This study examines the impact of natural resource exploitation, renewable energy consumption, economic growth, biocapacity, and information and communication technologies (ICT) on the ecological footprint of BRICS+ nations using panel data from 1991 to 2019. Advanced econometric techniques, including FMOLS, DOLS, CCR, and GMM, reveal significant findings relevant to sustainability-focused policymakers. The results show that natural resource exploitation significantly contributes to environmental degradation, while renewable energy consumption mitigates these effects to varying degrees across the studied countries. Although economic growth is crucial, it worsens ecological footprints unless accompanied by sustainable practices. ICT and biocapacity emerge as key factors in promoting environmental sustainability, with ICT enhancing innovation and efficiency to reduce ecological impacts. The study emphasizes the need for tailored policy frameworks that align economic growth with environmental sustainability, advocating for the adoption of renewable energy, eco-innovations, and green finance initiatives suited to the unique conditions of BRICS+ nations. The findings aim to guide policymakers in advancing sustainable development and mitigating the adverse environmental impacts of rapid industrialization and urbanization, while contributing to the global discourse on achieving a balance between economic growth and ecological well-being in developing countries.

We investigate the cosmological evolution of the universe for a spatially flat FLRW background space within the context of $f(T,B)$ gravity, which is a recently formulated teleparallel theory that connects both $f(T)$ and $f(R)$ gravity under suitable limits. The analysis has been done by focusing on four different $f(T,B)$ cosmological models corresponding to various choices of scale factor, namely emergent, logamediate, and intermediate. In addition to this, we also assume a power-law-like function of $f(T,B)$ gravity. The reconstruction of $f(T,B)$ gravity has been done by considering the Holographic Ricci Dark Energy(HRDE) (a particular case of a highly generalized holographic dark energy given in Nojiri et al. in General Relativity and Gravitation, 38, pp.1285-1304,2006) as the background fluid. We analyze the equation of state parameters and the squared speed of sound for the reconstructed models. Finally, we conducted the thermodynamical analysis for each reconstructed model. The generalised second law of thermodynamics(GSLT) is valid for the four different $f(T,B)$ cosmological models.

Predicting the thermophysical properties of designed materials at the nanoscale is crucial. However, this remains a significant challenge despite numerous efforts by researchers and scientists. This paper presents a unified thermodynamic model to study the size and shape-dependent cohesive energy and the melting temperature of semiconductor nanosolids, including InSb, ZnSe, CdS, and CdSe. The model provides insight into the thermal stability of nanosolid materials by considering the combined impact of size, shape, and packing density. The finding indicates that smaller nanoparticles exhibit a lower cohesive energy than larger ones. Our unified thermodynamic model yields results consistent with experimental values and demonstrates a closer agreement than those from the universal liquid drop model of size-dependent cohesive energy, which includes a shape factor of α = 2/3 for nanowires. According to the results, the melting temperature of nanoparticles drops as their size decreases. Below a diameter of 5 nm, this trend becomes more noticeable. In the nano-scale domain, the nanoparticle's shape also matters greatly. In particular, compared to tetrahedral nanoparticles, nanowires show a lesser reduction in melting temperature. Also, up to a diameter of roughly 10 nm, the melting temperatures of these nanoparticles rise with particle size. The search results show that, especially in the < 5 nm size range, the size and shape of nanoparticles significantly affect their melting point. The models accurately predict the relationship between particle size and melting point for various semiconductor nanomaterials, aligning with experimental findings. Interestingly, the information indicates a potential preference for these nanomaterials to form nanowire structures in the < 5 nm size range. Our research offers helpful insights into the thermophysical properties of these semiconducting materials, which may have significant implications for their use in a diversity of technological applications.

Fractured media are seldom considered viable for storing excess thermal energy seasonally, compared to the more commonly used porous aquifers, due to their heterogeneity, lower storage capacity, and potential for unpredictable flow paths. This study employs COMSOL Multiphysics to create a numerical model of a fractured granite reservoir located below the Bedretto underground laboratory. The energy efficiency of both single-well and doublet systems was evaluated over 25 cycles, each comprising four 91-day phases: injection, storage, production, and resting. Results indicated that the single-well system was more efficient, with energy efficiency increasing with the flow rate. For an injection temperature of 60 °C, the system achieved energy efficiencies of up to 59.3% and 67.7%, after 10 and 25 cycles, respectively, aligning with porous Aquifer Thermal Energy Storage (ATES) system efficiencies at this temperature. Exploration of electricity production using water injected at 120 °C revealed it to be uneconomical and ineffective. However, the most promising use of the retrieved water was found to be direct ground heating for a greenhouse. This technology offers a potential alternative for thermal energy storage in regions lacking suitable porous aquifers, although identifying appropriate locations with the necessary geological characteristics may present significant challenges.

This study presents a comprehensive approach to calculating the free energy of hydration of methane using Molecular Dynamics simulations. We employed the Free Energy Perturbation (FEP) method to determine the Gibbs free energy associated with transferring a methane molecule into water. Simulations were conducted in a cubic simulation box containing one methane molecule and 1000 TIP4P water molecules. The forward and backward routes were both analyzed, providing consistent free energy differences, which validates the robustness of our methodology. The Gibbs free energy profiles demonstrated characteristic energy barriers and stabilization points, indicative of the interaction dynamics in the solvation process. The results demonstrate the robustness of the FEP method implemented in LAMMPS, yielding free energy in close agreement with experimental data and previous computational studies. The calculated free energy differences for methane hydration exhibited deviations of 13% and 8% for the forward and backward routes, respectively, compared to experimental values. These findings underscore the accuracy and efficiency of using LAMMPS for free energy calculations, contributing to the broader understanding of solvation thermodynamics. Additionally, radial distribution functions were analyzed to provide insights into the structural arrangement of water molecules around methane, revealing strong interaction between methane's carbon atom and water molecules.

Camouflage is a natural or artificially process to prevent an object from being detected while camouflage breaking is a countering process for the identification of the concealed object. We report that a perfectly camouflaged object in a two-dimensional scene can be retrieved and detected with stereo-vision assisted three-dimensional (3D) imaging perceived with stereopsis. The analysis is based on binocular energy model applied to general 3D settings. We show that a perfectly concealed object with random noise background can be retrieved with vision’s stereoacuity to resolve the hidden structures. The theoretical analysis is further tested and demonstrated with distant natural images taken by a drone-camera, processed with a computer and displayed in an autostereoscopy. The recovered imaging is presented with removal of the background interference to demonstrate the general applicability for camouflage breaking with stereo imaging and sensing.

Dimethylformamide (DMF), a polar solvent, is commonly used for preparing graphene/epoxy nanocomposites. While commonly previous research has predominantly highlighted the improvement in physio-mechanical properties of these nanocomposites, the effect of DMF on processing and its direct influence on the final characteristics of MXene/epoxy nanocomposites have not been investigated.This unexplored link between DMF dosage, MXene concentrations, and the final composite properties presents an exciting direction for future research. In this study, a fixed dosage of DMF was used with varying MXene concentrations to fabricate the nanocomposites. To assess the reliability of DMF dosage on the characteristics of the fabricated nanocomposites, various evaluation techniques were employed, including dispersion evaluation, mechanical tests, thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), electromagnetic interference (EMI) shielding, and surface roughness measurements. The research outcomes revealed that as MXene concentration increased, the characteristics of the MXene/epoxy nanocomposites, improved across the board, indicating their potential for use in energy storage applications.

In central area of Liaoning province, the thermal performance of rural building envelopes are mostly non-standardized in Northern China, resulting in a significant heat loss. In this study, The objective was to propose some low-cost and energy-efficient solutions. Through a field of inves-tigations, heating energy consumption was saved by 20% and increased construction costs was less than 8000 RMB, which was acceptable for rural residents. In order to achieve this target, NSGA-II algorithm was integrated with Rhino+Grasshopper and EnergyPlus simulation kernel to establish a thermal performance optimization model for heat transfer of the rural building envelopes. Among the above Pareto optimal solutions, the recommended thickness of insulation layer for the room floors, ceilings, and external walls were 70mm, 50mm, and 40mm respectively. Furthermore, try to reduce the window to wall ratio as much as possible. Finally, based on the lower total cost, three technical solutions that rural residents could select according to their specific needs have been put forward.

This study aims to find countries that differ in their development of the agricultural sector in terms of environmental care and to examine the relationship between renewable and non-renewable energy consumption and agricultural sector production in European Union countries. The classification of countries was conducted using the principal component method and biplot. Panel data for the period 2000-2022 and a VAR model, an impulse response function (IRF) and causality tests were used for the study. The results indicate two distinct groups of countries that significantly differ in adopting green agricultural practices. Only seven EU countries stand out for sustainable agriculture with low pesticide use, a significant share of organic farms and high use of renewable energy in agriculture. Energy consumption affects agricultural production differently in the two groups of countries studied: in countries with sustainable agriculture, an increase in renewable energy consumption translates into a positive increase in agricultural production. On the other hand, an increase in non-renewable energy consumption shows a dampening effect on agricultural production growth, especially in countries with less sustainable agriculture. The study results highlight the need to promote renewable energy development in agriculture and raise awareness about the adverse environmental effects of intensive agriculture while emphasising the positive impact of organic agriculture on agricultural production.

This study investigates cloud cavitation suppression around a model scale NACA66 hydrofoil using active water injection and explores the effect of multiple injection parameters. Numerical simulations and a mixed-level orthogonal test method are employed to systematically analyze the impact of jet angle αjet, jet location Ljet, and jet velocity Ujet on cavitation suppression efficiency and hydrofoil energy performance. The study reveals that jet location has the greatest influence on cavitation suppression, while jet angle has the greatest influence on hydrofoil energy performance. The optimal parameter combination (Ljet = 0.30C, αjet = +60 degrees, Ujet = 3.25 m/s) effectively balances energy performance and cavitation suppression, reducing cavitation volume by 49.34% and improving lift-drag ratio by 8.55%. The study found that the jet's introduction not only enhances vapor condensation and reduces the intensity of the vapor-liquid exchange process but also disrupts the internal structure of cavitation clouds and elevates pressure on the hydrofoil suction surface, thereby effectively suppressing cavitation. Further analysis shows that positive-going horizontal jet components enhance the lift-drag ratio, while negative-going components have a detrimental effect. Jet arrangements near the trailing edge negatively impact both cavitation suppression and energy performance. These findings provide valuable reference for selecting optimal injection parameters to achieve a balance between cavitation suppression and energy performance in hydrodynamic systems.

Daylighting design is not only a stage of dimensioning glazed surfaces to provide sufficient natural light to an occupied space, but also a method of analysing how this matter can be achieved without unwanted effects, such as: gains and losses of heat, glare, and variations of the daylighting intensity, at various indoor distances and levels. According to the international regulations in force, glazed surfaces must be designed with a careful balance between the admission of natural light and thermal performance, such as heat loss in winter and heat gain in summer. In a novel project, it is essential to determine the optimal ratio of window-to-wall surface area. This necessity arises because the materials constituting the glazed surfaces of windows typically exhibit lower insulation properties compared to those of the building's walls. This methodology could be applied to building renovations when envelope modifications are possible and suitable. The case study presented in the paper highlights the energy consumed due to a group of windows with a large glazed area in an existing building, located in a temperate continental climate area. The energy consumption results from supplementary artificial lighting required to maintain adequate illumination for indoor activities and that to counterbalance heat loss during colder periods are evaluated. The analysis performed by modifying the glazed surface led to the identification of an optimum value of windows dimensions for an energy consumed minimum.

