Shared public buildings have become centers of innovation, integrating advanced technologies to meet evolving societal needs. With a heightened emphasis on occupants’ health and well-being, these buildings serve as hubs for technological convergence, facilitating seamless connectivity and intelligent data analysis and management. Within this context, environmental monitoring emerges as a foundational element, pivotal to all aspects of building management. This article provides findings from the nationally funded RE-START project, which focuses on shared public buildings, with special regard to educational and medical facilities. The project explores enhanced indoor air quality monitoring, focusing in particular on CO2 concentration that is directly correlated with occupancy, as a fundamental element for developing health and safety protocols, energy efficiency strategies, integration of smart building technologies, and data-driven energy management. The intersection of environmental monitoring, energy efficiency, security, and IoT technologies in in indoor spaces are relevant. The outcomes of the study reveal the delicate nature of all the involved components, that need to be carefully developed in an integrated manner.

In order to achieve its carbon peak and neutrality targets, a high proportion of distributed power sources are connected to the distribution network in China, which greatly increases the risk of distribution network operation. Aiming at the above problems, this paper proposes an active distribution network risk planning model based on multi-source data from carbon capture and power internet of things, and conducts exceeding testing of distribution network based on the stochastic load flow algorithm with semi-invariant and level expansion, calculates the semi-invariant of each order of node state vectors and branch current vectors, and then utilizes the Gram-Charlier level expansion to obtain the exceeding probability density function and probability distribution function of the node voltages and line powers of the distribution network. The probability density function and probability distribution function of the exceeding are obtained using the Gram-Charlier series expansion. Combined with multi-source data, the active distribution network with integrated energy system considering carbon capture is modeled. According to the risk scenario of the distribution network, the nonconvex constraints in the model are simplified by the second-order cone relaxation, and the optimal planning scheme of the distribution network is solved by combining the gurobi solver with the risk index as the first-level objective and the economic benefit as the second-level objective. The simulation results of a coupled network consisting of a 39-node distribution network and an 11-node transportation network verify the effectiveness of the proposed model.

This manuscript employs a surface stress-driven nonlocal model to explore the combined effects of long-range interaction and surface energy on higher vibration modes of functionally graded nanobeams. The nanobeam theory, based on Bernoulli-Euler kinematics, incorporates surface effects such as surface elasticity, surface residual stresses, surface density, and rotary inertia. Hamilton's principle is applied to derive the governing equation with size-dependent considerations. The main outcomes of a parametric investigation, considering four different kinematic boundary conditions (Cantilever, Simply-Supported, Clamped-Pinned, and Doubly-Clamped) while varying the nonlocal parameter and material gradient index, are presented and discussed. Additionally, the normalized natural frequencies for the second, third, fourth and fifth modes of vibrations are provided and analyzed for each case under study. The results underscore the model's effectiveness in capturing surface energy effects on the overall dynamic behavior of functionally graded Bernoulli-Euler nanobeams, offering a cost-effective approach for designing and optimizing nano-scaled structures.

The strength of laser joined metal and plastic hybrids is based purely on adhesion. Unpolar plastics like polypropylene depend solely on the mechanical adhesion while polar plastics like polyamide 6.6 develop covalent bonds with the metal. In this research the influence of different surface metallizations on the lap shear strength of laser joined hybrids was investigated. Sandblasted AISI 304 was used as base metal and reference. Aluminum and titanium coatings were deposited by the means of Arc-PVD. Polypropylene and polyamide 6.6 were utilized as polar und unpolar plastics. The lap shear strength of all hybrids with polyamide 6.6 was higher than the polypropylene samples. For all investigated variations of the laser power, scanning speed and the cohesive and adhesive failure modes, the samples joined with the sandblasted AISI 304 showed the highest lap shear strength. The reduction in lap shear strength for the coated samples was due to the increased difference in thermal conductivity between the plastics and the coating materials. This lead to increased warping and residual stresses. It can be concluded that the thermal properties of the metallization in laser joined metal and plastic hybrids has a high impact on the lap shear strength.

