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.

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.

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.

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.

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.

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.

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.

Previously reported atomic data (spectral lines, wavelengths, energy levels, and transition probabilities) have been collected and systematically analyzed for the Cs VI. The present theoretical analysis is supported by extensive calculations made for Cs VI with a pseudo-relativistic Hartree--Fock (HFR) method together with the superposition of configuration interactions implemented in Cowan's codes. In this critical evaluation, we provided several possibly observable lines with Ritz-wavelengths, computed from the optimized energy levels, and theoretical transition probabilities with their estimated uncertainties. In addition, we provided the radiative transition parameters for several forbidden lines within the ground configuration $5s^25p^2$ of Cs VI.

This paper discusses about the quantum energy levels of muonic hydrogen considering only Coulomb interaction. The computational analysis in this paper will help the reader get a good understanding of how different a muonic hydrogen is from its electronic counterparts. Energy eigenvalues are calculated by numerical method and the probability density distribution of muon around the nucleus is plotted for different quantum states using special functions. The code is written in python. A comparative study of emission spectra between the muonic hydrogen and hydrogen has also been discussed.

Much evidence suggests a correlation between degeneration and mitochondrial impairment. Typical cases of degeneration can also be observed in physiological phenomena (aging) as well as in neurological neurodegenerative diseases and cancer. All these pathologies have as a common denominator the dyshomeostasis of mitochondrial bioenergy. Even neurodegenerative diseases show a bioenergetics imbalance in their pathogenesis or progression. Huntington's chorea and Parkinson's disease are both neurodegenerative diseases, but while Huntington's disease is a genetic, and progressive disease with early manifestation and severe penetrance, Parkinson's disease is a pathology with a multifactorial aspect. Indeed, there are different types of Parkinson/Parkinsonism. Many forms are early onset diseases linked to gene mutation, others can appear in young adults and senescent only post-injury, and a final group is idiopathic. Huntington's was defined as a hyperkinetic disorder, while Parkinson's is a hypokinetic disorder; but in the middle, there are a lot of similarities as well as neuronal excitability, the loss of striatal function, psychiatric comorbidity, etc. In the review, we would embrace the theories that both diseases start and develop in light of mitochondrial dysfunction. These dysfunctions act on energy metabolism and reduce the vitality of neurons in many different brain areas.

Much evidence suggests a correlation between degeneration and mitochondrial impairment. Typical cases of degeneration can also be observed in physiological phenomena (aging) as well as in neurological neurodegenerative diseases and cancer. All these pathologies have as a common denominator the dyshomeostasis of mitochondrial bioenergy. Even neurodegenerative diseases show a bioenergetics imbalance in their pathogenesis or progression. Huntington's chorea and Parkinson's disease are both neurodegenerative diseases, but while Huntington's disease is a genetic, and progressive disease with early manifestation and severe penetrance, Parkinson's disease is a pathology with a multifactorial aspect. Indeed, there are different types of Parkinson/Parkinsonism. Many forms are early onset diseases linked to gene mutation, others can appear in young adults and senescent only post-injury, and a final group is idiopathic. Huntington's was defined as a hyperkinetic disorder, while Parkinson's is a hypokinetic disorder; but in the middle, there are a lot of similarities as well as neuronal excitability, the loss of striatal function, psychiatric comorbidity, etc. In the review, we would embrace the theories that both diseases start and develop in light of mitochondrial dysfunction. These dysfunctions act on energy metabolism and reduce the vitality of neurons in many different brain areas.

We have used the varying physical constant approach to resolve the flatness problem in cosmology. Friedmann equations are modified to include variability of speed of light, gravitational constant, cosmological constant and the curvature constant. The continuity equation obtained with such modifications includes scale factor dependent cosmological term as well as the curvature term along with the standard energy-momentum term. The result is that as the scale factor tends to zero (i.e. as the big-bang is approached) the universe becomes strongly curved rather than flatter and flatter in the standard cosmology. We have used the supernovae 1a redshift versus distance modulus data to determine the curvature variation parameter of the new model, which yields a better fit to the data than the standard ΛCDM model. The universe is found to be open type with radius of curvature R_c = 1.64 (1+z)^-3.3 c₀/H₀, where z is the redshift, c₀ is the current speed of light and H₀ is the Hubble constant.

Results of rapid economic growth, China, USA, and India have become the largest energy stealer and the greatest emitter of CO₂ in the world and burn over 45% of global fuels in 2016. Meanwhile, the developing strategies of 24 polluted countries to decrease the energy consumption without additional economic output. This paper is exploring the effect of world top polluted countries C0₂ emission and their GDP and the production of electricity by energy indicators. The GLM model is not predict logistic and probit analysis directly; instead, it is mainly used for instinct to response of CO₂ emission, using data for the period 1968-2017. The huge production of electricity will cause of abnormal CO₂; this study offers true indication of exploring consumption of energy issues from the perspective of Granger casual and a positive unidirectional causality is detected between energy consumption to economic growth, while short-run bidirectional casualty exists among energy indicators.

By using the method of high-temperature solid-phase reaction, the new piezoceramic SrBi2Nb2-2xWxSnxO9 was obtained, in which partial substitution of niobium (Nb) atoms with Sn4+ and W6+ atoms in the compound SrBi2Nb2O9 took place in the octahedra of the perovskite layer (B-position). X-ray diffraction studies have shown that these compounds are single-phase SrBi2Nb2-2xWxSnxO9 (x = 0.1, 0.2) and two-phase SrBi2Nb2-2xWxSnxO9 (x = 0.3, 0.4), but they all had the structure of Aurivillius – Smolensky phases (ASPs) with similar parameters of orthorhombic elementary cells, corresponding to the spatial group A21am. The dependences on temperature of the relative permittivity ε/ε0 and the tangent of the loss angle tan d at different frequencies were measured.

This article provides a comprehensive review of the intersection of 5G technology and Beyond, and Smart Grids, focusing on the potential of Vehicle-to-Fog as an industrial alternative for addressing energy efficiency challenges in data processing. This study aims to investigate relevant articles and patents to understand the collaborative potential between 5G and Smart Grids. It explores how to establish new regulatory standards within the architectural framework of 5G to facilitate decentralized data processing and remodel energy consumption patterns. The hypothesis suggests that decentralized 5G architecture and Smart Grids can be most effectively applied through vehicular fogging powered by solar energy. A combined quantitative and qualitative methodology guides the exploration of articles and patents. The study concludes by advocating for new standards that embrace decentralized 5G data processing, emphasizing the potential of Vehicle-to-Fog and the future deployment of 6G technology in Smart Grids. These advancements can significantly enhance energy efficiency in the context of 5G and pave the way for future innovations.

To control the volatility and reduce the electricity costs for indoor farming, the agrivoltaics agrotunnel introduced here uses: 1) high insulation for a building dedicated to vertical growing, 2) high-efficiency LED lighting, 3) heat pumps (HPs), and 4), solar photovoltaics (PV) provide known electric costs for 25 years. In order to size the PV array, this study develops a thermal model for agrotunnel load calculations and validates it using the Hourly Analysis Program and measured data so the effect of plants’ evapotranspiration can be included. HPs are sized, plug loads (i.e., water pump energy needed to provide for the hybrid aeroponics/hydroponics system, DC power running the LEDs hung on grow walls, and dehumidifier assisting in moisture condensation in summer) are measured/modeled. Ultimately, all models are combined to establish an annual load profile for an agrotunnel that is then used to model the necessary PV to power the system throughout the year. The results find that agrivoltaics to power an agrotunnel range from 40 to 50kW and make up an areas from 3.2 to 10.48 m²/m² of an agrotunnel footprint. Net zero agrotunnels are technically viable although future work is needed to deeply explore the economics of localized vertical food growing systems.

Buildings consume 30% of the total energy consumption around the globe and 29% of the energy consumption in Egypt which in 2022 had a total population of 102 million, out of which 43 % live in urban areas . The operation of buildings contributes to around 30% of global CO2 emissions due to their high energy consumption (IEA, 2022a). Among the efforts made towards improving the energy efficiency of buildings are Advanced Energy Design Guides (AEDGs), building rating systems, codes, and standards. Furthermore, numerous research studies that are either literature review studies, experimental studies, or computational studies addressed the topic of energy efficiency in buildings. These are all examined in this literature review with the purpose of identifying the research gap in available research with a focus on Egypt. The identified gap is the development of a prescriptive path for the GPRS energy efficiency category based on whole building energy simulations.

Many models with structures of matter associated with a structure of extra spatial dimensions have been proposed in recent decades. On employing a further generalisation from the local 4-dimensional spacetime form to a general form for proper time, we describe how matter fields resembling the Standard Model of particle physics can be accommodated far more directly than with a higher-dimensional spacetime theory. The successful identification of key features of visible matter in this non-spatial sector of extra dimensions in turn motivates seeking a candidate for dark matter residing in the original extra spatial dimension sector, and provides a close guide for the explicit form this invisible matter might take. We describe how such Standard Model and dark matter sectors in different extra-dimensional branches of generalised proper time are gravitationally connected through their common root in the local 4-dimensional spacetime and consider further possible mutual interactions and implications in comparison with existing dark matter models. A yet further possible branch of generalised proper time can be connected with dark energy models, hence in principle accounting for all three major components of cosmological structure within this framework.