Semi-Interlocking Masonry (SIM) represents an innovative building system developed at the Centre for Infrastructure Performance and Reliability at The University of Newcastle, Australia. This system employs a unique approach to interlocking mortar-less engineered masonry panels constructed from SIM units. These units are designed to offer substantial energy dissipation capacity, primarily attributed to the friction occurring on the sliding bed joints between the units within the panel during seismic events. The primary aim of this study is to evaluate the viability of incorporating semi-interlocking masonry as infill panels in the construction of multi-storey buildings across diverse geographical locations with varying seismic conditions in Australia. To assess the feasibility of SIM panels in different conditions (according to Australian Standard AS1170) in Australia, a comprehensive analysis using Strand7 is conducted on a three-storey structure incorporating traditional masonry infill panels and SIM panels. The comparison of displacement and base shear capacities is carried out in response to seismic events across various scenarios in different locations within Australia. The insights gained from this comparative analysis contribute valuable information regarding the viability of implementing SIM as a contemporary construction material.

Background: Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, agreement of these devices with gold standard method still require investigation. The aim was to analyze the agreement between a gold standard %BF assessment method with BIA and US devices. Methods: Twenty-three men (age 30.1 ± 7.7 years, 82.5 ± 14.9 kg, 1.77 ± 0.05 m) underwent Dual Energy X-Ray Absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessment. Pearson and concordance correlations were analyzed. T-test compared means between methods, and Bland Altman plots analyzed agreement and proportional bias. Alpha was set at &lt; .05. Results: Pearson coefficients between BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p &lt; .001). Concordance coefficient was high for BIA (0.80) and moderate for US (0.49). BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) were on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p &lt; .001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = .09) and US (p = .057) to present proportional bias and underestimate BF%. Conclusions: Despite the correlation, the mean difference between the methods were significant, and the agreement limits are very wide. This indicate that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

We analyzed the interaction of two acceptor materials, reduced graphene oxide (RGO) and [6,6]-phenyl-C6-butyric acid methyl ester (PCBM), and poly(3-hexylthiphene) (P3HT), as well as the dependence of its photophysical properties with the temperature in the range 90 to 300 K. The nanocomposite of the films was analyzed by optical absorption ultraviolet-visible (UV-Vis) and photoluminescence (PL) and emission ellipsometry (EE) in a function of sample temperature. The surface morphology was studied by atomic force microscopy (AFM). We noted that onset levels (Eonset) of the nanocomposite of P3HT and RGO is smaller than the others. The PL spectra showed the presence of anomalies in the emission intensities in the nanocomposite of P3HT and PCBM. It was also possible to determine the electron-phonon coupling by calculating the Huang-Hys parameters and its dependence with the sample’s temperature. Through EE it was possible to analyze the degree of polarization and the anisotropy. We observed a high degree of polarized emission of the P3HT films which varies subtly according to the temperature. For nanocomposites with RGO the polarization degree in the emission decreases and the roughness on the surface increases. As a result, the RGO improves the energy transfer between adjacent polymer chains at the cost of greater surface roughness. Then, the greater energy transfer may favor applications of this type nanocomposite in OPVC's with enhancement in energy conversion efficiency.

In the ground-based infrared optical remote sensing system, the target signal is very weak due to the dynamic strong light background and the movement of small and small targets. In order to improve the limit detection capability, the background suppression and target enhancement methods are required to be more suitable for this scene. To solve this problem, we first analyze the image features in the current scene, and propose a more perfect point target and noise model. Then, we propose a new WY distribution function based on the Fermi Dirac distribution function, and propose an anisotropic filtering method based on this function, and further suppress the back-ground through the difference results of two steps. Then, based on the distribution function, we further designed an energy concentration accumulation strategy in 9 scale directions, through which the SNR of the target is effectively improved and the suppression ability of the background is enhanced. Through quantitative and qualitative experimental analysis, compared with the same type of algorithms, the proposed method has better robustness against extremely weak targets and dynamic backgrounds.

This study assesses the impact of militarization, industrialization, technological innovation, and energy consumption on CO2 emissions in NATO countries, divided into "traditional" (Group 1) and "new member" states (Group 2), using data from 1985 to 2019. It identifies heterogeneity in effects and dependencies between the groups. Employing Pedroni and Kao panel cointegration tests, a long-term equilibrium relationship among the variables is confirmed. The analysis, using panel ARDL and GMM methods, reveals distinct outcomes for each group. In Group 1, military spending and energy consumption significantly increase CO2 emissions, while industrialization and technological innovation reduce them. Conversely, in Group 2, technological innovation and energy consumption raise emissions, whereas military spending and industrialization decrease them. The findings suggest Group 1 should strategize military expenditure and energy consumption to cut emissions, whereas Group 2 should focus on eco-friendly technology and efficient energy use to achieve environmental sustainability.

Relevance of the subject. Keyword selection is critical to finding relevant literature and requires justification for querying abstract databases and other sources to ensure accuracy and completeness. The topic of Energy Systems is of great importance due to the introduction of renewable energy sources, modern control methods, and complex energy systems during the energy transition. The aim of this study. The goal of this paper was to identify keywords that would be useful to subject matter experts when collecting literature on a particular topic, based on entries in the IEEE Terms field. Data. Bibliometric data were exported from the IEEE Xplore platform in the following order: for 2019-2023, 2000 records sorted by relevance, for 2024, 1680 records current as of April 11, 2024. Analytical methods applied and software used. VOSviewer, Scimago Graphica implementing the Clauset-Newman-Moore algorithm and agglomerative hierarchical clustering method implemented in Multidendrograms. Results. The main issues of the Energy Systems topic are presented in tabular and graphical formats. The fpgrowth utility offers flexible data preparation options, which makes it worthwhile to conduct a separate study to analyze the score of co-occurrence terms given by its algorithm.

The increase in population and the challenges caused by it are always among the concerns of decision-makers and policymakers in large countries. One of the most serious concerns is in the field of energy consumption. Optimizing energy use is one of the most effective ways to manage limited resources and energy. Energy consumption in residential houses constitutes a significant percentage of the total energy consumption worldwide; therefore, current research focusing on mathematical models aims to provide a predictive multi-objective linear mathematical model for residential house consumption. For this purpose, the consumption of water, electricity, and gas for 80 residential houses, including 10 household appliances and equipment on a weekly basis, has been considered. The results showed that the mixed-integer multi-objective predictor model is able to optimize household consumption plans compared to the actual state of household energy consumption. Since the goals of household satisfaction and energy consumption costs in the model conflict with each other, the influence coefficient was calculated to demonstrate the simultaneous achievement of these goals. The optimal value achievable with the default model for the model's purposes is 69%.

The decarbonization of the electricity grid as one among the actions to reduce fossil fuel emissions, and thus their impact on global warming in the future, will be achieved mainly via the integration and widespread diffusion of renewable power sources. This is going to be supported also by the shift from the paradigm production-transmission-distribution, where electricity production oversees large-size power plants, to renewable-based distributed/diffused production, where electricity is generated very close or even by the same (group of) user(s) (or prosumers in the latter case). The number of mid-/small-size installations based on renewable energy technologies will therefore increase substantially, and the related renewable generation will be dominant against that from large-size power plants. Unfortunately, this will reduce the reliability of the grid very likely, unless appropriate countermeasures are taken/implemented, hopefully at the same time the paradigm shift is being achieved. To this aim, it is important to identify the anomalies and main fault causes that might determine in renewable-based power systems. This paper surveys the current state-of-the-art on anomalies and faults affecting wind-PV-storage hybrid power systems, i.e., the main renewable technology ensemble that will establish the future grid, and highlights possible research directions that may help to fill the literature gaps.

The construction industry plays a crucial role in shaping the built environment and contributes to the global economy. However, the construction process is associated with negative impacts on the environment and communities. This paper examines the environmental impacts of construction and presents strategies for mitigating them, focusing on sustainable construction practices. The research draws on a comprehensive literature review, case studies, and expert interviews to fully understand the construction industry and its environmental effects. The findings indicate that the implementation of greater supervision of every construction project phase, using alternative design practices, and the use of sustainable construction practices can reduce the negative impacts of construction on the environment and society. The study concludes that sustainable construction practices can contribute to a better environment for a better quality of life and should be embraced by the construction industry. The recommendations for future work include the adoption of green building standards, the use of renewable energy sources, the reduction of waste, and the promotion of stakeholder engagement. Future research should focus on the evaluation of the effectiveness of these strategies and their scalability.

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.

This study aimed to evaluate a cantilever beam-type piezoelectric energy harvester operating on train-induced vibrations for powering Wireless Sensor Networks (WSNs) used in railway track monitoring systems. The harvester's behaviors under different conditions are simulated in MATLAB using the analytical model. Natural frequency, maximum deflection, and stress were calculated with greater precision using eigenfrequency and stationary analysis using COMSOL Multiphysics. At a base excitation of 2 g and a resonant frequency of 4.38 Hz, the simulated results showed that the developed energy harvester prototype could generate up to 14 V of AC output voltage and 550 mW of output power. These findings highlight the promising potential of the proposed energy harvester for transforming train mechanical energy into electrical power. This energy harvester's viability and dependability for real-world applications in monitoring railway tracks are supported by developed analytical and simulation models.

The article delves into the crucial realm of compressing hydrogen in its gaseous state, a pivotal process for enhancing its viability in both civil and industrial sectors. The study initiates by providing a concise overview and comparison of diverse hydrogen storage methodologies, laying the groundwork with an in-depth analysis of hydrogen's thermophysical properties. It scrutinizes plausible configurations for hydrogen compression, aiming to strike a delicate balance between energy consumption, predominantly derived from the fuel itself, and the requisite number of compression stages. Notably, to render hydrogen storage competitive in terms of volume, pressures of at least 350 bar are deemed essential, albeit at an energy cost amounting to approximately 10% of the fuel's calorific value. Multi-stage compression emerges as a crucial strategy, not solely for energy efficiency, but also to curtail temperature rise, with an upper limit set at 200°C. This nuanced approach is underlined by the exploration of compression levels commonly cited in the literature, particularly 350 bar and 700 bar. Ultimately, the study advocates for a three-stage compression system as a pragmatic compromise, capable of achieving high-pressure solutions while keeping compression work below 10 MJ/kg, a threshold indicative of sustainable energy utilization.

Direct Energy Deposition (DED) is a versatile and efficient method in metal additive manufacturing. However, humping, caused by abnormal dynamics in the melt pool (MP), poses a significant threat to the geometric integrity of manufactured products. Current state-of-the-art (SOTA) methods primarily detect humping by analyzing late-stage spatial abnormalities, such as MP detachment. This approach is fundamentally reactive, leading to a tendency to miss early humping spatiotemporal dynamics, like cyclic elongation of the MP. This study introduces a novel, proactive indicator named VIMPS (Variability of Instantaneous MP Solidification-Front Speed), a physics-based tool designed to quantify early abnormal fluctuations in MP solidification speed. The experiments demonstrate VIMPS correlation with humping-induced geometric inaccuracies. By capturing early spatiotemporal dynamics of the MP, VIMPS reduces detection latency by 30 seconds compared to existing SOTAs that focus solely on spatial abnormalities. This significant improvement transforms detection from reactive to proactive, providing the time needed for corrective actions to enhance the overall productivity and quality of the DED process.