This review paper explores the innovative realm of transparent solar panels, investigating their properties, applications, challenges, and recent advancements. Transparent solar panels, designed to harvest solar energy while allowing visible light to pass through, have gained significant attention due to their potential to revolutionize renewable energy technologies. The paper delves into the working mechanisms of various types of transparent solar panels, including Organic Photovoltaic (OPV) panels, Dye-Sensitized Solar Cells (DSSC), Perovskite Solar Cells, and Transparent Thin-Film Silicon Solar Cells. It discusses their integration into diverse applications, such as building-integrated photovoltaics, consumer electronics, the automotive industry, and aerospace. The review identifies challenges, including low efficiency, durability concerns, production costs, and integration hurdles, that currently hinder their widespread adoption. Moreover, the paper emphasizes the transformative potential of transparent solar panels in shaping the future of renewable energy, not only as energy generators but also as aesthetically pleasing and multifunctional components of our built environment. Finally, the paper underscores the need for continued research and development efforts to enhance efficiency, improve stability, and address integration challenges, paving the way for transparent solar panels to play a central role in the transition toward a more sustainable and energy-efficient future.

As an irreplaceable ecological barrier, the ecological conservation developing area (ECDA) is vital for the integrated construction of urban and rural areas, and optimization and adjustment of industrial structure. Developing green agriculture is the foundation and guarantee for improving the rural ecological environment and meeting the increasing needs of farmers′ income. Issued by the Chinese government, No. 1 Central Document stated the necessity of promoting agricultural green development (AGD) and the related technologies in dealing with ecological pressure and resource shortages, especially for large cities like Beijing. However, few empirical studies have conducted on spatiotemporal variations of AGD in ECDA of large cities. Based on the green agricultural traits of Beijing and the accessible data, we evaluate AGD and analyze its spatial and temporal heterogeneity of Beijing ECDA by constructiing a framework with 13 indicators. The weight coefficients of AGD indicators were calculated by the projection pursuit method, with the district panel data from 2006 to 2016. The results demonstrated that energy consumption is a vital factor of green agriculture production, and agricultural output value per unit of the arable land area is the key to the green agricultural revenue. From 2006 to 2016, the AGD index of ECDA had an increasing trend till 2012, followed by a decreasing tendency. The AGD index of the northern region is higher than the southern of ECDA. The obstacle degree model was used to verify AGD limiting factors. They were poor infrastructure, slow agritourism, low labor productivity, and low resource utilization efficiency that varied by districts in ECDA. Given these findings, our study is conducive to the AGD evaluation at the district (county) level for ECDA of large cities and also provides important policy implications.

The atomic nucleus contains protons and neutrons surrounded by a structured electron cloud. Some combinations of protons and neutrons induce the nucleus to behave like a microscopic magnet, possessing a unique magnitude and orientation known as the nuclear magnetic moment (µ). When the numbers of protons and neutrons are both even then µ=0, but otherwise each nu-clide’s nuclear magnetic moment is unique. A second unique nuclear physical property relates to the nucleon binding energy (BE), which can be thought of as the energy between protons and neu-trons bound within the nucleus. The sequence of stable nuclides increases one nucleon at a time through 36Ar. The binding energy associated with the addition of each successive nucleon (∆BE) through this progression is unique. The hypothesis here is that the unique non-zero magnetic mo-ment and ∆ binding energy of each nuclide derive from its respective microscopic nuclear struc-ture, analogous to the way that the atomic physical properties of an element ultimately derive from its unique electron orbital structure. By extension, the identification of nuclear periodic pat-terns might eventually inform a theory of nuclear structure. The light, stable nuclides through 36Ar were arranged in ascending order according to atomic mass, and their nuclear magnetic mo-ments and binding energies were evaluated for periodic patterns. Fixed-period lengths from 4 through 18 nuclides per period were considered. These fixed periods, each of equal length, were stacked one upon the other and analyzed for vertical trends. The best evidence of periodicity in both µ and ∆BE converges precisely at the fixed 12-nuclide period. Implications for nuclear structure are discussed.

A major public health emergency has been created by the COVID-19 pandemic, which is brought on by the SARS-CoV-2 virus. Due to its crucial function in viral replication, the primary protease (Mpro) of the virus is a prime target for therapeutic research. In this study, we used molecular modeling and molecular dynamics simulations to examine the potential therapeutic uses of Mpro inhibitors for the treatment of COVID-19. Using induced fit docking and molecular dynamics simulations, we confirmed the top compounds after screening a library of compounds for their ability to bind to Mpro. Simulation interaction diagrams were used to investigate protein-ligand interactions, and MM-GBSA was used to determine binding energies. The Swiss ADME server was used to predict ADME properties. According to our findings, numerous substances are strong COVID-19 medication candidates since they have excellent ADME features and high binding affinities. This work serves as a foundation for additional experimental research and drug development initiatives aimed at Mpro.