Diverse factors may have an impact in Carbon dioxide (CO₂) emissions; thus, three main contributors, energy consumption, exergy indicator and gross domestic product (GDP) are examined in this work. This study explores the relationship between economic growth and energy consumption by means of the hypothesis postulated for the Environmental Kuznets Curve (EKC). Panel data for 10 countries, from 1971 to 2014 have been studied. Despite all this wide gamma of research, the role of an exergy variable has not been tested to find the EKC; then exergy analysis is proposed. Exergy analyses were developed to propose an exergetic indicator as a control variable and a comparative empirical study is developed to study a multivariable framework with the aim to detect correlations between them. High correlation between CO₂, GDP, energy consumption, energy intensity and trade openness are observed, conversely not statistically significant values for trade openness and energy intensity. The results do not support the EKC hypothesis, however exergy intensity opens the door for future research once it proves to be a useful control variable. Exergy provides opportunities to analyze and implement energy and environmental policies in these countries, with the possibility to link exergy efficiencies and the use of renewables.

Plastic waste constitutes one of the most important sources of pollution worldwide. Despite the growing recycling trend, nowadays there are no effective technologies that can compensate for the continuous increase in plastic production. Polyesters and polyamides are one of the most produced single-use plastics, mainly used in manufacturing textiles and soft drinks bottles. Today, only a very low fraction of these polymers can be recycled. It can be done by exploiting two leading technologies: mechanical and chemical recycling. Mechanical recycling represents, nowadays, the most used industrial application. However, it can treat a very narrow range of waste materials due to the impossibility of removing dyes and the deterioration of mechanical properties due to the incompatibility of different plastic materials. Another critical limit of this recycling technology is the limited number of recycling loops that can be done due to the thermal degradation that occurs during the extrusion process. The second possibility is chemical recycling, which allows the depolymerization of the original product to recover the monomers directly. The main drawbacks are the long reaction times and the many solvents needed to achieve high-purity products. Therefore, chemical recycling is economically feasible, only for big companies that can produce the virgin polymer in situ. In this work, a new technology has been patented. This process is constituted of three main steps. The first one is the distillation-assisted cyclodepolymerization (DA-CDP), introduced as a modification of the CDP process. In this unit, cyclic oligomers together with high molecular weight compounds have been produced. Then, after polymer purification, it is possible to achieve the same molecular weight of the initial polymer in less than 30 minutes, exploiting the ring-opening polymerization (ROP) in the next step.

Establishing an accurate mathematical model is the foundation of simulating the motion of marine vehicles and structures, and it is the basis of modeling-based control design. System identification from observed input-output data is a practical and powerful method. However, for modeling objects with different characteristics and known information, a single modeling framework can hardly meet the requirements of model establishment. Moreover, there are some challenges in system identification, such as parameter drift and overfitting. In this work, three robust methods are proposed for generating ocean hydrodynamic models based on Bayesian regression. Two Bayesian techniques, semi-conjugate linear regression and noisy input Gaussian process regression, are used for parametric and nonparametric gray-box modeling and black-box modeling. The experimental free-running tests of the KVLCC2 ship model and a multi-freedom wave energy converter (WEC) are used to validate the proposed Bayesian models. The results demonstrate that the proposed schemes for system identification of the ship and WEC have good generalization ability and robustness. Finally, the developed modeling methods are evaluated considering the aspects required conditions, operating characteristics and prediction accuracy.

The world is progressing towards a more advanced society where end-consumers have access to local renewable-based generation and advanced forms of information and technology. Hence, it is in a current state of transition between the traditional approach to power generation and distribution, where end-consumers of electricity have typically been inactive in their involvement with energy markets and a new approach that integrates their active participation. This new approach includes the use of distributed energy resources (DER) such as renewable-based generations and demand response (DR), which are being rapidly adopted by end-consumers, where incentives are strong. This paper presents the role of DR aggregator to effectively integrate DER technologies as a new source of energy capacity, into the electricity networks using information communication technology and industry knowledge. This framework based on DR aggregators will facilitate renewable energy integration and customer engagement in electricity market efficiently. To this aim, advantages and disadvantages of DR aggregators are discussed in this paper from political, economic, social and technological (PEST) point of views. Based on this analysis, a strengths, weaknesses, opportunities, and threats (SWOT) analysis for a typical DR aggregator is presented.

One of the biggest challenges in characterizing 2-D image topographies is finding a low-dimensional parameter set that can succinctly describe, not so much image patterns themselves, but the nature of these patterns. The 2-D Cluster Variation Method (CVM), introduced by Kikuchi in 1951, can characterize very local image pattern distributions using configuration variables, identifying nearest-neighbor, next-nearest-neighbor, and triplet configurations. Using the 2-D CVM, we can characterize 2-D topographies using just two parameters; the activation enthalpy and the interaction enthalpy. Initial investigations with two different representative topographies (``scale-free-like'' and ``rich club-like'') produce interesting results when brought to a CVM free energy minimum. Additional phase space investigations, where one of these two parameters has been set to zero, identify useful parameter ranges. Careful comparison of the analytically-predicted configuration variables versus those obtained when performing computational free energy minimization on a 2-D grid show that the computational results differ significantly from the analytic solution. The 2-D CVM can potentially function as a secondary free energy minimization within the hidden layer of a neural network, providing a basis for extending node activations over time and allowing temporal correlation of patterns.

Here, using the theory of electrical modelling of the neutron and proton as a three-phase alternating current electrical generator, we will begin the path to demonstrate that the interactions of electromagnetic forces, weak force and strong force that are part of the standard model, can be described by a single electromagnetic force interaction, in other words: SU(3) x SU(2) --> U(1). We will also hypothesize two particles that would give rise to gravitons. It is the interactions of the quarks (U, Û, D, ^D) that dominate the dynamics; They are responsible for the origin of bosons (photons, gluons, W⁺, W⁻, Z⁰, gravitons and Higgs boson).

We present large eddy simulations of a mid-latitude open ocean front using a modified state of the art computational fluid dynamics code. We investigate the energy and information fluxes at the submesoscale/small-scale range in the absence of any atmospheric forcing. We find submesoscale conditions (Ro∼1, Ri∼1) near surface, within baroclinic structures related with partially imbalanced frontogenetic activity. Near surface, the simulations show a significant scale coupling on scales larger than ∼103(m). This is manifested as a strong direct energy cascade and intense mutual communication between scales, where the latter was evaluated using an estimator based on Mutual Information Theory. At scales smaller than ∼103(m) the results show near-zero energy flux, however, at this scale range, the estimator of mutual communication still shows values corresponding with a significant level of communication between them. This fact motivates to investigate the nature of the self-organized turbulent motion at this scale range with weak energetic coupling but where communication between scales is still significant and to inquire into the existence of synchronization or functional relationships between scales with emphasis on eventual underlying non-local processes.

The principles of causality and unitarity are studied within rational nonlinear electrodynamics proposed earlier. We investigate dyonic and magnetized black holes and show that in the self-dual case, when the electric charge equals the magnetic charge, corrections to Coulomb's law and Reissner-Nordstrom solutions are absent. In the case of the magnetic black hole, the Hawking temperature, the heat capacity and the Helmholtz free energy are calculated. It is shown that there are second-order phase transitions and it was demonstrated that at some range of parameters the black holes are stable.

Abstract: A fertilisation experiment with aim to determine the effect of different potassium fertiliser rates and their interaction with nitrogen and phosphorus on field rotation productivity, potassium balance, fertiliser utilization and changes in content of potassium in soil was carried out in Lithuania between 1971 and 2020. The multi-factorial scheme with 45-treatment plots, where seven (including zero) rates of nitrogen, phosphorus and potassium fertilisers were studied. The experimental treatments during the study period included winter wheat, spring wheat, spring barley, sugar beet, spring rapeseed, annual and perennial grasses. It was found that potassium fertilisers was the most effective on agricultural crops when used in combination with other major plant nutrients – nitrogen and phosphorus. The balance of potassium (K2O) in soil, when nitrogen and phosphorus fertilisers were applied together, to compensate for potassium removal, when applying low nitrogen (N) 72 kg ha-1 and phosphorus (P2O5) 64 kg ha-1 fertiliser rates, 128 kg ha-1 of potassium fertilisers is required. When using high nitrogen 180 kg ha-1 and phosphorus 160 kg ha-1 fertiliser rates, 160 kg ha-1 of potassium is needed. The highest potassium uptake, reaching 51.6%, was achieved when plants had been fertilised with nitrogen 108 kg ha-1, phosphorus 96 kg ha-1, and potassium 96 kg ha-1. When fertilising with potassium fertilisers alone, the content of plant available K2O content in the soil increased, while fertilisation with nitrogen and phosphorus combined it’s decreased, except in the plots where the plants had been fertilised with potassium fertiliser at rates of 128 kg ha-1 and higher. Due to the influence of fertilizers, the amount of non-exchangeable potassium in the soil also increased, but relatively less compared to the amount of available potassium content.

