates downward with the upward phase, and the maximum depth can reach over 2000 m.

Energy resources are important sources of social and economic development, human survival and security. However, energy resources are objective and scarce, especially the fossil energy, such as coal, oil, natural gas, etc. Human survival environment is increasingly damaged, and the condition of energy is also gradually becoming deficient, so it is necessary to develop new energy resources to meet the increasing demand of material civilization. Solar energy can meet the needs of human development in the future as a kind of clean resource and it has been concerned by all countries in the world. We analyzed the effectiveness of subsidies to the PV industry of both the price and R&D by the spatial econometric model. In some region, the production capacity of photovoltaic industry has shown a significant spatial agglomeration situation in China since 2012. At the same time, benchmarking price and R&D subsidies played a positive incentive to the photovoltaic industry production capacity. It is a certain degree of inverse correlation between the scale of policy subsidies and the resource endowment of solar resources. Therefore, the countermeasures should be considered from the aspects of institutions, industry, technology and public financial policies.

Our primary objective is to construct a plausible unified model of inflation, dark energy and dark matter from a fundamental Lagrangian action first principle, where all fundamental ingredients are systematically dynamically generated starting from a very simple model of modified gravity interacting with a single scalar field employing the formalism of non-Riemannian spacetime volume-elements. The non-Riemannian volume element in the initial scalar field action leads to a hidden nonlinear Noether symmetry which produces energy-momentum tensor identified as a sum of a dynamically generated cosmological constant and a dust-like dark matter. The non-Riemannian volume-element in the initial Einstein-Hilbert action upon passage to the physical Einstein-frame creates dynamically a second scalar field with a non-trivial inflationary potential and with an additional interaction with the dynamically generated dark matter. The resulting Einstein-frame action describes a fully dynamically generated inflationary model coupled to dark matter. Numerical results for observables such as the scalar power spectral index and the tensor-to-scalar ratio conform to the latest 2018 PLANCK data.

This paper proposes an ARIMA approach to battery health forecasting with accuracy improvement by K shape-based clustered predictors. The health prediction of the battery pack is an important function of a battery management system in data centers. Accurate forecasting of battery life turns out to be very difficult without failure data to train a good forecasting model in real life. The conventional ARIMA model is compared with total and clustered predictors for battery health forecasting. Results show that the forecasting accuracy of the ARIMA model significantly improved by utilizing the results of the clustered predictors for 40 batteries in a real data center. One year of actual historical data of 40 batteries of large scale datacenter is presented to validate the effectiveness of the proposed methodology.

To account for the very low mass density associated with Dark Energy and the Cosmological Constant, a new approach to the ground state of empty space is presented. The resulting model for the vacuum state associated with empty space proposes a crystalline-like texture for the chromatic structure of empty space. This vacuum state has the appropriate mass density and predicts acceleration for the Universe expansion. Furthermore, the model predicts that this texture is anisotropic and may lead to measurable changes in the production of electron and positron pairs by gamma rays incident on a solid crystal of low mass density such as graphite.

An increasing amount of electric energy is consumed by computers as they progress in function and capabilities. All of it is dissipated in heat during the computing and communicating operations and we reached the point that further developments are hindered by the unbearable amount of heat produced. In this paper we briefly review the fundamental limits in energy dissipation, as imposed by the laws of physics, with specific reference to computing and memory storage activities.

This paper updates earlier thoughts by the author on a putative propulsion system. The concept was based around static electromagnetic momentum, as expounded in the “Feynman Disk” and experimentally verified by Graham and Lahoz. That said, naïve static electromagnetic momentum schemes to achieve linear translation are defeated by “hidden momentum” mechanisms, so too are simple arrangements just cycling the fields; we shall survey the flaws in their arguments. It may however be possible to achieve linear translation by means of arrangements of torques with a novel mechanism to break the symmetry of forces (or torques) on the second half of the cycle as the field is switched off. At the time of earlier presentation no mechanism could be found to explain the momentum balance for the process but it was believed that momentum was being given to the zero-point of the field. We show that it is possible to dump angular momentum and thence linear momentum to the ground state by standard quantum analysis of the EM field. None of this violates the conservation of momenergy.

Ce³⁺ and Dy³⁺ ions doped Ca₂Al₂SiO₇ (CAS) phosphors were prepared by the solid-state reaction at 12800C for 1h. X-ray diffraction patterns confirmed a tetragonal crystalline structure. The luminescent spectra of CAS: Ce³⁺, Dy³⁺ phosphors consist a board band with peaking at 420 nm corresponding to the luminescence of Ce³⁺ ions and narrow lines of Dy³⁺ ions. The energy transfer from Ce³⁺ ion to Dy³⁺ ion is presented and discussed