In the realm of the Internet of Things (IoT), a network of sensors and actuators collaborates to fulfill specific tasks. As the demand for IoT networks continues to rise, it becomes crucial to ensure the stability of this technology and adapt it for further expansion. Through an analysis of related works including Feedback-based Optimized Fuzzy Scheduling Approach (FOFSA) algorithm, Adaptive Task Allocation Technique (ATAT) and Osmosis Load Balancing algorithm (OLB), we identify their limitations in achieving optimal energy efficiency and fast decision-making. To address these limitations, this research introduces a novel approach to enhance the processing time and energy efficiency of IoT networks. The proposed approach achieves this by efficiently allocating IoT data resources in the Mist layer during the early stages. We apply the approach to our proposed system known as the Mist-based Fuzzy Healthcare System (MFHS) that demonstrates promising potential to overcome the existing challenges and pave the way for efficient Industrial Internet of Healthcare Things (IIoHT) of the future.

A series of derivatives, involving two dithienylethene (DTE), groups, connected by several molecular linkers (bis(ethylene-1,2-dithiolato)Ni- (NiBDT), naphthalene, quasilinear oligothiophene chains) are investigated with the aid of computational quantum chemistry methods. This involves the computation of the second- and third-order nonlinear optical properties, i.e. molecular hyperpolarizabilities of the designed/selected derivatives. These properties can be efficiently controlled by DTE switches, in connection with light of appropriate frequency. We found that NiBDT, as a linker, is associated with a greater contrast, in comparison to naphthalene, between the first and second hyperpolarizabilities of the “open-open” and the “closed-closed” isomers. This is explained by invoking the low lying excited states of NiBDT. It has been found that the second hyperpolarizability can be used as an index, which follows the structural changes induced by photochromism. The two-photon absorption, which is related to the imaginary part of second hyperpolarizability, has also been investigated for the S0S1 transition. Furthermore, the intramolecular excited-state energy transfer (EET) is studied as well as the overlap between the absorption and emission spectra of the donor and acceptor groups of the molecules. The electronic coupling, VDA, between the donor and acceptor fragments, as well as the emission spectrum of the donor and the absorption spectrum of the acceptor have been computed, assuming a Förster type transfer mechanism. EET is a critical factor governing the photochromism. Two methods were used to compute VDA, one based on linear response and one based on the distributed multipole analysis (DMA); both techniques give very similar results for the dominating Coulomb contribution. For NiBDT as the linker a low VDA value has been computed. We found that VDA is affected by the molecular geometry. Our results clearly show that the linker strongly influences the communication between the open-closed DTE groups and thus, photochromism. The present computations show that full photochromism is attained in derivatives where two DTE groups are linked by a tetrathiophene chain, in agreement with experiment. The sensitivity of molecular linear and nonlinear optical properties upon photochromism can assist with the identification of the molecular isomers.

Applications for Wireless Sensor Networks (WSNs) range from monitoring the environment to automating factories. However, sustained and effective functioning is made more difficult by Sensor Nodes (SNs) limited energy supplies in which optimization is the main issue. So with the aim of increasing the lifespan by decreasing the energy consumption of WSN, Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol with Deep Learning (DL) algorithm is analyzed in this paper. LEACH is a hierarchical mechanism that elects Cluster Heads (CHs) and regularly rotates their positions in order to allocate energy use effectively by using the same amount of energy. However, Deep Learning (DL) method is used to further improve energy optimization. In many applications, the types of Deep Learning methods like Artificial Neural Networks (ANNs) have shown to be very useful. Using this method, WSNs may make more efficient decisions that reduce energy consumption. Data aggregation, duty cycling, and transmission protocols may all be optimized by Deep Learning model's ability to recognize patterns and forecast network behavior. This results in lower energy consumption, a longer lifespan for the network, and better overall performance.