The rebound behaviors of rubber balls based on ethylene-propylene-diene monomer (EPDM) / chlorinated butyl rubber (CIIR) blends were investigated systematically. A novel method was proposed to characterize the damping capacity of the EPDM/CIIR blends. The damping capacity can be represented by the rebound height of rubber balls, and lower rebound height corresponds to better damping capacity. A mathematical model expressed by an equation obtained through theoretical derivation has been proposed to predict the rebound height of the rubber balls. The energy dissipation rate (EDR) defined by the ratio of the height loss to the rebound time was proposed to further characterize the damping capacity. The EDR value shows the highest for the pure CIIR and lowest for the pure EPDM, showing a decrease trend with the increase of EPDM content in the rubber blends. By comparison one can obtain that the damping capacity of the EPDM/CIIR blends decreases with the decrease of external excitation, the conclusion of which plays a key role in the formulation design of viscoelastic damping rubber materials.

The wood-based panel industry is experiencing an excessive accumulation of solid residues from the production of medium-density fiberboard (MDF) panels and moldings. It is possible to create new MDF products with acceptable physical and mechanical properties by revaluing MDF residues. Additionally, those products’ thermal properties can be improved by incorporating phase change materials (PCMs). This study aims to develop a wood-based fiberboard made of MDF residues, capable of storing thermal energy. Two types of PCMs, two PCM ratios, and two types of adhesives were used to produce eight different types of panels. The vertical density profile, thickness swelling, water absorption, internal bond (IB), and static bending properties – modulus of elasticity (MOE) and modulus of rupture (MOR) – were determined for each panel type. The specific heat of the panels was also determined. The results show the panels’ densities were greater than 700 kg/m3. Thickness swelling in water improved by 23% compared to the reference value of the control panel PCMs after PCM incorporation. The highest IB value was 1.30 MPa, which is almost three times the minimum required by regulation standards. The incorporation of PCMs reduced the panels’ bending properties compared to the properties of the control panels. Even though the values obtained are sufficient to comply with the minimum values set out in ANSI standard A208.2 with a MOE value of 2072.4 MPa and the values obtained are sufficient to comply with the minimum standards with a MOE value of 2072.4 MPa and a MOR value of 16.4 MPa. When microencapsulated PCM is used, the specific heat of the panels is increased by more than 100% over that of the control panels. This study develops a feasible alternative for using MDF residues: to create fiberboard that is capable of storing thermal energy and has adequate physical and mechanical properties.

This research aimed to investigate the relationship between climate policy uncertainty (CPU), clean energy (ENERGY), carbon emission allowance prices (CARBON), and Bitcoin returns (BTC) for the period from August 2012 to August 2022. The empirical analysis strategies utilized in this study included the Fourier Bootstrap ARDL long-term coefficient estimator, Fourier Granger Causality, and Fourier Toda Yamamoto Causality methods. Following the confirmation of cointegration among the variables, we observed a positive relationship between BTC and CARBON, a positive relationship between BTC and CPU, and a negative relationship between BTC and ENERGY. In terms of causal associations, we identified one-way causality running from CARBON to BTC, BTC to CPU, and BTC to the ENERGY variable. The study underscores the potential benefits and revenue opportunities for investors seeking diversified investment strategies in light of climate change concerns. Furthermore, it suggests actionable strategies for policymakers, such as implementing carbon taxes and educational campaigns, to foster a transition towards clean energy sources within the cryptocurrency mining sector and thereby mitigate environmental impacts.

Three Seas Initiative (3SI) is still an underresearched area and is particularly important due to historical circumstances and economic backwardness. A study was carried out to assess the impact of renewable energy and production generated by the agricultural sector on CO2 emissions in 3SI countries between 2008 and 2020. The study used panel data analysis based on the two-step system generalised method of moments (GMM) and the Dumitrescu-Hurlin panel causality test. The results show that a 1% increase in the value-added generated by agriculture increases CO2 emissions in the countries studied by 0.11%. In contrast, a 1% increase in GDP leads to a 0.29% increase in CO2 emissions. Conversely, when renewable energy consumption increases by 1%, CO2 emissions fall by 0.25% in the countries studied. One way to reduce CO2 emissions from agricultural production in the short term is to increase the share of renewables, which, incidentally, is in line with EU action.

NiV2O6 thin films were grown on glass slides with varying thicknesses using the nebulizer spray pyrolysis. The impact of thickness on the thin films' optical, structural, morphological, and electrical characteristics was systematically investigated. The X-ray diffraction and micro-Raman analysis confirmed the formation of the triclinic NiV2O6 system. Surface morphology and roughness variations in the as-deposited NiV2O6 films were studied using scanning electron microscopy (SEM) and a profilometer. Optical properties, including optical band gap (Eg), extinction coefficient (k), absorption coefficient (α), and refractive index (n), were determined through optical reflectance and transmittance measurements. The optical energy gap of the as-deposited NiV2O6 films decreased from 2.3 eV to 1.9 eV with increased layer thickness. Furthermore, the photo-detectivity of the films demonstrated an enhancement corresponding to the prolonged spray time. The sensitivity values obtained for visible irradiation are 328, 511, and 433 for samples S1, S2, and S3, respectively. The obtained results are imputed to the specific porous microstructure.

The emergence of electric vehicles has brought new issues such as the problem of rolling element bearings (REBs) operating at high speeds. Losses due to these components in mechanical transmissions are a key issue and must therefore be taken into account right from the design stage of these systems. Among these losses, the one induced by the motion of rolling elements , known as drag loss, becomes predominant in high-speed REBs. Although an experimental approach is still possible, it is difficult to isolate this loss in order to study it properly. A numerical approach based on CFD is therefore a possible way forward, even if other issues arise. The aim of this article is to study the ability of such an approach to correctly estimate the drag coefficient associated with the motion of rolling elements. The influence of the numerical domain extension, the mesh refinement, the simplification of the ring shape and the presence of the cage, on the values of the drag coefficient is presented. While it seems possible to compromise on the calculation domain and mesh size, it appears that the other parameters must be taken into account as much as possible to obtain realistic results.

The scientific community has shown considerable interest in Industry 4.0 due to its capacity to revolutionise the manufacturing sector through digitalisation and data-driven decision-making. However, the actual implementation of Industry 4.0 within complex industrial settings presents obstacles that are typically beyond the scope of mainstream research articles. In this paper, a comprehensive case-study detailing our collaborative partnership with a leading medical device manufacturer is presented. The study traces their evolution from a state of limited digitalisation to the development of a digital intelligence platform that leverages data and machine learning models to enhance operations across a wide range of critical machines and assets. The main business objective was to enhance the energy efficiency of the manufacturing process, thereby improving its sustainability measures while also saving costs. The project encompasses energy modelling and analytics, Fault Detection and Diagnostics (FDD), renewable energy integration and advanced visualisation tools. Together, these components enable informed decision making in the context of energy efficiency.

The UN Sustainable Development Goal 7 Report 2022 is about ensuring access to clean and affordable energy, which is key to the development of agriculture, business, communications, education, healthcare, and transportation. The lack of access to energy hinders economic and human development. Nevertheless, the current pace of progress is insufficient to achieve Goal 7 by 2030. Huge disparities in access to modern sustainable energy persist. Rising commodity, energy and shipping prices have increased the cost of producing and transporting solar photovoltaics modules, wind turbines and biofuels worldwide, adding uncertainty to a development trajectory that is already far below Goal 7 ambitions. Achieving energy and climate goals will require continued policy support and a massive mobilization of public and private capital for clean and renewable energy such as methane from biomass. An important factor in improving methane yield from biomass waste is pre-treatment of the biomass prior to anaerobic digestion. Size reduction of lignocellulose biomass is important for changing and increasing digestibility thus increasing methane yield. A Hollander beater was used as the mechanical pre-treatment machine throughout this study. Results indicate that methane yield is directly proportional to feedstock/Inoculum (F/I) ratio as higher F/I ratio led to higher methane yield. It was observed at an F/I ratio of 0.5 that 5 minutes pre-treatment time produced highest methane yield, while the lowest methane yield was observed at an F/I ratio of 0.2 with 1 minute of pre-treatment time. Methane yield decreased by 30% from 140 mL gTS-1 at F/I ratio 0.5 with 5 minutes pre-treatment time to 98 mL gTS-1 at F/I 0.2 with 5 minutes pre-treatment time. The optimum methane yield was attained at high F/I ratio allowing sufficient nutrient essential for complete degradation of biomass. Overall, this research shows the Hollander beater is not efficient in optimizing methane yield for cardboard.

In the context of the coordinated development of digital economy and environmental protection, we take the strategy of "Broadband China" as a quasi-natural experiment, adopts the panel data of 284 cities from 2007 to 2020, and evaluates the policy effect of digital economy on total factor energy efficiency through the progressive DID model. The results show that: The construction of "Broadband China" demonstration city has significantly promoted the improvement of the total factor energy efficiency of the demonstration city, but there is also significant urban heterogeneity, which is manifested in the significant improvement of the total factor energy efficiency of the eastern city, the southern city, the big city and the non-resource-based city. It has no significant effect on the total factor energy efficiency of central and western cities, northern cities, small and medium-sized cities and resource-based cities. The construction of "Broadband China" demonstration cities can improve total factor energy efficiency by promoting technological progress and strengthening environmental regulations. Therefore, we should further strengthen the construction of digital infrastructure and give full play to its positive effects. Different cities should seek differentiated development paths based on their own resource endowments and development conditions, so that the digital economy can effectively improve the total factor energy efficiency.

We considered the hypothesis that the sources of dark energy (DE) could be black holes (BHs) or more exotic objects, such as naked singularities or gravastars. We proposed a definition of the presence of DE in the Universe and a criterion for what can be considered the source of this dark energy. It is based on the idea of the accelerated expansion of the Universe, which requires antigravity caused by large negative pressure. A recently proposed hypothesis was examined that mass of BHs increases with time according to the same law as the volume of the part of the Universe containing it and the population of BHs can mimic DE. We demonstrate the reasons why it cannot be accepted, even if all the assumptions on which this hypothesis is based are considered true.

We review our theory of interdependence applied to autonomous human-machine teams, with which we have made several generalizations based on theory that have led to new discoveries, compared to social science which is struggling to break free of its validation crisis, but also has no generalizations to new discoveries with human teams, let alone to human-machine teams. In this invited article, based around the stability of a team, of our discoveries, we review the uncertainty between a team's structure and its performance, our first finding. We generalize that finding to deception, vulnerability, innovation and fittedness. From there, our next generalization is to the quantum likeness of interdependence and quantum mechanics; we move on to Shannon holes, knowledge, and conclude with the value of debate and the need for boundaries to contain debate, to reduce interference, and to protect states of interdependence. After the introduction, we extend our model in Section 2 to energy and time, and we close with a brief review of innovation and future plans.

Industry 4.0 is in continuous technological growth that benefits all sectors of industry and society in general. This article reviews the concept of Digital Twin (DT) and the interest of its application in photovoltaic installations. A comparison is made on how other authors use the DT approach in photovoltaic installations to improve the efficiency of the renewable energy generated and consumed, the energy prediction and the reduction of the operation and maintenance costs of the photovoltaic installation. It is reviewed how, by providing real-time data and analysis, DTs enable more informed decisions in the solar energy sector. The objectives of the review are to study the digital twin technology and to analyze its application and implementation in photovoltaic systems.