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.

This research project focuses on the optimization of the hybrid energy system together with the assistance of thin-film coatings aiming to achieve self-sustainable food and crop storage facilities which will run effectively with its own generated energy. An infrastructure will be designed and constructed that will comprise a hybrid power generation system accompanied by thin-film coated semitransparent and non-transparent construction materials for energy saving. Thin-film low emissivity (Low-E) type coatings will assist the transparent or semitransparent construction materials to reflect most of the infrared (IR-mostly heat) and UV spectra of sunlight without interrupting the visible spectrum and will lead to saving energy consumption by reducing the heat and lighting during day time

This paper proposed a damping method for enhancing oscillatory stability performance of power systems with high penetration of renewable energy by a resilient wide-area multi-mode controller. The resilient wide-area multi-mode controller is used as an additional controller in a renewable energy system with a battery energy storage to enhance the damping of the critically weak modes. The weak modes are likely to be triggered in the event of line outages or any other disturbances, and the system may become unstable in the absence of proper corrective and preventive control. A firefly algorithm has been employed to design such a controller. Eigenvalue analysis and time-domain simulation are used to analyze the performance of the proposed controller in a realistic representative power system. From the simulation results, it is evident that the oscillatory stability performance of the renewable rich power system can be enhanced with the proposed control to keep the damping on critical modes to the industrial standards. Furthermore, renewable energy penetration can be increased significantly in the realistic representative system by introducing the proposed controller without disturbing the oscillatory stability margin.

In-cloud ice mass accretion on wind turbines is a common challenge faced by energy companies operating in cold climates. On-shore wind farms in Scandinavia are often located in regions near patches of forest, the heterogeneity length scales of which are often less than the resolution of many numerical weather prediction (NWP) models. The representation of these forests--including the cloud water response to surface roughness and albedo effects related to them--must therefore be parameterized in NWP models used as meteorological input in ice prediction systems, resulting in an uncertainty that is poorly understood and to present date not quantified. The sensitivity of ice accretion forecasts to the subgrid representation of forests is examined in this study. A single column version of the HARMONIE-AROME 3D NWP model is used to determine the sensitivity of the forecast of ice accretion on wind turbines to the subgrid forest fraction. Single column simulations of a variety of icing cases at a location in northern Sweden were examined in order to investigate the impact of vegetation cover on ice accretion in varying levels of solar insulation and wind magnitudes. In mid-winter cases, the wind speed response to surface roughness was the primary driver of the vegetation effect on ice accretion. In early season cases, the cloud water response to surface albedo effects plays a secondary role in the impact of in-cloud ice accretion, with the wind response to surface roughness remaining the primary driver for the surface vegetation impact on icing. Two different surface boundary layer (SBL) forest canopy subgrid parameterizations were tested in this study that feature different methods for calculating near-surface profiles of wind, temperature, and moisture, with the ice mass accretion again following the wind response to surface vegetation between both of these schemes.

The purpose of this paper is to test the Kuznets Environmental Curve (KEC) hypothesis for 10 MENA (Middle East and North Africa) countries during the period 1987-2017. To do this, the translogical functional form has been adopted to estimate the relationship between Toxic Gases (TG) emissions, energy consumption and GDP per capita. The results confirm the presence of KEC, GDP per capita and energy consumption have a positive influence on TG emissions, and the presence of a feedback relationship between GDP per capita and energy consumption. As a result, the environmental framework of the selected countries improves as their level of growth has become more advanced. In addition, to reduce TG emissions, MENA countries are expected to significantly increase the use of renewable energy and a more efficient energy policy.

In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of vehicle semi-active energy regenerative suspension with electro-hydraulic actuator (EHA). In light of the proposed concept, a specific energy regenerative scheme is designed and the mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using recursive least squares algorithm. On the basis of system principle, the nonlinear model of the semi-active energy regenerative suspension with EHA is built. Meanwhile, LQG control strategy of the system is designed. And then the influence of the main parameters of EHA on the damping performance and energy regenerative performance of suspension is analyzed. Finally, the main parameters of EHA actuator are optimized via genetic algorithm. The test results show that when sinusoidal is input at the frequency of 2Hz and the amplitude of 30mm, the spring mass acceleration RMS value of optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and energy regenerative power RMS value is increased by 40.51%, which means while meeting the requirements of certain vehicle ride comfort and driving safety, energy regenerative performance is improved significantly.

We present a thermodynamic approach in modeling the evolution of the universe based on a theory that space consists of energy quanta, the spaceons. From wave-particle duality, they can be treated as an ideal gas. The model is similar to the Big Bang but without Inflation. It provides an insight into the nature of dark energy and dark matter, and an explanation for the accelerated expansion of the universe. The universe started from an atomic size volume of spaceons at very high temperature and pressure. Upon expansion and cooling, phase transitions occurred resulting in the formation of fundamental particles, and matter. These nucleate and grow into stars, galaxies, and clusters due to the action of gravity. From the cooling curve of the universe we constructed a thermodynamic phase diagram of cosmic composition, from which we obtained the correlation between dark energy and the energy of space. Using Friedmann’s equations, our model fits well the WMAP data on cosmic composition with an equation of state parameter, w= -0.7. The dominance of dark energy started at 7.25 x 10⁹ years, in good agreement with BOSS measurements. The expansion of space is attributed to a scalar quantum space field. Dark Matter is identified as a plasma form of matter similar to that which existed during the photon epoch, prior to recombination. The thermodynamics of expansion of the universe was adiabatic and decelerating during the first 7 billion years after the Big Bang; it accelerated thereafter. A negative pressure for Dark Energy is required to sustain the latter. This is consistent with the theory of General Relativity and the law of conservation of energy. We propose a mechanism for the acceleration as due to consolidation of matter forming Dark Energy Stars (DES) and other compact objects. The resulting reduction in gravitational potential energy feeds back energy for the expansion. Space will continue to expand and dark energy will undergo phase transition to a Bose-Einstein condensate, a superfluid form of matter. Self-gravitation can cause a bounce and start a new Big Bang. We show how the interplay of gravitational and space forces leads to a cyclic, maybe eternal, universe.

Building a new-type power system is the key core of the green and low-carbon development of energy, the restructuring of the power system will inevitably have a linked impact on the coordinated development of the economy-energy-environment (3E) system. This paper constructs a "Dual-Triangle" theoretical framework consisting of the “Energy Trilemma” and the "Sustainable Development Triangle", by combining historical statistical analysis with scenario predictive analysis, analyzes the historical characteristics of the "Dual Triangle" and future development trends under different scenarios, and studies the coupled interaction relationship of the "Dual-Triangle" to explore the optimal transformation path of the power system that is most beneficial to the coordinated development of the 3E system. The conclusions are as follows: (1) The energy system gradually inclined towards economy and cleanliness from 2010 to 2022, the level of coordinated development of the 3E system fluctuated upwards, and the operation status of the "Dual Triangle" was stable. (2) Positive coupling relationship between "Dual Triangle" of scenario S1 is close, which can be regarded as the preferred path for the reconstruction of the power system. Due to phased development has clear development priorities, scenario S2 will artificially break the balance of the “Energy Trilemma”, which is a development model that dynamically mitigates the challenges of the “Energy Trilemma”.(3)The contradiction between economy and cleanliness is continuously weakened, and security has become the core contradiction of the "Impossible Triangle". The combination of renewable energy and energy storage is the key to resolving this contradiction. This paper conducts an integrated and innovative application of the "Dual-Triangle" theory, and the results provide a case basis for how to achieve the coupled interaction of the "Dual-Triangle", promote high-quality energy development, and support the sustainable development of the economy and society.

Previous studies on the water-energy nexus mainly focused on the calculation and comparison of resource consumption at the national or regional level, lacking interprovincial sector-sector transfer analysis. In this study, the intensity of water and energy consumption of various sectors in China were calculated, the key nodes and paths of resource networks were identified, and countermeasures for resource conservation were proposed from the new perspective of the “dual saving” and “bidirectional saving” of water and energy. The results showed that the metallurgical industry (Me) in Jiangsu and the chemical industry (Ch) in Hebei and Jiangsu had high node strength in the water and energy network and were key sectors in China with “dual saving” effects of water and energy. The construction industry, Ch, Me in Jiangsu, electricity and hot water production and supply industry in Beijing, and Me in Hebei had high node strength in the water-related energy network and energy-related water network, significantly supporting the “bidirectional saving” effect of water and energy in China. The electrical equipment industry (El) in Jiangsu→El in Zhejiang, El in Zhejiang→El in Shanghai frequently appeared in key paths, which could effectively reduce the resource consumption of the entire network.