Here we mathematically model black holes and the early universe following dynamics similar to RLC electrical models, focusing on their similarities at the singularity. We use this mathematically modelling to hypothesize the evolution of an expanding universe as the result of a black hole collapse followed by its evaporation. Or model consists of several steps defined by: (1) the formation of a black hole following general relativity equations; (2) growth of the black hole modelled as a resistance-capacitance-like electrical circuit; (3) expansion of space-time following the disintegration of the black hole, modelled by RLC-like dynamics. In updating this article, version 2, we will expand by presenting three additional examples related to the theory of the generalization Boltzmann's constant in curved space-time and the theory of general and especial relativity. We will calculate the critical mass to produce a black hole in the LHC, the existence of a high temperature Bose-Einstein condensate and finally we will demonstrate the existence of a tangential force to the repulsion force in the disintegration of subatomic particles. In the update of this article, version 3, we will expand to develop two examples. First, we will present the relationship between M-theory, extra dimensions with the theory of the generalization of Boltzmann's constant in curved space-time. Secondly, we will propose the idea of ​​updating the Lambda-CDM model, considering the primordial gravitational waves to correctly describe the evolution of the universe.

The paper presents the final results from the research project “Urban Abacus of Building Energy performances (Abaco Urbano Energeticodegli Edifci – AUREE)” aimed at supporting the renovation and energy efficiency enhancement of urban building heritage financed by the “Ricerca Sistema Elettrico (MISE) program”. The crux of AUREE project is a Web – GIS GeoBlog portal with customized semantic dashboards aimed at sharing information on urban built environment and promoting the participation of local stakeholders to its improvement. As the latest development of this research, a workflow integrating the AUREE portal with BIM authoring and an open source IoT platform has been implemented and applied to an experimental case study concerning a public building in Carbonia (Italy). The headquarters of the sustainable energy research center Sotacarbo was selected as case study. The presented results proved that it was possible to create an open system, which could be easily consulted by "non-expert" users as well, to make available real-time monitoring data obtained from IoT sensors measuring the energy consumption, the indoor environmental conditions and the usage profiles of public buildings. The proposed open system could also be suitable to be later used as an effective tool to support the rising “energy communities”.

A steel damper column is an energy-dissipating member that is suitable for reinforced concrete (RC) buildings and multistory housing. To assess the seismic performance of buildings with steel damper columns, the peak displacement of the whole building and the energy dissipation demand of the dampers must be evaluated. This article proposes an energy-based prediction procedure for the peak and cumulative response of an RC frame building with steel damper columns. The proposed procedure considers two energy-related seismic intensity parameters, namely the maximum momentary input energy and the total input energy. The peak displacement is predicted considering the energy balance during a half cycle of the structural response, using the maximum momentary input energy. The energy dissipation demand of the dampers is then predicted considering the energy balance during a whole response cycle using the total input energy. The local responses (e.g., peak drift, maximum plastic rotation of beams, maximum shear strain, and energy dissipation demand of dampers) are predicted using pushover analysis. Numerical analysis results for 8- and 16-story RC buildings show that the proposed prediction method achieves satisfactory accuracy.

The negative energy solutions of the Klein-Gordon and Dirac equations have been used to define the antiparticle with the positive energy from the Feynman - Stueckelberg interpretation in the standard model based on the 4-D Minkowski space with the relative time. The negative energy solutions of the Klein-Gordon and Dirac equations are used to define the antiparticles with the negative energy in the present 3-D quantized space model. Note that all the present results are based on the 4-D Euclidean space with the absolute time (t) and relative time (t_l). Then the particle with the positive energy and antiparticle with the negative energy have the 4-D P₄ = TCP = T_cP symmetry. The continuity equations are derived from the Klein-Gordon, Dirac and Schrodinger equations. The Klein-Gordon and Schrodinger equations with the potential barriers are solved. The Klein paradox is explained by using the pair production of the electron with the positive energy and positron with the negative energy under the P₄ = _TcP symmetry, The effective velocity ( c_eff=√2 " c " ) and effective energy ("Etl =" √2 E ) along the relative time axis (ctl) give the relative time momentum of "p_tl"=E_tl/c_eff =(√2 E)/(√2 c)=E/c=p_t=p_x. This indicates that the photons with the energy of E have the constant photon velocity of c and the constant photon momentum of "ptl"=E_tl/c_eff =(√2 E)/(√2 c)=E/c=p_t=p_x. For the negative energy particles, the space momentum directions are opposite to the particle velocity directions because the energy is negative. And the matter collapse to the photons at the very high particle velocity is discussed from the length expansion. It is, for the first time, proposed that the gamma ray burst is originated from the matter collapse to the photons near the black hole. Also, the wave function collapse is explained from the length expansion. The wave function collapse takes place when the measurement makes the particle velocity to be zero. It is concluded that the negative energy solutions of the Klein-Gordon and Dirac equations support the existence of the partner antimatter universe with the negative energy and negative time direction. Our matter universe has the positive energy and the positive time direction.