The U.S. Energy Information Administration (EIA) provides crucial data on monthly and annual fuel consumption for electricity generation. This data covers significant fuels such as coal, petroleum liquids, petroleum coke, and natural gas. Fuel consumption patterns are highly dynamic, influenced by diverse factors. Understanding these fluctuations is essential for effective energy planning and decision-making. This study outlines a comprehensive analysis of fuel consumption trends in electricity generation. Utilizing advanced statistical methods, including time series analysis and autocorrelation, our objective is to uncover intricate patterns and dependencies within the data. This paper aims to forecast fuel consumption trend for electricity generation using data from 2015 to 2022. Several time-series forecasting models, including all four benchmark methods (Mean, Naïve, Drift, and seasonal Naïve), Seasonal and Trend Decomposition using Loess (STL), Exponential Smoothing (ETS), and Autoregressive Integrated Moving Average (ARIMA) methods, have been applied. The best-performing models are determined based on Root Mean Squared Error (RMSE) values. For Natural Gas (NG) consumption, the ETS model achieves the lowest RMSE of 20,687.46. STL demonstrates the best performance for coal consumption with an RMSE of 5,936.203. The seasonal Naïve (SNaïve) model outperforms others for petroleum coke forecasting, yielding an RMSE of 99.49. Surprisingly, the Mean method has the lowest RMSE of 287.34 for petroleum liquids, but the ARIMA model is reliable for its ability to capture complex patterns. Residual plots are analyzed to assess the models' performance against statistical parameters. Accurate fuel consumption forecasting is very important for effective energy planning and policymaking. The findings from the study help policymakers strategically allocate resources, plan infrastructure development and support economic growth.

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.

In the last ten years, plasma waste treatment has gained increasing prominence as a technology in response to growing challenges in waste disposal and the recognition of opportunities for generating valuable by-products. The efficiency and outcomes of this process are intricately linked to the characteristics of the plasma involved, such as plasma enthalpy and heat flux. We employed an experimental radio frequency inductively coupled plasma (RF-ICP) torch operating at atmospheric pressure to generate plasma. Utilizing optical emission spectroscopy (OES), we measured plasma parameters, specifically the effective electron temperature (Teff) and plasma density (ne), while varying argon gas flow rates and RF powers. Our investigations revealed that both flow rate and RF power exert significant control over plasma parameters, and we observed an unusual phenomenon within this range of discharge pressures. Consequently, both the plasma's enthalpy and the heat flux it generates are influenced by variations in both flow rate and RF power.

The main development direction of energy efficiency technologies in construction is the creation of various materials with a complex structure and unique strength, thermal and other properties. The aerogel is a material with high porosity and excellent thermal insulation properties. This paper provides the state-of-the-art of aerogel applications for the additive manufacturing of energy efficient buildings. This work provides the experimental and numerical assessment results of thermal conductivity of aerogel-enhanced blanket, the experimental assessment results of thermal performance of aerogel-enhanced building structure, the experimental assessment results of the aerogel application as mixture powder component of the concrete mixture to printing building and the experimental assessment results of the aerogel application as parget powder component. Experimental results show the effect of aerogel powder component application: thermal conductivity decreased by 25%.

More water utilities are adopting Aquifer Storage and Recovery (ASR) to balance long-term water supply and demand. Due to large implementation and operation costs, ASR projects need to be optimized, particularly for energy use, which is a major operating expense. This study examines the relationships among energy use, recharge, and recovery at two ASR projects in the western United States. The major finding is an economy of scale for recovery processes, but not for gravity-fed recharge processes. The economy of scale found is as follows: the energy intensity recovered decreases with volume. This suggests it is more energy-efficient to recover large volumes of water in one interval instead of recovering smaller volumes at more frequent intervals. The H2Oaks recovery process experienced a 78% decrease in energy intensity from 0 to 50,000 m3 recovered, while the Sand Hollow site experienced a 43% decrease in energy intensity from 0 to 50,000 m3 recovered. Statistical analyses of the recovery process showed p values lower than 0.0001, R2 values between 0.43 and 0.57, and a RMSE value between 0.55 and 2.1, indicating the presence of a moderate correlation between energy and volume. This economy of scale has been observed in multiple instances in water and wastewater treatment. This finding not only has applications to ASR but also all recovery or recharge wells, whether or not they are paired with each other. Furthermore, this study confirms the need for more reliable and accessible energy data to fully understand the implications of the energy–water nexus.

Penrose’s singularity from 1965 predicted that in the center of the black hole space-time curvature is infinite and consequently gravity force there is infinite. In 2014 NASA measured universal space has Euclidean shape. This means that stellar objects cannot curve universal space and that the space-time singularity model has no physical existence. In the center of black holes energy density of superfluid space is so low that the electromagnetic properties of space are changed. This causes electromagnetic forces between the nucleus and orbiting electrons to become unstable. In the center of a black hole, atoms are falling apart into elementary particles. Black holes are rejuvenating systems of the universe, they transform old matter into fresh energy in the form of elementary particles. Astrophysical jets are the outcome of this process.

In the context of high-temperature water vapor treatment, Zn-Mg-Al alloy-coated steel sheets exhibit the emergence of a black surface. This study aims to explore the factors and mechanisms contributing to surface blackening by inducing black surfaces on Zn-Mg-Al alloy-coated steel sheets, which were fabricated through molten coating subjected to water vapor treatment at 150 degrees Celsius. The surfaced composition was predominantly identified as ZnO, a zinc oxide film, validated through X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). Morphological analysis of the surface and cross-section post-water vapor treatment revealed a disrupted lamellar structure with diffused features, resulting in the formation of an oxide film. Optical properties analysis demonstrated an increased absorbance and a decreased bandgap energy after water vapor treatment, indicative of an augmented blackening effect. Consequently, the high-temperature water vapor treatment led to the formation of oxides on the surface, with the highly reactive Mg and Al extracting oxygen from the predominantly present ZnO surface. This process resulted in the creation of an oxygen-deficient oxide, ultimately causing surface blackening.

New ways of generating energy are currently being discussed, with a transition from traditional primary sources to more environmentally friendly options, particularly renewables. Energy storage is also closely related to this transition. Battery storage currently dominates this area. However, flywheel energy storage system (FESS) technology offers an alternative that uses stored kinetic energy to be transformed into mechanical energy and, using a motor-generator, electrical energy. FESS technology is thus flexible and can be applied in different industrial applications. The management of the technology of recycling W-MMC waste material from other products and the subsequent trial production of high-strength W-MMC material with a density of more than 17 500 kg/m3 from recycled powders allowed to test the limits of the so-called "heavy" flywheels used in rotor production. Materials with densities ≥ 7 800 kg/m3, and operating at lower to medium speeds up to 20 000 rpm. The results achieved lead to the conclusion that the developed recycled materials of the W-MMC type with a density ≥ 17 500 kg/m3, with a yield strength of 1 200 - 1 700 MPa depending on the production method, can be used as a substitute for the structural steels used today, without an enforced reduction of the maximum allowed rotor speed due to exceeding the maximum allowed stress.

This paper examines patterns and drivers of energy choices for cooking and lighting in South Africa using the Statistics South African (StatSA, 2022) Census data at district municipality (districts) levels. Employing spatial and regression analysis, the findings show that electricity is the main source of energy for cooking across South Africa. However, there is a large swathe of the country covering districts, such as Vhembe and Mopani in Limpopo, eastern Mpumalanga, KwaZulu-Natal, and northern Eastern Cape provinces, where wood is the predominantly used energy type for cooking. There is almost uniform use of gas for cooking across the country. Electricity is the main energy source for lighting in South Africa. It is followed by candles, likely explained by loadshedding, and surprisingly solar energy a distant third. In terms of drivers, dwelling types play statistically significant role in what energy type to use for cooking and lighting, albeit differently. In terms of lighting, formal dwelling is positively related to the choice of electricity and informal dwelling is related to the choice of electricity (negatively) and candles (positively) for lighting. The level of higher education, household size, and the dependency ratio have varied statistically significant roles in the choice of either energy type for cooking or lighting by formal, informal, and traditional dwellers. Relevant policy prescriptions that are needed to engender the country towards sustainable energy use, diversification of energy types from electricity to other renewable energy sources, such as solar, and reduction in over-dependency on the biomass energy sources, such as paraffin and wood, especially in rural and poor districts, are proposed.

We study the coupling of two topologcal subsystems in distinct topological states, and show that it leads to a precursor behavior of the topological phase transition in the overall system. This behavior is solely determined by the symmetry classes of the subsystem Hamiltonians and coupling terms, and is marked by the persistent existence of subgap states within the bulk energy gap. By investigating the critical current of Josephson junctions involving topological superconductors, we also illustrate that such subgap states play crucial roles in physical properties of nanoscale devices or materials.

As the global demand for renewable energy continues to rise, biogas technology has emerged as a promising solution for sustainable energy generation. This review article presents the advantages of biogas technologies and extensively discusses the main principles of biogas production in the methane fermentation process. In this respect, the main parameters of the process, which require monitoring and are at the same time decisive for its course and efficiency are described, the principles of substrate selection are discussed and the necessity and advantages of the use of organic waste according to the model of a circular economy and the concept of sustainable development, are indicated. The part on biogas production is summarised with an explanation of the necessity to treat and purify biogas, taking into account the share of methane extracted. A special place in this paper is devoted to the design, construction, functioning and operation of biogas plants, based on both scientific and practical aspects. In conclusion of this chapter, the economic aspects and profitability of operating biogas plants are discussed, taking into account, in a theoretical balance sheet – in addition to investment and operating costs and the availability and cost of raw materials – the possibilities of producing and using electricity and heat, as well as environmental and social benefits. The article concludes with a discussion of opportunities and barriers to the development of biogas plants, pointing to: financial issues, access to feedstock, political regulations, public awareness and the geopolitical situation as key factors issues related to biogas plants – in different regions of the world.

One of the future challenges of increasing the harnessed solar power is efficiency using of CubeSat sides. One of the approaches is using integrated antenna systems with solar panels or payloads. This study proposes a new approach to the use of integrated antenna systems in remote sensing missions. In this approach, due to the integration of antenna system with payload (in our case, with camera), it is possible to achieve a significant increase in the power generation. Calculations are carried out for cases when the antenna system are integrated with the optical system (α = 0°), which implies that they use one plane, in the second case they are spaced at an angle of α = 90° and in the third case when they are directed to opposite sides (α =180°). In the case of α = 0°, where the camera and antenna module are aligned co-axially, there is no energy expenditure for CubeSat orientation. However, in the other two cases, energy is required for rotation and maintenance of the specified orientation throughout the entire duration of the satellite's flight over the ground station, amounting to 111.99 mW when α = 90° and 44.33 mW when α = 180°.

Copper-nitride (Cu3N) semiconductor material is attracting much attention as a potential, next-generation thin-film solar-light absorber in solar cells. In this communication, polycrystalline Cu3N thin films were prepared using reactive-RF-magnetron-sputtering deposition, at room temperature, onto glass and silicon substrates. The very-broadband optical properties of the Cu3N thin film layers were studied by UV-MIR (0.2-40 μm) ellipsometry and optical transmission, to be able to achieve the goal of a low-cost absorber material to replace the conventional silicon. The reactive-RF-sputtered Cu3N films were also investigated by focused ion beam scanning electron microscopy, and both FTIR and Raman spectroscopies.