This work demonstrates that microbial fuel cells (MFCs), optimized for energy recovery, can be used as an effective tool to detect the presence of antibiotics in water-based environments. MFCs directly convert chemical energy of organic matter in electrical energy thanks to electroactive biofilms. The efficiency of the conversion process can be significantly affected by the presence of contaminants acting as toxicants for the biofilm. In the present work, we demonstrate that MFCs can successfully detect the presence of antibiotic residues in water and water-based electrolytes associated to the food industry, especially using honey as a new and more complex electron donor. The effectiveness of MFCs to sense antibiotics is here demonstrated for tetracycline that was added to both water and water/honey electrolytes with a minimum concentration close to 3.5 μg⁄kg. MFCs not only efficiently detect the presence of tetracycline in both the electrolytes, but also recover the same performance after each cycle of exposure, showing to a be very robust and reliable technology for both biosensing and energy recovery.

The perceived poor performance of publicly traded companies on their sustainability commitments and the quality of sustainability reporting has prompted stakeholders to consider the economic, environmental, and social impacts of corporate activities. Economic activities have led to various threats in the form of climate change, pollution, greenhouse gas emissions, natural disasters, and other issues that have negatively impacted the environment and stakeholders. Companies are expected to report to stakeholders on their sustainability performance, but reality proves that present reporting falls below stakeholders’ expectations mainly due to its still voluntary nature. The present study aims to provide a literature review of the relationship between sustainability reporting and the role of companies governance, especially observing if climate change requirements and energy-needed changes are being accounted. Results highlight mixed evidence for the influence of board governance attributes, providing interesting insights for research advancement. The study has practical implications for businesses, regulators, governments, and other stakeholders in their policy deliberations and investment decisions. Further empirical studies are recommended to re-examine sustainability reporting using the variables identified as important factors and gaps in this study and other board characteristics to improve the generalizability of the results.

Abstract: The COVID-19 pandemic has disrupted global energy markets and caused significant socio-economic impacts worldwide. The pandemic has also impacted the energy sector, with demand for energy reducing due to lockdowns and reduced economic activity. Hence, this paper aims to provide a comprehensive and analytical review of the impact of COVID-19 on the energy sector and discuss the potential role of artificial intelligence (AI) in mitigating some of these effects. This review examines the changes in energy demand patterns resulting from the pandemic and the implications for the energy industry, including the shifts in policymaking, communication, digital technology, energy conversion, environmental, energy market, and power system operation. The analysis of the energy pattern is discussed according to the timeframes which include pre-, mid-, and post-pandemic periods. Furthermore, we explore how AI can be used to improve energy efficiency, optimize energy use, and reduce energy wastages. The potential for AI to contribute to developing more efficient and sustainable energy systems has also been addressed. Lastly, we highlighted AI’s challenges, which play a significant role in the energy sector's response to the COVID-19 pandemic. The recommendations for AI applications in the energy sector for the transition to a more sustainable energy future are outlined. Information corroborated in this review is expected to provide important guidelines for crafting future research areas and directions in preparing the energy sector for any unforeseen circumstances or pandemic-like situations.

This paper presents the results of numerical simulations examining the thermodynamic processes during hydraulic hydrogen compression, using COMSOL Multiphysics® 6.0. These simulations focus on the application of hydrogen compression systems, particularly in hydrogen refueling stations. The computational models employ the CFD and Heat Transfer modules, along with deforming mesh technology, to simulate gas compression and heat transfer dynamics. The superposition method was applied to simplify the analysis of hydrogen and liquid piston interactions within a stainless-steel chamber, accounting for heat exchange between the hydrogen, the working fluid, and the cylinder walls. The study investigates the effects of varying compression stroke durations and initial hydrogen pressures, providing detailed insights into temperature distributions and energy consumption under different conditions. The results reveal that the upper region of the chamber experiences significant heating, highlighting the need for efficient cooling systems. Additionally, the simulations show that longer compression strokes reduce the power requirement for the liquid pump, offering potential for optimizing system design and reducing equipment costs. This study offers crucial data for enhancing the efficiency of hydraulic hydrogen compression systems, paving the way for improved energy consumption and thermal management in high-pressure applications.

Cities consume over 75% of natural resources, produce over 50% of global waste and emit 60 - 80% of greenhouse gases. The scenario that by 2050 two thirds of the world population will live in cities, highlights how cities are still responsible of the growing consumption characterized by linear economy processes, with the production of various types of waste. In this unsustainable framework, the Circular Economy offers the opportunity to shape the urban system by means of rethinking the possibility to produce and use goods and services exploring new ways to ensure long-term prosperity. The Circular City paradigm contains in fact all the principles of the Circular Economy: recovery, recycling and sharing. In particular, Circular City also introduces actions related to the development of renewable energy communities, use of green materials, CO2 absorption approaches and Proximity Cities. The aim of this work is to develop a methodology to build a composite index (Circular City Index) capable of measuring the degree of implementation of urban policies that enable the territory to initiate an ecological transition of public assets. The city of Cagliari (Sardinia, Italy) represents the case study to apply circular urban policies in public properties, for civil and military use.

The uptake of buildings employing cross-laminated timber (CLT) assemblies and designed to Passivhaus standard has accelerated internationally over the past two decades due to several factors including design responses to the climate crisis by decarbonising the building stock. Structural CLT technology and the voluntary Passivhaus certification both show measurable benefits in reducing energy consumption, while contributing to durability and indoor comfort. However, there is a general lack of evidence to support a fast uptake of these technologies in Australia. This paper responds to the compelling need of providing quantitative data and adoption strategies, it explores their combined application as a potential pathway for climate-appropriate design of energy-efficient and durable mass timber envelope solutions for subtropical and tropical Australian climates. Hygrothermal risk assessments of interstitial condensation and mould growth of CLT wall assemblies inform best-practice design of mass timber buildings in hot and humid climates. This research found that the durability of mass timber buildings located in hot and humid climates may benefit from implementing the Passivhaus standard to manage interior conditions. The findings also suggested that climate-specific design of the wall assembly is critical for mass timber buildings, in conjunction with excellent stormwater management practices during construction and corrosion protection for metallic fasteners.

The wide interest in developing green energy technologies stimulates the scientific community to seek, for devices, new substitute material platforms with low environmental impact, ease of production and processing and long-term stability. The synthesis of metal oxide (MO) semiconductors fulfils these requirements and efforts are addressed at optimizing their functional properties, through improvement of charge mobility or energy level alignment. Two MOs have rising perspectives for application in light harvesting devices, mainly for the role of charge selective layers but also as light absorbers, namely MoO3 (an electron blocking layer) and Co3O4 (a small band gap semiconductor). The need to achieve better charge transport has prompted us to attempt doping strategies with vanadium (V) ions that, when combined with oxygen in V2O5, produce a high work function MO. We report on subcritical hydrothermal synthesis of V-doped mesostructures of MoO3 and of Co3O4, in which a tight control of the doping is exerted by tuning the relative amounts of reactants. We accomplished a full analytical characterization of these V-doped MOs that unambiguously demonstrates incorporation of the vanadium ions in the MO crystal lattice, as well as effects on the optical properties and work function. We foresee a promising future use of these materials as charge selective materials in energy devices based on multilayer structures.

Polymer materials are increasingly being used for sliding machine elements due to their numerous advantages. They are used even where they are deformed and in such a state they interact frictionally e.g. in machine hydraulics or lip seals. Few publications deal with the influence of deformation, which is the effect of e.g. assembly on tribological properties of polymeric material. This deformation can reach up to ε ≈ 20% and is achieved without increasing the temperature of the polymer material. The paper presents the results of investigations in which high-density polyethylene (PE-HD) was maintained in deformation by means of a special grip (holder). The wear of the sample was significantly higher than that of the undeformed sample. This effect persisted even after partial relaxation of the stress in the sample after 24 hours. Additional investigations were carried out to explain the obtained results. There were the microscopic observations of the surface after friction, measurements of microhardness and free surface energy. Changes in the value of surface free energy and a significant decrease in microhardness with deformation under tension were observed. Strained material had a different surface appearance after friction and a different size and form of wear products. It was indicated that it is probable that the cohesion of the material will decrease and that the character of the wear process will change as a result of tension. Tension without heating of polymeric material (PE-HD), e.g. as a result of assembly, has been qualified as a hazard to be taken into account when designing and analysing polymeric sliding elements.

Species data of 249 National Nature Reserves in China was used to identify potential underlying drivers of latitudinal gradients in plant diversity. We used generalized linear models (GLMs) to assess the correlations between predictor and response variables. We also used SAM (Spatial Analysis in Macroecology) to eliminate autocorrelation along each of the 249 studied locations. We used the Akaike information criterion (AICc; Montoya et al. 2007) to select the independent variables were those included in the best models from different combinations of climate, habitat and animal variables. Variance partitioning was used to decompose the variation in plant richness across different taxonomic levels among the three groups of predictors. We found that: Total plant species, gymnosperms, angiosperms and ferns showed significant latitudinal trends in richness (p < 0.001). Water-energy and habitat variables generally explained more variation in richness across different plant groups than did animal richness. Annual precipitation was selected as the best water-energy variable across different taxonomic plants groups, soil PH and elevation range were selected as the best habitat variables across different taxonomic plant groups. The independent effects of habitatvariables were higher than that of water-energy and animal variables across different taxonomic plants groups. Water-energy, habitat heterogeneity, and animal variables explain 48.8% of the variation in total species richness, 28.2% in gymnosperm richness, 44.2% in angiosperm richness, and 38.9% in fern richness.Plants showed significant latitudinal trends in richness (p < 0.001). Water-energy and habitat variables generally explained more variation in richness across different taxonomic plants groups than did animal variables. The independent effects of habitat variables were higher than those of water-energy and animal variables across different taxonomic plants groups.