SARS-CoV-2 belongs to the group of RNA viruses with a pronounced tendency to mutate. Omicron BA.2.75 is a subvariant believed to be able to suppress the currently dominant BA.5. Omicron BA.2.75 is characterized by a greater infectivity compared to earlier Omicron variants. However, Gibbs energy of biosynthesis of virus particles is slightly less negative compared to those of other variants. Thus, the multiplication rate of Omicron BA.2.75 is lower than that of other variants. This leads to slower accumulation of newly formed virions and less damage to host cells, indicating evolution of SARS-CoV-2 towards decreasing pathogenicity.

The rate of technical innovation, system interconnection, and advanced communications undoubtedly boost distributed energy networks' efficiency. However, when an additional attack surface is made available, the possibility of an increase in attacks is an unavoidable result. The energy ecosystem's significant variety draws attackers with various goals, making any critical infrastructure a threat, regardless of scale. Outdated technology and other antiquated countermeasures that worked years ago cannot address the complexity of current threats. As a result, robust artificial intelligence cyber-defense solutions are more important than ever. Based on the above challenge, this paper proposes an ensemble transfer learning spiking immune system for adaptive smart grid protection. It is an innovative Artificial Immune System (AIS) that uses a swarm of Evolving Izhikevich Neural Networks (EINN) in an Ensemble architecture, which optimally integrates Transfer Learning methodologies. The effectiveness of the proposed innovative system is demonstrated experimentally in multiple complex scenarios that optimally simulate the modern energy environment. In this way, the proposed system fully automates the strategic security planning of energy networks with computational intelligence methods. It allows the complete control of the digital strategies of the potential infrastructure that frames it, thus contributing to the timely and valid decision-making during cyber-attacks.

Machine learning (ML) has found increasing use in research on energy conversion and storage technologies, in particular, so-called sustainable technologies. While often ML is used to directly optimize the parameters or phenomena of interest in the space of features, in this perspective, we focus on using ML to construct objects and methods that help in or enable the modeling of the underlying phenomena. We highlight the need for machine learning from very sparse and unevenly distributed numeric data in multidimensional spaces in these applications. After a brief introduction of some common regression-type machine learning techniques, we will focus on more advanced ML techniques which use these known methods as building blocks of more complex schemes and thereby allow working with extremely sparse data and also allow generating insight. Specifically, we will highlight the utility of using representations with sub-dimensional functions by combining the high-dimensional model representation ansatz with machine learning methods like neural networks or Gaussian process regressions in applications ranging from heterogeneous catalysis to nuclear energy.

Powder bed fusion (PBF) process is a metal additive manufacturing process which can build parts with any complexity from a wide range of metallic materials. PBF process research has predominantly focused on the impact of only a few parameters on product properties due to the lack of a systematic approach for optimizing a large set of process parameters simultaneously. The pivotal challenges regarding this process require a quantitative approach for mapping the material properties and process parameters onto the ultimate quality; this will then enable the optimization of those parameters. In this study, we propose a two-phase framework for optimizing the process parameters and developing a predictive model for 316L stainless steel material. We also discuss the correlation between process parameters -- i.e., laser specifications -- and mechanical properties and how to achieve parts with high density (> 98%) as well as better ultimate mechanical properties. In this paper, we introduce and test an innovative approach for developing AM predictive models, with a relatively low error percentage of 10.236% that are used to optimize process parameters in accordance with user or manufacturer requirements. These models use support vector regression, random forest regression, and neural network techniques. It is shown that the intelligent selection of process parameters using these models can achieve an optimized density of up to 99.31% with uniform microstructure, which improves hardness, impact strength, and other mechanical properties.