Implementing High-Performance Computing to solve In-Memory Data Grid (IMDG)-based energy infrastructure resilience research problems in a heterogeneous environment presents a challenge to workflow management systems. Large-scale energy infrastructure needs multi-variant planning and tools to allocate and dispatch resources in IMDG taking into account the subject domain specificity, resource characteristics, and constraints and quotas for resource use. To that end, we propose a workflow management system using our Orlando Tools framework. To scale computing resources, we provide their integration and use corresponding software to determine key application parameters that can significantly impact the processed data size and the required number of allocated resources. We automated the IMDG cluster launch for the workflow executions. To demonstrate the advantage of our solution, we apply it to evaluate the resilience of the existing energy infrastructure model. Compared to similar approaches, our approach explores large infrastructures by modeling many simultaneously failed elements of different types up to the number of network elements. In terms of problem-solving efficiency and resource use, we achieve near-linear speedup with increasing the number of nodes of each resource.

High-performance insulation and airtight building envelopes are the two most important factors to optimize the building energy efficiency and thermal performance. However, thermal performance of building envelopes can be significantly affected by thermal bridging. Thermal bridges can take place at different locations of the building envelope, causing added transmission losses, increasing heat flow, lower inner surface temperatures. Thermal bridges are regarded in all national regulations for new buildings of all states of European Union (EU) but there are no specifications assessing balconies to wall junctions and the impact on the building thermal performance is not well regulated. In this paper, balcony to wall thermal bridge assessment using infrared thermography is highlighted. The originality is that, infrared thermography, has been applied to a real living latest building in the north east of France showing that there is noncompliance in the national regulations as some exigencies are not met. Thermography of thermal break windows and window doors has also revealed air leakage. The goal, is to illustrate that thermal imaging is a means of quality assurance to new building specifications and should include a clause specifying quality assurance procedure for balconies junction in national building regulations for all states if the EU.

The aims of this paper can be traced back to goals number seven, twelve and thirteen introduced by Agenda 2030, namely "affordable and clean energy", “responsible consumption and production” and "climate action”, respectively. This is due to the fact that the present work supports decarbonization processes acting in a direct way on the electricity consumption achieved by plants pertaining to the waste industry; in fact, this study aims at the realization of a machine learning model for predicting the energy consumption achieved by a mechanical biological treatment (MBT) waste plant located in central Italy, given the distribution of the entering waste. This model is implemented in MATLAB. The model can be used to tune the distribution of the entering waste in order to adapt the plant energy consumption to the capability of the energy sources and can serve as a play-ground model for other energy transformation plants. The results of the study, which feed the literature on the application of artificial intelligence to real industrial plants, could be used to determine energy efficiency actions that could be incorporated into Property’s strategic planning.

By utilizing a generalized version of the Madelung quantum-hydrodynamic framework that incorporates noise, we derive a solution using the path integral method to investigate how a quantum superposition of states evolves over time. This exploration seeks to comprehend the process through which a stable quantum state ultimately emerges in the presence of fluctuations induced by the noisy gravitational background. The model defines the conditions that give rise to a limited range of interaction for the quantum potential, allowing for the existence of coarse-grained classical descriptions at a macroscopic level. The theory uncovers the smallest attainable level of uncertainty in an open quantum system and examines its consistency with the localized behavior observed in large-scale classical systems. The research delves into connections and similarities with decoherence theory and the Copenhagen interpretation of quantum mechanics. Additionally, it assesses the potential consequences of wave function decay on the measurement of photon entanglement. To validate the proposed theory, an experiment involving entangled photons transmitted between detectors on the Moon and Mars is discussed. Finally, the findings of the theory are applied to the creation of larger Q-bits systems at elevated temperatures.

Portugal, in line with the European Union, is aiming for carbon neutrality by 2050 (Net 1 Zero), which implies a transition to sustainable energy sources. Climate change is all too evident, extreme weather periods are occurring in a cyclical manner, with greater brevity to such an extent that the grid operator must deal with production scenarios where it can no longer rely on hydroelectric production given the recurring drought situation. This situation increases dependence on thermal production using natural gas and imports. This has significant economic implications. Portugal has exploited its onshore wind potential, reaching an installed capacity of 5.671 MW by 2022. However, the expansion of onshore wind energy is limited to reinforcing existing infrastructure. To overcome these challenges, it is necessary to expand the exploitation of offshore wind potential that is already underway. This article proposes the location of offshore wind production platforms along the Portuguese coast. This allows for an analysis of offshore production and its optimization according to the minimum cost per MWh in the face of extreme scenarios, i.e., in periods of extreme drought where hydroelectric production capacity is practically non-existent. The model is fed by using market price indications and the amount of energy needed for the following day. Using forecast data, the model adapts offshore wind production for the following day according to the minimization of the average market price. The results of the simulations allow us to conclude that despite the high cost of offshore technology (in deep waters), in extreme climate scenarios, it enables cost reduction and a clear decrease in imports.

Thermoelectric (TE) waste heat recovery has attracted significant attention over the past decades, owing to its direct heat-to-electricity conversion capability and reliable operation. However, methods of system-level TE design optimization for specific application systems have not been thoroughly investigated. This work theoretically studies the performance optimization and exergy analysis of TE systems for recovering waste heat from the exhaust ducts of a gas turbine power plant. A numerical tool has been developed to solve the coupled charge and heat current equations with temperature-dependent material properties and convective heat transfer at the interfaces. Our calculations show that at the optimum design with 50 % fill factor and 6-mm leg thickness made of state-of-the-art Bi2Te3 alloys, the proposed system can reach power output of 10.5 kW for the TE system attached on a 2 m-long, 0.5 x 0.5 m2-area exhaust duct with system efficiency of 5 % and material cost per power of 0.23 $/W. Moreover, our extensive exergy analysis reveals that only 1 % of the exergy content of the exhaust gas is exploited in this heat recovery process and the exergy efficiency of the TE system can reach 8 % with improvement potential of 85 %.

Static and dynamic analysis of website security risks is generally used for website security meas-urements. The website security measurements method recently proposed includes similarity hash-based website security risk analysis and machine learning-based website security risk anal-ysis. In this study, a method that can be performed through information disclosed on the Internet was proposed to measure the risk of a website. DNS information, IP information, and website history information are required to measure the risk of a website. In addition, global traffic rank-ing, malicious code distribution history, and HTTP access status can be checked in the website history information. In this study, information related to the security risk of websites in a total of 2,000 domains was collected and analyzed in 1,000 normal and malicious domains. Through the experiment results, 11 open information collection items were selected to measure the security risk of the website. This study presented the possibility of using public information collection to measure website security risk.

To determine the impacts of metabolizable energy levels on the performance indices of geese and to forecast the ideal range of dietary metabolizable energy levels, this study was carried out. Literature on the effects of dietary metabolized energy level on the performance of geese was searched from CNKI, Wanfang, VIP, PubMed, Web of Science, and ScienceDirect databases from January 1, 2000, to December 31, 2022. A dose-response meta-analysis was performed by STATA (14.0), data were calculated by the robust error meta-regression model (REMR), and nonlinear dose-effect curves were plotted by the restricted cubic spline method (RCS). 29 papers were chosen from the 1,475 literatures that fit the criteria and were included in the dose-response meta-analysis. There were 6,079 geese included in the sample. The following production performance indices included average daily gain (ADG), average daily feed intake (ADFI), feed-to-gain ratio (F/G), dressed percentage, percentage of half-eviscerated yield, percentage of eviscerated yield, percentage of breast muscle, percentage of leg muscle and percentage of abdominal fat. The Egger test assessed publication bias, while sensitivity analysis was used to examine the heterogeneity. The verified results are consistent and reliable. The results indicated that for each group, the optimal dietary metabolizable energy level was about 13 to 13.5MJ/kg for medium-sized geese aged 0 to 4 weeks, 12 to 13MJ/kg for medium-sized geese aged above 5 weeks, 12.5 to 13MJ/kg for small-sized geese aged 0 to 4 weeks, and 13 to 13.5MJ/kg for mall-sized geese over 5 weeks of age. Future research should be conducted on related diets of large-sized geese, small-sized geese, and higher metabolizable energy levels.

This paper presents a parametric study of the multistorey hydro-powered pump, known as "Bunyip," which has demonstrated significant potential in contributing to rural regions. The study aims to understand the underlying physics of the system and enhance its hydraulic performance. A transient three-dimensional model using the commercial Computational Fluid Dynamics (CFD) tool Ansys-Fluent is utilized to gain insights into the fundamental flow mechanics, operational efficiency, standard capacity, and relative delivery. The investigation involves an initial assessment of performance for three Bunyip devices based on manufacturing data. Parametric analysis is conducted, and a parametric dataset is generated through meticulous application and numerical modelling. The CFD results are validated against experimental data. Three design configurations are considered, and 58 sets of varied input parameters are examined. The best design configuration is evaluated against five cases of conventional hydro-power pump systems. The results indicate that a smaller diameter of the pressure chamber and a higher supply head lead to higher pressure, achieving a target head of 3 m with 15% efficiency and a flowrate of 11.82 l/min.

: This work introduces the instrument design of the medium energy proton detector (MEPD, detection range: 30keV-5MeV) mounted on the Chinese Fengyun-4B (FY-4B) satellite. Compared with the similar detector on the Fengyun-3E (FY-3E) satellite, the instrument has undergone significant changes due to the different orbital radiation environment and solar lighting conditions. Based on the calculation of radiation model AP8, the geometry factor is reduced to 0.002 cm2sr, while the MEPD on FY-3E satellite is 0.005 cm2sr. Another difference is that sensors in some directions is exposed to direct sunlight for 80 minutes every day on this orbit, depending on the attitude angle of the satellite, which is much worse than that on FY-3E satellite. According to the calculation results of permeability of photons through different materials, a 100 nm thickness nickel film is added in front of sensors in order to eliminate light pollution completely. The experiment on the solar simulator shows that the measure is effective and the detector has no error counts when the solar irradiance coefficient is 1.0. In addition, Geant4 software is applied to simulate particle transportation process under complete machine condition so that to check the contamination of electrons on sensors among all directions after magnetic deflection. Data obtained in orbit shows that the instrument works properly, and the data is in good agreement with the AP8 model. The observations of the MEPD on board the FY-4B satellite can provide important support for the safety of the spacecraft and the theoretical research related to space weather.

Offshore Wind Turbines (OWT) with increasingly higher energy output are being developed to meet energy demand, posing challenges for their foundation design. Several foundation types are used to support these turbines with monopiles (MP) accounting for 80% of the installed capacity. In this study, three-dimensional (3D) nonlinear finite element models (FEM) were employed to investigate the behaviour of monopile foundation supporting a 5MW wind turbine when subjected to lateral loading. Results indicate that the MP behavior depending on the pile length to diameter (L/D) ratio and the soil shear strength. Inspection of bending moment profiles at the lateral ultimate capacity indicated the monopiles can behave in flexible manner even with low L/D ratio. The L/D ratio affected the MP normalized lateral ultimate capacity at varying degrees and the biggest effect was for soft clays, amounting to around 5 folds increase for L/D values of 3.33 to 13.33. Lesser effects were found for stiff clays.