Geothermal energy generation faces challenges in efficiency, partly due to restrictions on reinjection temperatures caused by scaling issues. Therefore, developing strategies to prevent scaling is critical. This study aims to simulate the scaling tendencies and corrosion effects of geothermal fluids on various construction materials used in scaling reactor/retention tank systems. A range of materials, including carbon steel, austenitic stainless steel, duplex stainless steel, two proprietary two-part epoxy coatings, and thermally sprayed aluminium (TSA), were tested in a simulated geothermal brine. Experiments were conducted in a laboratory vessel designed to replicate the wall shear stress conditions expected in a scaling reactor. The tests revealed varying scaling tendencies among the materials, with minimal corrosion observed. The dominant scale formed was calcium carbonate, consistent with geochemical modelling. The findings suggest that despite the high operating temperatures, the risk of corrosion remains low due to the brine's low chloride content, while the wettability of materials after immersion may serve as a useful indicator for selecting those that promote scaling.

One of the solutions of the Einstein equations, called McVittie solution, signifying a black hole embedded by the dynamic spacetime is studied. In the stationary spacetime the Mcvittie metric becomes the Schwarzschild-de Sitter metric (SdS). The geodesic of a freely falling test particle towards the black hole is examined in the SdS spacetime. It is found that unlike Schwarzschild case the potential of such particle becomes maximum at a point where it eventually stops to follow an unstable circular motion and then resumes its motion towards black hole center. It is shown that an observer or system of particles is spaghettified near the black hole singularity in the SdS spacetime. The dynamic of the universe in the framework of McVittie metric, being a generalized time dependent SdS solution, is represented in terms of that point, called stationary or turning point. The motion of the stationary point is studied in various regimes of the expanding universe and the possible outcomes are discussed in brief.

We present a new method for assessing the strength of fuzzy rules with respect to a dataset, based on the measures of the greatest energy and smallest entropy of a fuzzy relation. Considering a fuzzy automaton (relation) in which A is the input fuzzy set and B the output fuzzy set, the fuzzy relation R1 with greatest energy provides information about the greatest strength of the input-output and the fuzzy relation R2 with the smallest entropy provides information about uncertainty of the relationship input-output. We consider a new index of the fuzziness of the input-output based over R1 and R2. In our method this index is calculated for each pair of input and output fuzzy sets in a fuzzy rule. A threshold value is set for choosing the most relevant fuzzy rules with respect to the data.

To promote low-carbon and green travel, this study proposes a tripartite evolutionary game model among new energy vehicle manufacturers, consumers, and government agencies. The game strategy combinations of each party and the stability conditions of the equilibrium point in the evolutionary game system are analyzed, and the validity of the conclusions is verified through simulation results. The study shows a strong correlation between the three parties in the evolutionary game system. From the perspective of car manufacturers, the probability of producing new energy vehicles is positively proportional to the subsidy received from new energy policy, the additional revenue gained from the management of the carbon trading scheme, and the fine received for producing conventional fuel vehicles. However, from the consumer perspective, the likelihood that consumers purchase new energy vehicles is positively related to the utility value to consumers and the coverage of public charging points in the city, and inversely related to the sales price of new energy vehicles. From the government perspective, a combination of direct subsidy policies and indirect support strategies should be considered to stimulate the rapid development of the new energy vehicle industry.

Sustainability is pivotal in the urban transformation strategy in order to reach more resource-efficient, resilient and smarter cities. The goal of being a sustainable city should drive the decisions for city interventions. Nonetheless, impacts need to be quantified, lacking of standard and/or common methodologies that could be replicable across multiple cities. There exist many initiatives aiming at defining indicators and assessment procedures, but without convergence in the definition of terms and application methodologies, making complex its real implementation. Within mySMARTLife project (GA#731297), a KPI-driven evaluation framework is defined with the aim of covering the multiple pillars of a city (i.e. energy, mobility, citizens, economy) in a holistic way. This methodology also defines the concepts and terms to guide urban planners and/or experts at time of implementing the framework in a specific city. The evaluation framework has been deployed in the three cities of Nantes, Hamburg and Helsinki and some lessons learnt have been extracted, such as the necessity of providing a definition of measurement boundary to avoid interpretations. Thanks to a co-creation strategy, the main difficulties and issues from the cities have been taken into consideration for increasing the replicability.

Human and animal waste, including waste products originating from human or animal digestive systems such as urine, feces, and animal manure, have constituted a nuisance to the environment. Inappropriate disposal and poor sanitation of human and animal waste often cause negative impacts on human health through contamination of the terrestrial environment, soil, and water bodies. Therefore, it is necessary to convert these wastes into useful resources to mitigate their adverse environmental effect. The present study provides an overview and research progress of different thermochemical and biological conversion pathways for the transformation of human- and animal-derived waste into valuable resources. The physicochemical properties of human and animal waste are meticulously discussed as well as nutrient recovery strategies. In addition, a bibliometric analysis is provided to identify the trends in research and knowledge gaps. The results reveal that the U.S.A, China and England are the dominant countries in the research areas related to resource recovery from human or animal waste. In addition, researchers from the University of Illinois, the University of California Davis, the Chinese Academy of Science and Zhejiang University are front runners in research related to these areas. Future research should be centred on developing technologies for the on-site recovery of resources, exploring integrated resource recovery pathways, and exploring different safe waste processing methods.

The sustainable management of Land - Water - Energy - Food (LWEF) nexus requires an envi-ronmental characterization that allows the comparison of complex interlinkages between nexus resources and livelihoods. This complexity makes this characterization difficult coupled with limited study in quantifying sustainability of LWEF nexus and its linkage with livelihood. Therefore, the present study aimed to investigate the link between sustainable LWEF nexus and livelihoods. We used analytical hierarchy process and pairwise comparison matrix in combina-tion with weighting model. The result of composite LWEF nexus index was 0.083 representing, low sustainability. This could be linked with nexus resources consumption, use, and manage-ment. From the analysis of the weight of land, water, energy and food nexus resources, the highest weight was observed for food. The focus of on food production only shows no clear synergy on provisioning, supporting or regulating nexus resources to address livelihoods. The result further showed that LWEF nexus resources have strong correlation with livelihoods. This was evidenced by social (r>0.8, P<0.01), natural (r>0.3, P<0.05) and physical (r>0.6, P<0.01) liveli-hood indicators showed strong positive correlation with LWEF nexus resources. From this re-sults, it was observed that managing nexus resources not only provide a significant contribution to achieve sustainable LWEF nexus, but also be effective for enhancing livelihood through food security. This could be attained by strong evidence based policy to ensure sustainable use of nexus resources. The results provided by this study would serve as the foundation for future study, policy formulation and implementation.

Using the phenomenon of transpiration, plants are able to raise soil water to a height of about 100 meters. According to the Cohesion - Tension theory, water moves through the capillaries of plant along a gradient of negative water potential in a single unified flow along a single route from roots to leaves, entering on its way into living cells for their nutrition and evaporating into the atmosphere in significant amounts in the leaves. The paper shows that in a case of artificial transpiration devices (ATD), the flow of rising water can be divided into two streams - the transpiration stream and the passive water stream - and as a result, such devices become capable of raising water to any given height. As proof, the working variant of two-stream ATD is proposed. The development of this ATD was carried out in two stages, discussed in details in the paper. At the first, experimental stage, a physical model was designed and manufactured, in which the flow of rising water was divided into two streams moving along two independent routes. The first route is used exclusively for the purpose of transpiration of water - transporting it into an artificial evaporator for complete evaporation into the atmosphere. The second route is used exclusively to transport passive water using the energy obtained in the first route during the process of transpiration. During many hours of testing, the physical model demonstrated a stable ability to bring masses of passive water, maintaining normal atmospheric pressure in them, to a small height, even in the extreme case not exceeding 10 meters. At the second, analytical stage, this two-stream model was developed into a two-stream multi-stage model, capable of raising water to any given height by choosing the number of stages. The number of stages can be very large, and portions of water can be delivered to any given height, remaining under normal atmospheric pressure. The conclusion part of the paper discusses the prospects of creating on the basis of the developed two-stream ATDs large systems that can, using the phenomenon of transpiration, become a sources of clean energy, similar to how it is realized in the mass of plants.