Solar power innately has issues with weather, grid demand and time of day, which for the case of concentrating solar power (CSP) can be mitigated through use of thermal energy storage. Nuclear reactors, including lead-cooled fast reactors (LFRs), can load follow, but have high fixed and low operating costs which can make this economically unattractive. We investigate potential synergies through coupling CSP and LFR together in a single supercritical CO$_2$ Brayton cycle and/or using the same thermal energy storage. Combining these cycles allows for the LFR to thermally charge the salt storage in the CSP cycle during low demand periods to be dispatched when grid demand increases. The LFR/CSP coupling into one cycle is modeled to find the preferred location of the LFR heat exchanger, CSP heat exchanger, sCO$_2$-to-salt heat exchanger (C2S), turbines, and recuperators within the supercritical CO$_2$ Brayton cycle. Three cycle configurations have been studied: two-cycle configuration, which uses CSP and LFR heat for dedicated turbocompressors, has the highest efficiencies but with less component synergies; a combined cycle with CSP and LFR heat sources in parallel is the simplest with the lowest efficiencies; and a combined cycle with separate high temperature recuperators for both the CSP and LFR is a compromise between efficiency and component synergies. Additionally, four thermal energy storage charging techniques are studied: the turbine positioned before C2S, requiring a high LFR outlet temperature for viability; the turbine after the C2S, reducing turbine inlet temperature and therefore power; the turbine parallel to the C2S producing moderate efficiency; and a dedicated circulator loop. While all configurations have pros and cons, use of a single cycle offers component synergies with limited efficiency penalty. Using a turbine in parallel with the C2S heat exchanger is feasible but results in a low charging efficiency, while a dedicated circulator loop offers flexibility and near perfect heat storage efficiency but increasing cost with additional cycle components.

The present work aims to characterize the mechanical behavior of a new composite material for the conservation and development of the vast historical and architectural heritage that is particularly vulnerable to environmental and seismic actions. The new composite consists of natural hydraulic lime (NHL) -based mortar, reinforced by sisal short fibers randomly oriented in the mortar matrix. The NHL-based mortar ensures the chemical-physical compatibility with the original feature of the historical masonry structures (mostly in stone and clay) aiming to pursue both the effectiveness and durability of the intervention. The use of vegetable fibers (i.e. the sisal one) is an exciting challenge for the construction industry since they require a lower degree of industrialization for their processing, and therefore, their costs are also low, as compared to the most common synthetic/metal fibers. Beams of sisal-composite sizing 160x40x40 mm3 with a central notch are tested in three-point bending, aiming to evaluate both their bending strength and fracture energy. Also, tensile tests and compressive tests were performed on the composite samples, while water retention test and slump test were performed on the fresh mix. Finally, the tensile tests on the Sisal strand were carried out to evaluate the tensile strength of both strand and wire. A final comparison with unreinforced mortar specimens shows that the proposed composite ensures great workability and good performances in term of ductility and strength and it can be considered a promising alternative to the classic fiber-reinforcing systems.

Structural and biochemical studies have recently revealed a range of rationally engineered nanobodies with efficient neutralizing capacity against SARS-CoV-2 virus and resilience against mutational escape. In this work, we combined atomistic simulations and conformational dynamics analysis with the ensemble-based mutational profiling of binding interactions for a diverse panel of SARS-CoV-2 spike complexes with nanobodies. Using this computational toolkit, we identified dynamic signatures and binding affinity fingerprints for the SARS-CoV-2 spike protein complexes with nanobodies Nb6 and Nb20, VHH E, a pair combination VHH E+U, a biparatopic nanobody VHH VE, and a combination of CC12.3 antibody and VHH V/W nanobodies. Through ensemble-based deep mutational profiling of stability and binding affinities, we identify critical hotspots and characterize molecular mechanisms of SARS-CoV-2 spike protein binding with single ultra-potent nanobodies, nanobody cocktails and biparatopic nanobodies. By quantifying dynamic and energetic determinants of the SARS-CoV-2 S binding with nanobodies, we also examine the effects of circulating variants and escaping mutations. We found that mutational escape mechanisms may be controlled through structurally and energetically adaptable binding hotspots located in the host receptor-accessible binding epitope that are dynamically coupled to the stability centers in the distant epitope targeted by VHH U/V/W nanobodies. The results of this study suggested a mechanism in which through cooperative dynamic changes, nanobody combinations and biparatopic nanobody can modulate the global protein response and induce the increased resilience to common escape mutants.

The extended finite element method (XFEM) is now widely used in crack simulations and the direction of propagation of the XFEM crack in SS-304 has been quite interesting. This paper discusses the direction,θ(+ve in anti-clockwise direction), of the XFEM crack (under mode-I) propagation based on the von Mises stress-field around the crack-tip for static loading under the light water reactors (LWRs) conditions. The Mises core region from the crack-tip is chosen for β=〖90〗^o, the angle between the load and the initial crack. Experimental data for LWRs’environment is obtained and the simulations have been carried out applying three different static loads and results for the direction of the crack are calculated by measuring the stress-field around the crack-tip. It has been found that the direction of the XFEM varies inversely as the stress-field around the crack tip is increased. The computational results have been compared with the numerical results based on the minimum strain energy density criterion[S-criterion].