Traditional lithium-ion batteries cannot meet the high flexibility and bendability requirements of modern flexible electronic devices due to the limitations of their electrode materials. Therefore, the development of high-performance flexible energy storage devices is of great significance for promoting flexible electronics. In recent years, one-dimensional flexible fiber lithium-ion batteries have been rapidly developed due to the advantages of high flexibility and bendability. However, it is still a big challenge to realize 1D flexible fiber lithium-ion batteries with excellent electro-chemical properties and good mechanical performance. In this work, a reduced graphene ox-ide-based printing ink is proposed to fabricate flexible Li4Ti5O12/graphene fiber electrodes through a 3D printing assembly strategy. It is noteworthy that the green reducing agent vitamin C was used to reduce graphene oxide in one step, which improved the conductivity of the fiber elec-trode. Furthermore, a 3D conductive network is constructed inside the fiber electrodes due to the high specific surface area of reduced graphene oxide, which enhances the electronic conductivity and ion mobility. The fiber electrode not only has good mechanical performance, but also has ex-cellent electrochemical properties. Equally important, the method is simple and efficient, and the working environment is flexible. It can precisely control the shape, size and structure of the one-dimensional fiber flexible electrode, which is of great significance for the development of fu-ture flexible electronic devices.

Copper-nitride (Cu3N) material is attracting much attention as a potential next-generation thin-film solar-light absorber. In this work, polycrystalline Cu3N thin films were prepared using reactive-RF-magnetron sputtering, at room temperature,onto glass and silicon substrates. The optical properties of the Cu3N thin layers were studied by spectroscopic ellipsometry and transmission, to achieve a low-cost absorber material to replace conventional silicon. The reactive-RF-sputtered Cu3N films were also investigated by FIB-SEM microscopy and FTIR spectroscopy.

The European Union's current pressure on Member States to adopt the Green Deal and the Fit for 55 package is leading to an accelerated drive to put in place measures to meet the 2030 climate targets. At the same time, many discussions at international bilateral meetings of EU country representatives raise the question of the realism of setting climate targets and therefore the ability to meet these commitments. The results elaborated in this analytical study offer a realistic picture of the possibilities of meeting strategic climate targets using the example of the use of forest dendromass for the ability to achieve a 22% share of renewable energy sources (RES) in gross final energy consumption by 2030 in the Czech Republic. The study points out that at present the use of forest dendromass from primary pro-duction is at its maximum and meeting the climate targets for increasing the share of RES in the energy mix represents a major problem in the long term. The findings published in this study also point to the objective threat of increased use of dendrmass in the energy sector to the maintenance of sustainable forest management and the preservation of forest quality.

Forest biomass is one of the most significant renewable energy sources in the Czech Republic. Recently, Czech forests have been under attack by spruce bark beetles, threatening the stability of biomass supply also for energy purposes. The goal of this paper is to uncover the impact of four different biomass development scenarios and three policies on the energy system and to evaluate the contribution of biomass to decarbonization efforts. We use the TIMES-CZ energy system optimization model to perform the analyses. We provide a crucial extension of this model by regionalizing it into NUTS3 +1 regions. Our main findings are that under the expected price of various types of biomass and their transportation cost, energy system would still exploit available biomass almost entirely throughout the period under review; subsidizing the production cost of the most expensive type of biomass for households would help utilize the full potential of biomass; and power and heat sector and industry would compete for biomass consumption against the residential sector.

Due to urban warming, energy demand for cooling buildings is rising. The current study used CitySim to estimate the cooling energy requirements for 40 buildings in Downtown, Dubai using high-resolution climate data from weather research and forecasting (WRF) coupled with single layer urban canopy model (SLUCM). Simulating the four mitigation scenarios allowed for the examination of the reduction in cooling load caused by the addition of greenery at a rate ranging from 25% to 100%. The insulated building's cooling demand reduced by a maximum of 13.89% under 100% GI (M4). Scenario M4 resulted in a reduction of 4.6 kWh/m2 and 3.1 kWh/m2 for the non-insulated and insulated low-rise residential buildings, respectively, while the high-rise buildings saw a reduction of 3.09-4.91 kWh/m2 for the non-insulated and 2.07-3.09 kWh/m2 for insulated buildings. This study offered a potential remedy to deal with the problem of urban heating in subtropical environments.

Although buildings constitute 35% of global energy use and 38% of carbon emissions from energy, the amount of energy and energy-related carbon emissions are increasing rapidly. On the other hand, non-renewable usable energy resources are decreasing on the contrary. New buildings are being built due to the increasing population and the existing building stock not meeting the needs or losing its lifespan. Some of the existing building stock is demolished and renewed for structural reasons and some for reasons such as usage performance. It is possible to reduce both energy consumption and greenhouse gas emissions with strategic energy uses in existing building stocks. There are various techniques to measure the maximum performance of sustainable and energy-efficient use of existing building stocks with which changes. Building Information Modeling (BIM) technology is one of these techniques that provides wide opportunities to users in recent years, and it is almost a virtual laboratory of structures. Building stocks can be modeled with BIM, and alternative shell and system suggestions can be used to measure how building performance has changed and to achieve the best results. In this research study, improvement scenarios that optimize energy use in existing building stocks are investigated on a sample residential building by using the virtual laboratory facilities of BIM. After measuring the current energy performance of the existing building with BIM tools, 192 alternative results were obtained with 6 variables (external walls, roof, insulation layers, transparent surface materials, lighting, and photovoltaic panels). The obtained alternatives were compared with the current state of the existing building. The material expenditures and amortization periods required for these alternative scenarios are also calculated. The results obtained were evaluated according to annual / lifetime energy consumption, fuel, electricity, initial investment costs, energy use intensity, and carbon emission amounts. With the optimization of the current situation of the sample building, annual fuel consumption decreased by 61% and electricity consumption by 64%. The amortization period of the optimum improvement was determined as 12 years.

The thermal properties of a building envelope are key indicators of the energy performance of the building. Therefore, methods are needed to determine quantities like U-values or heat capacitance in a fast, reliable way and with as little impact on the use of the building as possible. In this paper a technique is proposed that relies on a simplified electrical analogical model of building envelope components which can cover their dynamic thermal behavior. The parameters of this model are optimized to produce the best fit between simulated and measured outside surface temperatures. As the temperatures can be measured remotely with an infrared camera this approach requires significantly less installation effort and intrusion in the building than other methods. At the same time, a single measurement provides data for a large range of locations on a facade or a roof. The paper describes the method and a first experimental implementation of it. The experiment indicates that this method has the potential to produce results which have an accuracy that is comparable to standardized reference methods.

Daniel Yergin’s “The New Map: Energy, Climate, and the Clash of Nations” is a remarkable and groundbreaking work that addresses the ever-changing global energy landscape and its profound geopolitical implications. In this modest book review, we aim to offer a fresh perspective by re-examining the core issues from the standpoint of political geography. The aim of this article is twofold: to enrich the existing literature on political geography and to provide valuable insights to students of geography to broaden their knowledge in this field.

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.

Solar energy is a rapidly growing sector, and solar farms are playing an increasingly important role in meeting the world's energy needs. However, as the size and complexity of these farms increase, so do the challenges associated with managing them efficiently. This article presents a comprehensive analysis of the fundamental parameters that underpin solar energy systems. Focusing on the latest research, we examine the challenges and opportunities intrinsic to the implementation of solar energy systems, paying particular attention to the various parameters that contribute to their performance. These parameters encompass a range of factors such as thermal performance, atmospheric boundary layer, solar energy meteorology, heat islands, cloud influences, agrivoltaic systems, shading factors, and surface energy budget. The review underscores the importance of considering a diverse array of parameters when developing solar energy systems to optimize their efficiency and effectiveness. Ultimately, by unraveling these challenges and opportunities, we can work towards creating more sustainable and reliable renewable energy sources and reducing our dependence on non-renewable alternatives.

We investigated new anodic coloring materials that are used as ion storage layers in complementary energy storage electrochromic devices (ESECDs) to enhance their electrochromic storage performance. In this study, we fabricated counter electrodes (ion storage layers) using IrO2 doping NiO (Ir: NiO) film through cathodic arc plasma (CAP) with varying surface charge capacities. We investigated the influence of MoO3-doped WO3 (Mo: WO3) film by various Ar/O2 gas flow ratios (1/4, 1/5, and 1/6). The ESECDs used in the demonstration were 10×10 cm2 in size. They achieved optical transmittance modulation of Ir: NiO- ESECDs (glass/ITO/ Mo: WO3/gel-polymer electrolytes/ Ir: NiO /ITO/glass), ΔT=53.3% (from Tbleaching (66.6%) to Tcoloration (13.1%)). The ESECDs had a quick coloration time of 3.58 seconds, a rapid bleaching time of 1.24 seconds, and high cycling durability. It remained at 45% transmittance modulation even after 3000 cycles. New anodic materials can provide an alternative to traditional active materials for bi-functional electrochromic batteries.

A micro energy harvesting device proposed in the literature, is numerically studied. It consists of two bluff bodies in a micro-channel and a flexible diaphragm at its upper wall. Vortex shedding behind bodies induces pressure fluctuation causing vibration of the diaphragm that converts me-chanical energy to electrical by means of a piezoelectric membrane. Research on enhancing vortex shedding is justified due to the low power output of the device. Amplitude and frequency of un-steady pressure fluctuation on the diaphragm center are numerically predicted. Vortex shedding severity is mainly assessed in terms of pressure amplitude. The CFD model set-up is described in detail and appropriate metrics to assess energy harvesting potential are defined. Several cases are simulated to study the effect of inlet Reynolds number and channel blockage ratio on the prospec-tive performance of the device. Furthermore, the critical blockage ratio leading to vortex shedding suppression is sought. Higher inlet velocity for a constant blockage ratio is found to enhance vor-tex shedding and pressure drop. Great blockage ratio values, but lower than the critical one, seem to provide great pressure amplitudes in the expense of moderate pressure drop. There is evidence that the field is fruitful for research and relevant directions are provided.

In this study, a new methodology based on the circuit approach is employed to obtain renewable electric energy. Although a voltage source and a current source generate voltage and current, respectively, they work only when they receive electric power, which is the product of voltage and current. However, this paper proposes a circuit with a voltage source, a current source and a super-condenser connected in series, in which the voltage source provides voltage for the current source and the current source provides current for the voltage source. Resultantly, electric power is generated both at the voltage and current sources, and the energy (i.e., the electric power) from the current source is converted to the charging energy in the super-condenser. Herein, we describe the method for charging the super-condenser using a voltage source and a current source. To confirm the abovementioned concept, we conducted experiments, and the energy was successfully produced, with high reproducibility. Finally, the brief mechanism for the energy conversion, a schematic method for reducing the capacitances of stored batteries, and the significance of this study are described.

In this work, we compiled our research on lanthanide-based luminescent materials, prepared down-shifter layers, and studied their effect on photovoltaic (PV) mini-modules. The compounds we have prepared (C1-C17), with formulas [Eu2(phen)2(bz)6] (C1), [Eu2(bphen)2(bz)6] (C2), [Eu(tta)3bphen] (C3), [Eu(bta)3pyz-phen] (C4), [Eu(tta)3pyz-phen] (C5), [Eu(bta)3me-phen] (C6), [Er(bta)3me-phen] (C7), [Yb(bta)3me-phen] (C8), [Gd(bta)3me-phen] (C9), [Yb(bta)3pyz-phen] (C10), [Er(tta)3pyz-phen] (C11), [Eu2(bz)4(tta)2(phen)2] (C12), [Gd2(bz)4(tta)2(phen)2] (C13), [EuTb(bz)4(tta)2(phen)2] (C14), [EuGd(bz)4(tta)2(phen)2] (C15), [Eu1.2Gd0.8(bz)4(tta)2(phen)2] (C16) and [Eu1.6Gd0.4(bz)4(tta)2(phen)2] (C17), can be grouped into three families based on their composition: Series C1–6 were synthesized using Eu3+ ions and phenanthroline derivatives as the neutral ligands, and fluorinated β-diketonates as the anionic ligands. Complexes C7–11 were prepared with ligands similar to those of compounds C1–6 but were synthesized with Er3+, Yb3+, or Gd3+ ions. Series C12–17 exhibit the general formula [M1M2(bz)4(tta)2(phen)2], where M1 and M2 can be Eu3+, Gd3+, or Tb3+ ions, and the ligands are benzoate (bz–), 2-thenoyltrifluoroacetone (tta–) and 1,10–phenanthroline (phen). All compounds were characterized using X-ray techniques, and their photoluminescent properties were studied. We then examined their impact on the EQE (External Quantum Efficiency) of PV mini-modules and their durability in a climate chamber when embedded in PMMA and EVA films. This review emphasizes the methodology employed and the key findings, including enhanced mini-module efficiency. Additionally, we present promising results on the application of compound C6 in a bifacial solar cell.