Considering the dynamic stall effects in engineering calculations is essential for correcting the aerodynamic loads acting on wind turbines, both during power production and stand-still cases, and impacts significantly the turbine aeroelastic stability. The employed dynamic stall model needs to be accurate and robust for a wide range of airfoils and range of angle of attack. The present studies are intended to demonstrate the performance of a recently implemented "IAG dynamic stall" model in a wind turbine design tool Bladed. The model is transformed from the indicial type of formulation into a state-space representation. The new model is validated against measurement data and other dynamic stall models in Bladed for various flow conditions and airfoils. It is demonstrated that the new model is able to reproduce the measured dynamic polar accurately without airfoil specific parameter calibration and has a superior performance compared to other models in Bladed.

The structural, elastic, anisotropic elastic, electronic, vibrational and properties of the Perovskite type Hydrides RbXH3 (X = Be, Ca, Mg) were performed via Vienna Ab – initio Simulation Pac-kage (VASP) based on Density Functional Theory (DFT). Our results have exhibited a well-agreement with previous calculations and experiments for each compound. In order to de-termine physical properties of RbXH3 has been used the Generalized Gradient Approximation (GGA) with Perdew-Burke-Ernzerhof (PBE) functional at this study. Present compounds were found to be mechanically stable as well as their gravimetric hydrogen storage capacities has been investigated. The Perovskite type Hydrides RbBeH3 and RbMgH3 has an indirect bandgap of 0.274 eV and 2.209 eV while RbCaH3 has a direct bandgap of 3.274 eV respectively and therefo-re these compounds has shown a semiconductor behaviour at equilibrium. Besides directional dependence of anisotropic properties was visualized by representing them with maximum - mi-nimum points..

Sport nutrition knowledge has been shown to influence dietary habits of athletes. The purpose of the current study was to examine relationships between sport nutrition knowledge and body composition and examine potential predictors of body weight goal in collegiate athletes. Participants included National Collegiate Athletic Association Division III women (n=42, height: 169.9 ± 6.9 cm; body mass: 67.1 ± 8.6 kg; fat-free mass: 51.3 ± 6.6 kg; body fat %: 24.2 ± 5.3%) and men (n=25, height: 180.8 ± 7.2 cm; body mass: 89.2 ± 20.5 kg; fat-free mass: 75.9 ± 12.2 kg; body fat %: 13.5 ± 8.9%) athletes. Body composition was assessed via air displacement plethysmography. Athletes completed a validated questionnaire designed to assess sport nutrition knowledge and were asked questions about their perceived dietary energy and macronutrient requirements, as well as their body weight goal (i.e. lose, maintain, gain weight). Athletes answered 47.98 ± 11.29 % of questions correctly on the nutrition questionnaire with no differences observed between sexes (men: 49.52 ± 11.76% vs. women: 47.03 ± 11.04%; p=0.40). An inverse relationship between sport nutrition knowledge scores and body fat percentage (r = -0.330; p=0.008), and fat mass (r = -.268; p=0.032) was observed for all athletes. Fat mass (β = 0.224), BF % (β = 0.217), and BMI (β = 0.421) were all significant (p&lt;0.05) predictors of body weight goal in women. All athletes significantly (p&lt;0.001) underestimated daily energy (-1,360 ± 610.2 kcal/d), carbohydrate (-301.6 ± 149.2 g/d), and fat (-41.4 ± 34.5 g/d) requirements. Division III collegiate athletes have a low level of sport nutrition knowledge, which was associated with a higher BF %. Women athletes with a higher body weight, BF % and BMI were more likely to select weight loss as a body weight goal. Athletes also significantly underestimated their energy and carbohydrate requirements based upon the demands of their sport, independent of sex.

The layered oxyselenide BiCuSeO has garnered significant interest because of its ability to exhibit low thermal conductivity and a high Seebeck coefficient. This study involved the preparation of Bi1−xNaxCuSeO1−xFx(x=0, 0.05, 0.10, 0.15, and 0.20) ceramics through the processes of high energy ball milling and cold isostatic pressing. A systematic study was conducted to investigate the impact of co−doping Na/F on the thermoelectric performance of BiCuSeO ceramics. Replacing Bi3+ with Na+ results in the introduction of a considerable amount of holes, leading to a notable enhancement in the electrical conductivity and power factor. The conductivity was significantly increased from 9.10 S cm−1 in the pure BiCuSeO to 94.5 S cm−1 in Bi0.85Na0.15CuSeO0.85F0.15 at 323 K. At 823 K, the power factor of the Bi0.85Na0.15CuSeO0.85F0.15 sample achieved 44.8×10−5 W/ m K2. Moreover, the Bi1−xNaxCuSeO1−xFx ceramics exhibit a minimum thermal conductivity of 0.43 W m−1 K−1. As a result, the Bi0.85Na0.15CuSeO0.85F0.15 sample achieves a maximum ZT value of 0.78, which is 7.09 times greater than that of the pure BiCuSeO sample (0.11) .

The adhesion of two-component lipid vesicles to a flat substrate is investigated. The components are characterized by different spontaneous curvatures. The shape of the vesicles is coupled to the lateral distribution of membrane components. The influence of the adhesion on the shape transformations and the lateral distribution of membrane components is investigated. The evolution of the vesicle’s shape and the lateral distribution of membrane components in the process of vesicle adhesion is studied. It has been shown that vesicle adhesion may induce mixing or demixing of membrane components. The change of the vesicle shape due to adhesion facilitates the curvature driven segregation of the membrane components and results in the formation of large membrane domains with various mean curvatures.

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 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.

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.

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.

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.

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.

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

The Ionian Sea is a crucial intersection for various water masses in the Mediterranean. Its hydrography and dynamics play a significant role in the seawater budgets and biogeochemistry of the neighboring sub-basins. Multiple theories have been formulated to gain a better understanding of the Ionian dynamics. These theories primarily attribute the variability of the near-surface Ionian circulation to internal processes. Here, we utilize horizontal currents and temperature-salinity profiles from the Copernicus reanalysis to examine the contribution of baroclinic modes to the variability of the basin horizontal circulation. Our findings demonstrate that, although the basin vertical structure is characterized by three layers, the primary patterns of the Ionian circulation can be attributed to the first baroclinic mode. This mode, along with the barotropic mode, accounts for over 85% of the overall variability in the Ionian circulation, suggesting that only one of the three interfaces separating the different water masses in the basin is dynamically active. We estimate the depth of this interface to be about 490 m. Additionally, our analysis shows that more than 90% of the kinetic energy over the water column is localized above this interface, indicating that the deep layer of the Ionian is dynamically nearly inert.

The study presents empirical results investigating the relationships among renewable and non-renewable energy consumption, CO2 emissions, and GDP within the Visegrád Group (V4) countries. Using FMOLS/DOLS and ARDL approaches, along with causality tests based on the Toda-Yamamoto method, the study explores these relationships at a regional level. The findings indicate that renewable energy has a small positive impact on long-term economic growth, with non-renewable energy having a more significant effect. Moreover, CO2 emissions have a negative impact on economic growth, suggesting ongoing reliance on non-renewable energy sources and a burden on economic expansion. On an individual country level, the effects vary. Poland, Slovakia, and Hungary exhibit a negative relationship between CO2 emissions and economic growth. Energy sources also differ in impact: in Poland, the Czech Republic, and Slovakia, non-renewable energy significantly affects economic growth, while in Hungary, renewable energy plays a more substantial role. Causality tests reveal a causal relationship between CO2 emissions and economic growth in the Czech Republic and Poland, suggesting CO2 emissions significantly influence economic expansion. In terms of energy production, renewable energy is causally related to economic growth in the Czech Republic and Slovakia. All countries demonstrate significant causality between non-renewable energy and economic growth. Additionally, a relationship between renewable energy and CO2 emissions is confirmed in Poland.

This article proposes a superconducting shielding magnetic field model based on the Meissner effect of superconductors, which blocks magnetic fields. By utilizing the shielding effect of the superconductor on the magnetic field during the phase transition, the model achieves intermittent shielding of electromagnetic force, allowing the electromagnetic force to work intermittently on the moving magnet within the model during its operation. The model is analyzed on the basis of superconducting thermodynamic theory, with a focus on the electromagnetic energy of the system. It is concluded that the energy is not conserved during the operation of the model. To verify the correctness of the analysis, electromagnetic simulations and data analysis were conducted via the COMSOL electromagnetic module and Ampère's law superconducting model parameters, which yielded identical results.

This work focuses on short-term forecasting of PV output power. The multilayer perception (MLP), convolutional neural networks (CNN), and k-nearest neighbour (kNN) neural networks have been used singly or in a hybrid (with other algorithms) to forecast solar PV power or global solar irradiance with good success. Their performances in forecasting PV power have been compared with other algorithms but not with themselves. The study aims to compare performance of a number of neural network algorithms in solar PV energy yield forecasting under different weather conditions. The performance of MLPNN, CNN and kNN are being compared using solar PV (hourly) energy yield data for Grahamstown, Eastern Cape, South Africa. The choice of location is part of the study parameters to provide insight into renewable energy power integration in specific areas in south Africa that may be prone to extreme weather conditions. The kNN algorithm was found to have RMSE value of 4.95% and MAE value of 2.74% at its worst performance, and RMSE value of 1.49% and MAE value of 0.85% at its best performance. It outperformed the others by a good margin and kNN could serve as a fast, easy, and accurate tool to forecast solar PV output power.