In this study, we discuss the properties of absolute void space or the universe at zero seconds, and how these properties play a vital role in creating a mechanism in which the very first particle gets created and we find the limit in which when the absolute void volume reaches will lead to the collapse that leads to the creation of the first particle. Later we discuss the standard model explanation through the elementary dimensions theory, as according to the elementary dimensions theory study that was peer-reviewed at the end of 2020, everything in the universe is made from four elementary dimensions, these dimensions are the three spatial dimensions (X, Y, and Z) and the force equivalent.

The modulation instability of surface capillary-gravity water waves is analysed in a shear flow model with a tangential discontinuity of velocity. It is assumed that air blows along the surface of the water with a uniform profile in the vertical direction. Such a model, despite its simplicity, plays an important role in hydrodynamics as the reference model for investigating basic physical phenomena of wave-current interactions and acquiring insights into a series of complex phenomena. In certain cases where the wavelength of interfacial perturbations is much bigger than the width of the shear fow profile, the model with the tangential discontinuity in the velocity is adequate for describing physical phenomena at least within limited spatial and temporal frameworks. A detailed analysis of the air-flow conditions under which modulation instability sets in is presented. It is also shown that the interfacial waves are subject to dissipative or radiative instability when negativeenergy waves appear at the interface.

The European Union Green Deal aims at curbing planet-warming greenhouse gas emissions and introducing clean energy production. But to achieve energy efficiency, the opportunity cost of different energies must be assessed. In this article, we analyse two different systems for the treatment of wastewater that, at the same time, produce energy for its own operation. On the one hand, high-rate algal ponds system (HRAP) is considered; on the other hand, we study a conventional activated sludge system which uses photovoltaic power (AS+PV). This paper offers a viability analysis of both systems based on the capacity to satisfy their energetic consumption. In order to assess this viability, the probability of not achieving the energy consumption threshold at least one day is studied. The results point that the AS+PV system self-sufficiency is achieved using much lesser surfaces than those of HRAP system (for the former, less than 6.500 m2, for the latter 40.000 m2). However, the important AS capital cost makes still the HRAP system more economic, although storage provides a great advantage for using the AS+PV in locations where we have a lot of irradiance. This viability analysis, along with the opportunity cost analysis, will be used to assess these two projects devoted to the treatment of wastewater.

Current global commitments to reduce emissions of greenhouse gases encourage national targets for renewable generation. Due to its small land mass, offshore wind could help Bahrain to fulfill its obligations. However, no scoping study has yet been carried out. The methodology presented here addresses this research need. It employs Analytical Hierarchy Process and pairwise comparison methods in a Geographical Information Systems environment. Publicly available land use, infrastructure and transport data are used to exclude areas unsuitable for development due to physical and safety constraints. Meteorological and oceanic opportunities are ranked, then competing uses are analyzed to deliver optimal sites for wind farms. The potential annual wind energy yield is calculated by dividing the sum of optimal areas by a suitable turbine footprint, to deliver maximum turbine number. Ten favourable wind farm areas were identified in Bahrain’s territorial waters, representing about 4% of the total maritime area, and capable of supplying 2.68 TWh/yr of wind energy or almost 10% of the Kingdom’s annual electricity consumption. Detailed maps of potential sites for offshore wind construction are provided in the paper, giving an initial plan for installation in these locations.