The binding affinity of trastuzumab and pertuzumab to HER2 has been studied using both experimental and in-silico methods. The experiments were conducted using the antibodies in their complete IgG form, as used in clinical therapy, and the extracellular domain of the HER2 protein in solution. This approach provides a precise, reproducible, and reliable view of the interaction between them in physiological conditions. Dynamic light scattering and size exclusion chromatography coupled with tetra detection were utilized to characterize the protein complexes, measure their concentrations, and calculate the equilibrium free binding energy, ΔGbind. In addition, PRODIGY, a QSAR-like model with excellent predictive ability, was employed to obtain in-silico ΔGbind estimations. The results obtained indicate that pertuzumab exhibits a slightly higher binding affinity to HER2 than trastuzumab. The difference in binding affinity was explained based on the contribution of the different interfacial contact (IC) descriptors to the ΔGbind value estimated by the PRODIGY model. Furthermore, experiments revealed that the pertuzumab IgG antibody binds preferentially to two HER2 proteins, one per Fab fragment, while trastuzumab mainly forms a monovalent complex. This finding was interpreted based on a geometrical model that identified steric crowding in the trastuzumab-HER2 complex as compared to the pertuzumab-HER2 complex.

Objective: To evaluate two different DECT postprocessing protocols for detection of MSU deposits in foot tendons of cadavers with verification by polarizing light microscopy as gold standard.Material and Methods: A total of 40 embalmed cadavers (15 male; 25 female; median age, 82 years; mean, 80 years; range, 52 - 99; SD ± 10.9) underwent DECT to assess MSU deposits in foot tendons.Two postprocessing DECT protocols with different Hounsfield unit (HU) thresholds 150/500 (=established) versus 120/500 (= modified) HU were applied to dual source acquisition with 80 kV for tube A and 140 kV for tube B.Six fresh cadavers (4 male; 2 female; median age, 78; mean, 78,5; range 61 - 95 ) were examined by DECT. Tendon dissection of 2/6 fresh cadavers with positive DECT 120 and negative DECT 150 studies were used to verify MSU deposits by polarizing light microscopy.Results: The tibialis anterior tendon was found positive in 57.5%/100% (DECT 150/120), peroneus tendon in 35%/100%, achilles tendon in 25%/90%, flexor halluces longus tendon in 10%/100%, and tibialis posterior tendon in 12.5%/97.5%. DECT 120 resulted in increased tendon MSU deposit detection, when DECT 150 was negative, with an overall agreement between DECT 150 and DECT 120 of 80 % (P = 0.013). Polarizing light microscope confirmed MSU deposits detected only by DECT 120 in tibialis anterior, achilles, flexor halluces longus and peroneal tendons.Conclusion: The DECT 120 protocol showed a higher sensitivity when compared to DECT 150.

Compared to other 2D materials, MBenes are at an early stage in both experimental and theoretical approaches. However, the wide range of possible 2D structures leads to novel and challenging properties and their consequent applications. From all the possible stoichiometries, we have performed a theoretical study of orthorhombic and hexagonal M2B2 MBenes in the framework of the Density Functional Theory. We have found that both symmetries of Cr2B2, Fe2B2, and Zr2B2 show a metallic behavior and could be grown under certain conditions, as they are demonstrated to be dynamically stable. Moreover, the values of the magnetic moment, in specific ferromagnetic cases exceeding 2.5 μB/M2B2, make them suitable as robust 2D magnets. All our findings represent an important step in the understanding of MBenes and open several windows to future research in fields like energy conversion and storage, sensing, catalysis, biochemistry, or nanotechnology, among others.

We derive a quantum speed limit for unitary evolution for the case of mixed quantum states using the stronger uncertainty relation for mixed quantum states. This bound can be optimized over different choices of Hermitian operators for a better bound. We illustrate this with some examples and show its better performance with respect to three existing bounds for mixed quantum states.

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.

In this paper, a fuzzy logic-based energy management system and multi-port quasi-z-source converter are proposed that utilizes hybrid renewable energy sources. The system ensures that each energy source module can be used individually by employing fuzzy logic to define power modes. This approach also helps prevent switching losses resulting from extra switching of the source modules. Also, the proposed energy management does not have a mathematical model, so applicability is simple and it is suitable for different multiple input topologies. The Mamdani fuzzy inference system can be designed to capture the nonlinear behavior of the system because of the linguistic rules. Moreover, by adopting the quasi-z-source network to the end of the multi-port converter, the switching losses of the multi-port modules have been significantly reduced. The simulation results are obtained using MATLAB Simulink, and the experimental results are obtained by connecting the circuit to MATLAB Simulink via an Arduino Due.

For thermoelectric materials study and development, it is very important to measure the electrical power and efficiency of a thermoelectric generator (TEG). In this study, thermoelectric properties such as electrical conductivity, Seebeck coefficient, and thermal conductivity of cement composites with graphene nanoplatelets and metallic oxides (Fe2O3, ZnO, MnO2) are measured and subsequently used to figure out the output electrical power and efficiency. A maximum of 1.5 W power per square meter for a temperature difference of about 50 °C can be estimated using GnP-ZnO added cement composites. This paper also talks about how to make a cement composite-based structural TEG module to enhance the total output voltage, power, and efficiency of the system.

Pakistan relies mostly on fossil fuel for fulfilling its energy demand which is expensive as 11 well as not friendly for the environment. The need of the hour is to shift from fossil fuels to renew-12 able energy resources like geothermal, wind, solar etc. to cater for global warming issues. Pakistan 13 has a lot of potential geothermal sites because of several fault lines and hot springs. A sound 14 knowledge of ground temperature is essential to use geothermal energy, which is obtained by drill-15 ing boreholes and putting sensors making it an expensive procedure. Thus, to avoid huge cost for 16 drilling bore holes, particularly for ground temperature analysis, a numerical approach has been 17 considered for determining ground temperature. Furthermore, correlation charts between air and 18 ground temperatures have been developed as there were no proper studies on the ground temper-19 ature of Pakistan. Then, with the help of a boreholes drilled in National University of Sciences and 20 Technology Islamabad Pakistan, the actual ground and numerically calculated temperatures have 21 been compared which shows an error margin in the range between 0.27% for higher depths to 7.3% 22 near surface. Thus, it is shown that the proposed method is easy to implement and better than large 23 scale testing methods for the depths at which geothermal energy is extracted.

The reliability of Underwater Wireless Sensor Networks (UWSNs) is measured in terms of energy consumption (EC), end-to-end delay(E2E) and packet delivery ratio (PDR). The adverse effects of channel may cause data loss. Reducing delay up to possible extend improves the reliability of the network, also increasing the number of nodes in a particular network increase reliability. Besides, increasing the number of nodes improve reliability but also increase power consumption. In order to overcome these shortcomings, the two routing protocols are proposed in this paper, namely Delay and Reliability Aware Routing (DRAR) protocol and Cooperative Delay and Reliability Aware Routing (Co-DRAR) protocol for UWSNs. In DRAR protocol, network is divided into two equal regions where two sink nodes(SNs) are positioned at upper region of the network and two SNs are placed at the mid region of the network. The protocol choose the relay node based on residual energy (RE), distance and Bit Error Rate (BER). These parameters protect the data packets from corruption and also provide stable path (where nodes remain active for longer period and do not die quickly). The protocol uses single link and may get worse sometimes while changing channel circumstances. To address this problem, cooperative routing scheme is added to DRAR protocol in order to developed its enhanced version known as Co-DRAR protocol. The protocol works by allowing the destination to receive multiple copies of data packets in order to decide the quality of packets. The proposed protocols DRAR and Co-DRAR perform routing irrespective to geographical position of sensors nodes conversely to the some of conventional routing protocols that's way our propose protocol better perform than the well-known protocol i.e. Depth base routing (DBR) in terms of EC, E2E, PDR, dead nodes, packet drop ratio and number of alive nodes (ANs).

Oscillating Sequential Universes Model (OSUM), an innovative cosmological model describing the universe's evolution through the interplay of dark energy and dark matter is presented in this study. The model proposes a series of expansions and contractions driven by dark energy and dark matter interactions, challenging the conventional view of a singular Big Bang event followed by continuous expansion. The necessity for model refinements, incorporating new observational constraints, reassessing dark energy-dark matter interaction assumptions, and investigating alternative mathematical formulations for the oscillation mechanism have been discussed in this study. The OSUM offers a comprehensive framework for future research and potential discoveries in astrophysics, cosmology, and fundamental physics, raising new questions and challenging prevailing assumptions about the cosmos.

Energy storage systems (ESSs) are the key elements to improve the operation of power systems. On the other hand, these elements challenge the power system planners. The difficulties arise as a result of the ESSs' economic and technological features. The cycle life of ESSs is a critical aspect that influences the choices made during expansion planning processes. In this manuscript, we have focused on a new model for the expansion planning of ESSs considering the impacts of technical properties, such as the cycle life and depth of discharge. For this purpose, the proposed model consists of the hourly operation planning of ESSs in the sample days of year. A new indicator is proposed to determine the daily charging/discharging cycles of ESSs. Numerical results show the ability of the proposed model to determine the optimal technology and capacity of ESSs.

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.

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.

The digital era offers many opportunities to the wind energy industry and research community. Digitalisation is one of the key drivers for reducing costs and risks over the whole wind energy project life cycle. One of the largest challenges in successfully implementing digitalisation is the lack of data sharing and collaboration between organisations in the sector. In order to overcome this challenge, a new collaboration method called WeDoWind was developed in recent work. The main innovation of this method is the way it creates tangible incentives to motivate and empower different types of people from all over the world to actually share data and knowledge in practice. In this present paper, the challenges related to comparing and evaluating different SCADA data based wind turbine fault detection models are investigated by carrying out a new case study, the "WinJi Gearbox Fault Detection Challenge", based on the WeDoWind Method. Six new solutions were submitted to the challenge, and a comparison and evaluation of the results show that, in general, some of the approaches (Particle Swarm Optimisation algorithm for constructing health indicators, performance monitoring using Deep Neural Networks, Combined Ward Hierarchical Clustering and Novelty Detection with Local Outlier Factor and Time-to-failure prediction using Random Forest Regression) appear to have a high potential to reach the goals of the Challenge. However, there are a number of concrete things that would have to have been done by the Challenge providers and the Challenge moderators in order to ensure success. This includes enabling access to more details of the different failure types, access to multiple data sets from more wind turbines experiencing gearbox failure, provision of a model or rule relating fault detection times or a remaining useful lifetime to the estimated costs for repairs, replacements and inspections, provision of a clear strategy for training and test periods in advance, as well as provision of a pre-defined template or requirements for the results. These learning outcomes are used directly to define a set of best practice data sharing guidelines for wind turbine fault detection model evaluation. They can be used by the sector in order to improve model evaluation and data sharing in the future.