Background: Extremametly lean athletes could have difficulty for adaptive eating (intuitively or consciously) during ad libitum refeed. Aims: we verificate if there is a relation between adaptive eating and coping strategies with energy intake in a model of refeed proposed for bodybuilders. Methods: Fourteen male bodybuilders (29.6±3.1yrs; 85.6±6.8kg, ≥6 competitions) completed the 4-week each consisting of a 5 days of energy restriction following 2 days of refeed. Dietary assessment, body composition (ultrasound), Recovery stress questionnaire (REST-Q) and BRUMS (Brunel mood scale) were accessed pre and post; Coping Function Questionnaire (CFQ), Mindful Eating Scale version 2 (MES 2) and the Intuitive Eating Scale-2 (IES-2) was used at 4th week. Results: The refeed day resulted in a daily caloric increment of ~44% compared to the average energy intake on the energy restriction days, culminating in a weekly calorie deficit of ~27% and a drop in body mass of 3.1±1.4% with relation to initial values. The most reduced body fat and preserved or gained lean mass. The energy consumption during refeed maintained an inverse relationship with the perception of satiety (r=-0.9; p<0.01), total scores of IES 2 (r=-0.82; p<0.01), as well as with the confidence in hunger and satiety cues (r=-0.62; p=0.02) and congruence in food-body choice (r=-0.56; p=0.04) dimensions. Coping based in emotions maintained a relationship with the total scores of IES 2 (r=0.54; p<0.05) and an inverse relationship with energy intake during refeed (r=-0.42; p<0.05). Conclusion: Our results suggest that a higher perception of internal hunger and satiety signals and higher scores in intuitive eating may contribute to energy intake adequate, even when high scores of coping based in emotions are present.

The creation of protonated water nanoclusters from amorphous water-ice under laboratory conditions suggests the possible ejection of such nanoclusters from ubiquitous amorphous water-ice-covered cosmic dust to interstellar space. The quantum properties of these quintessential water entities introduce a tantalizing prospect that bridges the origins of dark matter, dark energy, and life in the universe. The quantum-entangled diffuse Rydberg electronic states inherent to cosmic water nanoclusters make them plausible candidates for baryonic dark matter. Moreover, they exhibit the capacity to absorb, through the microscopic dynamical Casimir effect, virtual photons originating from zero-point-energy vacuum fluctuations occurring above the water-nanocluster vibrational frequency cutoff. This selective interaction leaves only vacuum fluctuations below these frequencies with gravitational significance, cancelling the vacuum-energy catastrophe and yielding a shared genesis for dark matter and dark energy. Moreover, this theory extends its implications to the origins of life itself, proposing that RNA protocells on Earth and habitable exoplanets may have emerged from the interactions between cosmic water nanoclusters and prebiotic organic molecules, thus yielding an anthropic narrative. Collectively, these findings coalesce into a cosmological framework depicting a cyclic universe, with cosmic water nanoclusters constituting a quintessence scalar field, instead of adhering to the multiverse concept based on cosmic inflation theory. Recent observations of CMB birefringence support this quintessence.

Primary materials supply is the heart for engineering and sciences; depletion of natural resources and an increase in the human population by a billion in 13 to 15 years pose a critical concern on the sustainability of the materials. Therefore, functionalizing renewable materials, such as nanocellulose, possibly exploiting its properties for various practical applications, has been undertaken worldwide. Nanocellulose has emerged as a dominant green natural material with attractive and tailorable physicochemical properties, renewable, sustainable, biocompatibility, and tunable surface properties. Nanocellulose is derived from cellulose, the most abundant polymer in nature with remarkable properties of nanomaterials. This article provides a comprehensive overview of the methods used for nanocellulose preparation, structure-property and processing-property correlations, and the application of nanocellulose and its nanocomposite materials. This article differentiates the classification of nanocellulose, provides a brief account of the production methods that have been developed for isolating nanocellulose, highlights a range of unique properties of nanocellulose that have been extracted from different kinds of experiments and studies; and elaborates on nanocellulose potential applications in various areas. The present review is anticipated to provide the readers regarding the progress and knowledge related to nanocellulose. Pushing the boundaries of nanocellulose further into cutting edge applications will be of particular interest for the future, especially as cost-effective commercial sources of nanocellulose continue to emerge.

Emission trading schemes (ETSs) have become vital tools in striving toward global emission reduction objectives and promoting a sustainable economy. This paper empirically investigates the impact of market conditions on interconnectedness within precious metals, clean energy, green bonds, and carbon markets, focusing on China and the EU ETSs as the study subjects. A TVP-VAR-based asymmetric connectedness approach is adopted to capture the evolving relationships between the variables of interest in the time–frequency domain. The empirical findings reveal that: First, time-varying asymmetric connectedness and spillover effects among clean energy, precious metals, green bonds, and carbon markets are identified in both time and frequency domains under diverse market conditions, with long-term connectedness asymmetry being particularly sensitive, although spillovers exhibit variations. Second, the role and intensity of net transmitters or receivers vary across market conditions and frequency domains, indicating the complex and nuanced nature of market interactions. The EU ETS demonstrates a higher level of connectivity with global markets for clean energy, precious metals, and green bonds when compared to the Chinese ETS. However, it also shows greater susceptibility to fluctuations in market conditions. These results have significant implications for both investors striving to build sustainable diversified portfolios and regulators endeavoring to craft effective policies for risk regulation and sustainable development.

The Vacuum Energy Parameter (VEP) of standard cosmology denotes the fraction of the critical density attributed to the accelerated expansion of the Universe. Astrophysical evidence sets the numerical range of VEP at 0.692 +, - 0.012, yet the root cause of these values is currently unknown. Drawing from the stochastic interpretation of early-Universe cosmology, we develop here a derivation of the VEP based on classical diffusion theory and the Langevin equation. Predictions are shown to be in reasonable agreement with observations.

Without an established energy management plan, human lifestyle improvement is incomprehensible. Adequate energy assets are the key to human lifestyle development, however, energy assets are restricted and exorbitant too. In this paper, an energy control system for a green environment called PMC (Power Management and Control) is proposed. The system is based on hybrid energy optimization, energy prediction, and multi-preprocessing. The blend of GA (Genetic Algorithm) and PSO (Particle Swarm Optimization) is utilized to make a fusion methodology to improve occupant comfort index (OCI) and decrease energy utilization. The main theme of the proposed PMC technique is to improve OCI and decrease energy utilization. The proposed framework gives better OCI when compared with its counterpart Ant Bee Colony along with Knowledge Base framework (ABCKB), GA-based prediction framework (GAP), Hybrid Prediction with Single Optimization framework (SOHP), and PSO-based power consumption framework. Compared with the existing AEO framework, the proposed PMC methodology gives practically the same OCI, but consumes less energy. The proposed PMC methodology additionally accomplished the most extreme OCI (i-e 1) when compared with the existing model FA-GA (i-e 0.98). The proposed PMC model consumed less energy as compared to existing models ABCKB, GAP, PSO and AEO. The proposed model consumed more energy than SOHP but provided better OCI. The comparative outcomes show the viability of the proposed PMC framework in lessening energy utilization and improving the OCI. Unlike other existing mythologies except for the AEO framework, the proposed PMC technique is additionally confirmed through a simulated climate by controlling indoor climate using actuators, like Fan, light, AC and boiler.

With the increasing demand for energy worldwide, researchers from different fields have been striving to improve the sustainability and proper utilization of energy resources. Passive radiative cooling, as a natural energy transport method, can achieve cooling without additional external energy input. This review provides a comprehensive examination of passive radiative cooling, including its fundamental theories and latest development. A particular emphasis is placed on the diverse range of fields where passive radiative cooling has been applied, notably including but not limited to construction and architecture. The current state of applications, potential challenges that may arise with wider adaption and promising research directions for each field are thoroughly discussed. This review underscores the universal applicability and feasibility of passive radiative cooling and contributes to its future development by identifying promising areas for further exploration.