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.

SARS-CoV-2 resembles the ancient mythical creature Hydra. Just like with the Hydra, when one head is cut, it is followed by appearance of two more heads, suppression of one SARS-CoV-2 variant causes appearance of newer variants. Unlike Hydra that grows identical heads, newer SARS-CoV-2 variants are usually more infective, which can be observed as time evolution of the virus at hand, which occurs through acquisition of mutations during time. The appearance of new variants is followed by appearance of new COVID-19 pandemic waves. With the appearance of new pandemic waves and determining of sequences, in the scientific community and general public the question is always raised of whether the new variant will be more virulent and more pathogenic. The two variants characterized in this paper, BA.5.2 and BF.7, have caused a pandemic wave during the late 2022. This paper gives full chemical and thermodynamic characterization of the BA.5.2 and BF.7 variants of SARS-CoV-2. Having in mind that Gibbs energy of binding and biosynthesis represent the driving forces for the viral life cycle, based on the calculated thermodynamic properties we can conclude that the newer variants are more infective than earlier ones, but that their pathogenicity has not changed.

Luminophores featuring thermally activated delayed fluorescence (TADF luminophores) are the workhorse of the third- and fourth-generation OLEDs. While these compounds had usually been used as dopants embedded in the host, non-doped TADF OLEDs have recently shown significant progress as well reaching the performance comparable to the host-dopant ones. For efficient operation of the non-doped OLEDs, charge transport in neat films and single crystals of TADF luminophores is important; however, this issue was nearly unexplored theoretically. In the current study, we calculated charge mobilities in four TADF single crystals, which have different molecular packing motifs. Specifically, in one of them both donor and acceptor moieties form uniform π-stacks, while in the others donors (acceptors) show alternating lateral shifts along the stacks; the difference in molecular packing results in the difference of transfer integral between the molecules. Reorganization energies differ as well up to four times for the studied crystals. As a result, charge mobilities vary from 0.001 to ~0.3 cm2/(V∙s), the largest being predicted for the crystal of the luminophore consisting of rigid donor and acceptor. We anticipate that the results obtained can be useful for the design of TADF luminophores for non-doped OLEDs, OLETs and other organic light-emitting devices.

Solar energy (SE) is essential for decarbonization of our economy and for energetic transition. Solar energy can be a sustainable economic activity as long as a balance is struck between the benefits it brings to climate change mitigation and the damage it can cause to biodiversity and ecosystems. Here we study this balance in an area with high biodiversity under pressure for installation of numerous photovoltaic plants (PPs). Our results show that developers give priority to the cheapest land close to connection points, while other values (e.g., environmental, landscape) are secondary. The regulatory process carried out by the Administration does not ensure the preservation of natural values, as several PPs with a high impact on important conservation areas have been approved. Experts' allegations provide quality information to the Administration to evaluate and demand changes to the projects presented. Such demands show that companies are willing to relocate plants to land occupied by olive groves. In this way, greater efficiency is achieved in land occupation, as well as shorter evacuation lines, water savings and less environmental impact. Prior strategic territorial planning could have avoided the impact of PPs already built, made the deployment of new PPs compatible with biodiversity conservation, and contributed to improving the management of key resources, such as subway aquifers. The proposed regulatory changes to the environmental assessment procedure (exclusion of renewables and public participation from the procedure) are detrimental, as they will make SE unable to meet the requirements of the Taxonomy Regulation.

In electric circuits, energy is delivered by electromagnetic fields through the space, as suggested by Kraus and Carver. They provide insights by showing electric/magnetic fields and Poynting vector directions around a DC circuit. In this work, the energy flow mechanism by Kraus and Carver is further studied theoretically for arbitrary terminal potentials of a DC power source.

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.

A Shape Memory Alloy (SMA) enabled Overtopping Wave Energy Converter (OWEC) that maximizes its overtopping discharge, and thus energy output under different wave conditions is presented. Among all the parameters affecting the overtopping discharge rate, the crest freeboard height is the most influential one to control the overtopping discharge rate and the stored overtopping volume behind it. Currently, all the OWEC crest freeboard heights are fixed by design to maximize the discharge rate on one particular sea state. In the present study, we show that the SMA can adjust the crest freeboard height through a control system based on the sea state and achieve an optimal overtopping discharge rate. A scaled OWEC model is built in the lab with its crest freeboard height controlled by springs made of SMA. The length (and thus tension) of the springs is controlled by temperature changes by changing the passing current through the springs. By adjusting the length of the springs based on the incoming wave condition, we adjust the freeboard to an optimal height known to generate a maximum overtopping discharge rate for energy conversion. This smart material-enabled design can maximize the overtopping discharge and thus the output power of the OWEC under various wave conditions. Furthermore, the simplicity of using SMA springs as the actuator leads to the minimum number of moving mechanical parts, which can remarkably decrease maintenance costs. As the proof of concept, two types of tests are conducted in the laboratory using the same OWEC model under several random wave trains generated from spectra with different significant wave heights - one type with a fixed crest freeboard height and the other type featuring the adjustable crest freeboard height controlled by the springs. The substantial increase of harvested output power in the OWEC with the adjustable crest freeboard height may pave the way for more efficient wave energy conversion systems.

With increasing constraints on energy and resource markets and the non-decreasing trend in energy demand, the need for relevant clean energy generation and storage solutions is growing and is gradually reaching the individual home. But small-scale energy storage is still an expensive investment in 2022 and the risk/reward ratio is not yet attractive enough for individual homeowners. One solution is for homeowners not to store excess clean energy individually but to produce hydrogen for mutual use. In this paper a collective production of hydrogen for a daily filling of a bus is considered. Following our previous work on the subject, the investigation consists of finding an optimal buy/sell rule to the grid, and the use of the energy with an additional objective: mobility. The dominant technique in the energy community is reinforcement learning, which is however difficult to use when the learning data is limited as in our study. We chose a less data-intensive and yet technically well-documented approach. Our results show that rulebooks, different but more interesting than the usual robust rule, exist and can be cost-effective. But they require fine-tuning as to not deteriorate system performance. In some cases, it is worth missing the H2 production requirement in exchange for higher economic performance.

The environmental impact and associated health issues have been seen as a significant global challenge. Efforts have been made to make solar cookers efficient to reduce the health risk and environmental impact of traditional cooking energy supplies used in rural areas. The solar cookers effectiveness for cooking purposes must be assessed in a specific area before installation. In essence, this paper assesses the experimental efficiency of German Scheffler, small mirror pieces, and aluminum foil based solar cookers. The solar cookers performances are evaluated at international standards by analyzing the figure of merits such as standard cooking power, sensible heating time, and exergy efficiency by using 1.7652 kg water and 1-liter oil as a heating material. The regression analysis is also performed to observe experimental data compliance with regression line. The time required to attain a water temperature of 95˚C by German Scheffler and small mirror pieces is 25 min and 1 hour with their exergy efficiency of 48.51% and 19.16% respectively, while the aluminum foil solar cooker achieves maximum water temperature of 74˚C within 2 hours and 5 minutes with 13.47% exergy efficiency. Similarly, the highest oil temperature of 275˚C is observed for the German Scheffler solar cooker. From experimental and regression results, it is revealed that German Scheffler possesses more cooking power relative to other solar cookers and their performances are highly dependent on following factors such as solar radiations, ambient temperature, environment (dust particles concentration and wind speed), radiation reflective material, aperture area, and heat losses respectively.

Gwadar is essential for Pakistan's financial stability. The third deep-water port in Pakistan, Gwadar, plays a significant part in trade between the Gulf countries, Africa, China, United Arab Emirates, and Cordillera Administrative Region. However, the load Shedding of 12-16 hours in Gwadar is the most concerning issue. Pakistan imports 70 MW of electricity from Iran. The wind and solar system are already installed but for a limited residential area. In Gwadar, there are enough renewable energy resources that can be utilized for electricity generation. In this context, a Techno and Economic Analysis is performed using the Hybrid Optimization Model for Multiple Energy Resources (HOMER) Pro. Two models are considered for this study. Model-1 includes PV/Wind Turbine/ and Battery while Model-2 consists of PV/Wind Turbine/Converter and Grid. The yearly energy generated by Model-1 and Model-2 is 57.37 GWh and 81.5 GWh, respectively. The levelized cost of electricity (LCOE) for Model-1 and Model-2 is respectively $0.401/kWh and $0.0347/kWh. It is shown that the simple payback of Model-1 is of 6.70 years, and the simple payback of Model-2 is 7.77 years. Due to the high LCOE of Model-1, its payback year is lesser than model-2. All of these facts indicate that Model 2 is the most optimal solution.

Lord Kelvin believed that the electromagnetic aether must also generate gravity. Presently, we have no methods to determine the density of the electromagnetic aether, or we say the $\Omega(1)$ substratum. Thus, we also suppose that vacuum is filled with another kind of continuously distributed substance, which may be called the $\Omega(2)$ substratum. Based on a theorem of V. Fock on the mass tensor of a fluid, the contravariant energy-momentum tensors of the $\Omega(1)$ and $\Omega(2)$ substrata are established. Quasi-static solutions of the gravitational field equations in vacuum are obtained. Based on an assumption, relationships between the contravariant energy-momentum tensors of the $\Omega(1)$ and $\Omega(2)$ substrata and the contravariant metric tensor are obtained. Thus, the cosmological constant is calculated theoretically. The $\Omega(1)$ and $\Omega(2)$ substrata may be a possible candidate of the dark energy. According to the theory of vacuum mechanics, only those energy-momentum tensors of discrete or continuously distributed sinks in the $\Omega(0)$ substratum are permitted to act as the source terms in the generalized Einstein's equations. Thus, the zero-point energy of electromagnetic fields is not qualified for a source term in the generalized Einstein's equations. Some people believed that all kinds of energies should act as source terms in the Einstein's equations. It may be this unwarranted belief that leads to the cosmological constant problem. The mass density of the $\Omega(1)$ and $\Omega(2)$ substrata is equivalent to that of around $3$ protons contained in a box with a volume of $1$ cubic metre.

Naltrexone (NTX) is a potent opioid antagonist with good blood-brain barrier permeability, targeting different endogenous opioid receptors, particularly the mu-opioid receptor (MOR). Therefore, it represents a promising candidate for drug development against drug addiction. However, the details of the molecular interactions of NTX and its derivatives with MOR are not fully understood, hindering ligand-based drug discovery. In the present study, taking advantage of the high-resolution X-ray crystal structure of the murine MOR (mMOR), we constructed a homology model of the human MOR (hMOR). A solvated phospholipid bilayer was built around the hMOR and submitted to microsecond (µs) molecular dynamics (MD) simulations to obtain an optimized hMOR model. NTX and its derivatives were docked into the optimized hMOR model and submitted to µs MD simulations in an aqueous membrane system. The MD simulation results were submitted to Molecular Mechanics Generalized-Born surface area (MMGBSA) binding free energy calculations and principal component analysis. Our results revealed that NTX and its derivatives showed differences in protein-ligand interactions; however, they shared contact with residues at TM2, TM3, H6, and TM7. The binding free energy and principal component analysis revealed the structural and energetic effects responsible for the higher potency of NTX compared to its derivatives.