Space and water heating for residential and commercial buildings amount to a third of the European Union’s total final energy consumption. Approximately 75% of the primary energy is still produced by burning fossil fuels, leading to high greenhouse gas emissions in the heating sector. Therefore, policymakers increasingly strive to trigger investments in sustainable and low-emission heating systems. This study forms part of the “Roll-out of Deep Geothermal Energy in North-West-Europe”-project and aims at quantifying the spatial heat demand distribution in the Interreg North-West-Europe region. An open-source geographic information system and selected Python packages for advanced geospatial processing, analysis, and visualization are utilized to constrain the maps. These were combined, streamlined, and optimized within the open-source Python package PyHeatDemand. Based on national and regional heat demand input data, three maps are developed to better constrain heat demand at a high spatial resolution of 100*100m2 for the residential and commercial sectors, and for both together (in total). The developed methodology cannot only be applied to transnational heat demand mapping but also on various scales ranging from city district level to states and countries. In addition, the workflow is highly flexible working with raster data, vector data, and tabular data. Results reveal a total heat demand of the Interreg North-West-Europe region of about 1,700TWh. The spatial distribution of the heat demand follows specific patterns, where heat demand peaks are usually in metropolitan regions like for the city of Paris (1,400MWh/ha), the city of Brussels (1,300MWh/ha), the London metropolitan area (520 MWh/ha), and the Rhine-Ruhr region (500 MWh/ha). The developed maps are compared with two international projects, Hotmaps and Heat Roadmap Europe’s Pan European Thermal Atlas. The average total heat demand difference from values obtained in this study to Hotmaps and Heat Roadmap Europe is 24 MWh/ha and 84 MWh/ha, respectively. It is assumed that the implementation of real consumption data is an improvement in spatial predictability. The heat demand maps are therefore predestined to provide a conceptual first overview for decision-makers and market investors. The developed methods will further allow for anticipated mandatory municipal heat demand analyses.

Abstract: With the continuous integration of various energy systems and the reform of energy trading marketization, the traditional power demand response can no longer meet the needs of multi-energy coupling. For the joint response problem of multi-energy, this paper proposes a comprehensive demand response optimization incentive model considering the user response characteristics, with the complete energy service providers and multiple users as the participants of the comprehensive demand response, to solve the response strategy for the optimal goal of all parties. The implementation architecture of integrated demand response and the electrothermal energy hub model is introduced first. Secondly, the integrated demand response collaborative optimization strategy of the integrated energy service providers and users is established, and the existence and uniqueness of the optimal solution are proved. Finally, the example analysis demonstrates that the proposed strategy can reduce the integrated energy service providers' response cost and user dissatisfaction under multiple scenarios.

Ever since oil was discovered in the Persian Gulf Region in the 1920s, the oil and gas industries have been dominant in the area. These countries are responsible for generating approximately 35 percent of the world's natural gas and 25 percent of its crude oil, making them the largest crude oil producers globally. The release of carbon dioxide (CO2) into the atmosphere is directly linked to the use of fossil fuels. CO2 accounts for 58.8 percent of all greenhouse gas emissions caused by human activities and has a detrimental impact on urban residents through the urban heat island effect. A significant portion of these emissions can be attributed to residential buildings. Some nations exacerbate the problem by relying excessively on fossil fuels. Oil-rich countries provide energy subsidies to the public in order to lower energy costs for their citizens. However, this policy can have negative consequences, including wasteful energy usage in countries like Iran.

The building and construction sector has a significant impact on CO2 emissions and pollutants released into the atmosphere, which contribute to climate change. The EPDB Directive mandates the achievement of a minimum energy class E for all residential buildings by 2030 and an energy class D by 2033. Particularly, in Italy, about 86% of the existing building stock predates the enactment of any energy laws and regulations, making it imperative to apply the energy efficiency interventions. This paper provides a support decision tool for the identification of standardized interventions on the envelope, air conditioning system and domestic hot water production. The study is focused on a specific construction period class (1976 - 1990) in six different climatic zones. The methodological approach is based on a cataloguing phase and definition of Ante Operam energy classes, on the case study identification, the energy requalification interventions identification, solutions simulations, cost estimation. By simulating standardized interventions for each climatic zone, a range of possible combinations will be identified. The most advantageous ones will be determined based on a cost-benefit analysis, considering the potential class jump achieved. The research result is a matrix of energy efficiency interventions that is applicable to each climatic zone and can be extended to the existing housing stock.

The construction industry has witnessed the increasing use of digital tools and smart solutions, particularly, in the realm of buildings energy automation within the concept of smart cities. While to truly realize the potential benefits of smart cities, a broader scope of smart initiatives is required to support the transition from smart buildings towards smart neighbourhoods, appreciated as the critical unit of urban development. To support this interplay of smart solutions between buildings and neighbourhoods, this article aims to collect and review all smart solutions presented in existing scientific articles, technical literature, and realized European projects. These solutions are classified under two main sections of buildings and neighbourhoods, which are investigated through five domains: buildings energy-related uses, renewable energy sources, water, waste, and open space management. Showcasing the quantitative outcomes demonstrates the potential benefits of implementing smart solutions from buildings to neighbourhoods. Moreover, this research concludes that the true enhancement of energy conservation goes beyond the buildings’ energy component and can be genuinely achieved by integrating intelligent elements of the neighbourhood, due to their strong interdependencies. Future research is recommended to focus on assessing the effectiveness of these solutions towards resource conservation.

The global demand for energy has been steadily increasing due to population growth, urbanization, and industrialization. Numerous researchers worldwide are striving to create precise forecasting models for predicting energy consumption to manage supply and demand effectively. In this research, a time-series forecasting model based on multivariate multilayered long short-term memory (LSTM) is proposed for forecasting energy consumption and tested using data obtained from commercial buildings in Melbourne, Australia: the Advanced Technologies Center, Advanced Manufacturing and Design Center, and Knox Innovation, Opportunity, and Sustainability Center buildings. This research specifically identifies the best forecasting method for subtropical conditions and evaluates its performance by comparing it with the most used methods at present, including LSTM, bidirectional LSTM, and linear regression. The proposed multivariate multilayered LSTM model was assessed by comparing mean average error (MAE), root-mean-square error (RMSE), and mean absolute percentage error (MAPE) values with and without labeled time. Results indicate that the proposed model exhibits optimal performance with improved precision and accuracy. Specifically, the proposed LSTM model achieved a decrease in MAE by 30%, RMSE by 25%, and MAPE by 20% compared to the LSTM method. Moreover, it outperformed the bidirectional LSTM method with a reduction in MAE by 10%, RMSE by 20%, and MAPE by 18%. Furthermore, the proposed model surpassed linear regression with a decrease in MAE by 2%, RMSE by 7%, and MAPE by 10%. These findings highlight the significant performance increase achieved by the proposed multivariate multilayered LSTM model in energy consumption forecasting.

Climate change complies firms to introduce various measures to enhance both their competitiveness and sustainability, particularly energy efficiency measures (EEMs). Energy efficiency is particularly important in energy-intensive sectors such as the industrial sector. However, EEMs within the industrial firms are hindered by several internal barriers such as competing interests within firms, the lack of information regarding energy efficiency opportunities, and the low technical competence. In this regard, energy audit aims to improve energy efficiency in facilities and to tackle internal barriers to energy efficiency. We construct a model which aims to explore the importance of energy audit in implementing EEMs and reducing the intensity of internal barriers to energy efficiency. Our research model was empirically tested through survey data gathered from 193 industrial firms in Morocco. Results show that competing interests, the lack of information and the low technical competence hinder the adoption of EEMs within industrial firms. In addition, energy audits enhance EEMs, and mitigate the negative effect of the lack of information and the low technical competence on the adoption of EEMs. However, energy audits do not attenuate the negative effect of competing interests on EEMs. This study reinforces previous studies with additional confirmation regarding the importance of energy audits for tackling the lack of information, and the low technical competence within firms. Furthermore, our study extends prior research as we found that energy audits do not reduce the intensity of competing interests within firms regarding EMMs’ implementation.

Open Inertia Modelling (OpInMod) is a modelling framework designed to create unit commitment and economic inertia dispatch optimisation problems. Present energy system modelling generators do not consider power system inertia in unit commitment and economic dispatch modelling to assess future energy system pathways. However, maintaining sufficient power system inertia in power systems is the foundation for power frequency controllability. The work at hand describes the functionality and approaches of open source tool OpInMod. The softwares universal design approach increases reuse potential. OpInMod is distributed with a set of examples to test and understand OpInMod

While many in-steam tidal energy resource studies have been carried out globally, very few studies have assessed the effect of seabed changes on tidal energy resources. For coastal regions in particular, where the seabed is generally more mobile than in deep waters, bathymetric evolution could have a significant effect on tidal energy production. Here two high-resolution models, one purely hydrodynamic and one morphodynamic, are used to analyse the potential effect of natural morphodynamic evolution on tidal energy resources at two macro-tidal sandy bays, Adaír Bay and San Jorge Bay, in the Upper Gulf of California, Mexico. The high-resolution models are validated using a low-resolution model and ADCP observations to assess the agreement between model predictions and observations of tides at three ADCP moorings within the domain of interest. The models’ skill is evaluated using several error statistics such as the mean relative error, the root mean square error (RMSE), and the correlation coefficient. It was found that the regions with the largest bed changes, and also the largest renewable energy resources, were near the shore. Moreover, the results indicated a good correlation between a) regions with the most significant depth changes, and b) the regions where the difference in annual energy production with and without depth change was largest. Finally, the morphodynamic model was run for two years, and the evolution of a zonal profile (in the west-east direction) off the coast at the southeastern corner of Adaír Bay was inspected. This profile evolved towards a featureless equilibrium profile, in good agreement with the morphological classification for macro-tidal sandy environments and with the model assumptions. But most importantly, this natural evolution would not be detrimental to tidal energy exploitation at the site.