Based on the observation and reanalysis data, the relationship between Madden-Julian Oscillation (MJO) over the Maritime Continent (MC) and the tropical Pacific-Indian Ocean temperature anomaly mode is analyzed. The results showed that the MJO over the MC region (100°-140°E, 10°S-5°N) (referred to as MC-MJO) possesses prominent interannual and interdecadal variations and seasonally "phase-locked" features. MC-MJO is strongest in the boreal winter and weakest in the boreal summer. Winter MC-MJO kinetic energy variation has significant relationships with the El Niño-Southern Oscillation (ENSO) in winter and the Indian Ocean Dipole (IOD) in autumn, but it correlates better with the tropical Pacific-Indian Ocean associated mode (PIOAM). The correlation coefficient between the winter MC-MJO kinetic energy index and the autumn PIOAM index is as high as -0.43. This means that when the positive (negative) autumn PIOAM anomaly strengthens, the MJO kinetic energy over the winter MC region weakens (strengthens). However, the correlation between the MC-MJO convection and PIOAM in winter is significantly weaker. The propagation of MJO over the Maritime Continent differs significantly in the contrast phases of PIOAM. During the positive phase of the PIOAM, the eastward propagation of the winter MJO kinetic energy always fails to move across the MC region and cannot enter the western Pacific. However, during the negative phase of the PIOAM, the anomalies of MJO kinetic energy over the MC is not significantly. MJO can propagate farther eastward and enter the western Pacific. One thing must be pointed out that there is a significant difference between the propagation of MJO convection over the MC region in winter and that of the MJO kinetic energy. That said, the MJO convection is more likely to extend to the western Pacific in the positive phases of PIOAM than in the negative phases

Abstract: The human race has always innovated, and in a relatively short time went from building fires and making stone-tipped arrows to creating smartphone apps and autonomous robots. Today, technological progress will undoubtedly continue to change the way we work, live, and survive in the coming decades. Since the beginning of the new millennium, the world has witnessed the emergence of social media, smartphones, self-driving cars, and autonomous flying vehicles. There have also been huge leaps in energy storage, artificial intelligence, and medical science. We are facing immense challenges in global warming and food security, among many other issues. While human innovation has contributed to many of the problems we are facing, it is also human innovation and ingenuity that can help humanity deal with these issues “New directions in science are launched by new tools much more often than by new concepts. The effect of a concept-driven revolution is to explain old things in new ways. The effect of a tool-driven revolution is to discover new things that have to be explained”. (F. Dyson, 1997 In this article, we review the impact of technology as evolving at beginning of 21st Century on future prospect of Energy demand either renewable or non-renewable form, Economy, to Ecommerce, Education and any other E-related of Modern Technology.

It is agreed that before the creation of particles, space was absolutely devoid of matter and radiation. In this study, we assume that the absolute void comprises four dimensions; three spatial dimensions and a force equivalent representing the factor of change among the elementary dimensions. Our hypothesis is based on the expansion of the spatial dimensions, and the subsequent space instability. We demonstrated that when the outward force equivalent strength exceeds a critical limit, it collapses inward to restore equilibrium in the system. Then, the void inside the collapsed force equivalent acts as a void in a confined system, the energy of the system remains conserved at all stages. With the decrease of the spatial dimensions due to the collapse the energy density increases, at the final stage the energy in the confined system is concentrated forming a solid state of energy. In which, this solid state of energy is a particle become the source of the elementary particles. The created high-energy sources are controlled by the internal and external forces of the source and all entities in its external force field until equilibrium is reached. The article gives the summary of Big bang theory and its problems which are further discussed in inflation. This article will help in understanding that how elementary dimensions play a role in the formation of elementary particles. The quark gluon plasma, inflation, gravitational collapse, and gravitational lensing provide evidence supporting the elementary dimensions theory presented in this paper.

Primary energy consumption is one of the key drivers of global CO₂ emissions that, in turn, heavily depend on the efficiency of involved technologies. Either the improvement in technology efficiency or the expansion of non-fossil fuel consumption require large investments. The planning and financing of such investments, by policy makers or global energy firms, require, in turn, reliable measures of associated global spreads and their evolution in time. In this paper, our main contribution is the introduction of index measures for accessing global spreads (that is, measures of inequality or inhomogeneity in the statistical distribution of a related quantity of interest) of technology efficiency and CO₂ emission in primary energy consumption. These indexes are based on the Gini index, as used in economical sciences, and generalised entropy measures. Regarding primary energy sources, we consider petroleum, coal, natural gas and non-fossil fuels. Between our findings, we attest some stable relations in the evolution of global spreads of technology efficiency and CO₂ emission, and a positive relation between changes in global spreads of technology efficiency and use of non-fossil fuel.

To understand the mystery of final unification, in our earlier publications, we proposed two bold concepts: 1) There exist three atomic gravitational constants associated with electroweak, strong and electromagnetic interactions. 2) There exists a strong elementary charge in such a way that its squared ratio with normal elementary charge is close to reciprocal of the strong coupling constant. In this paper we propose that, can be considered as a compound physical constant associated with proton mass, electron mass and the three atomic gravitational constants. With these ideas, an attempt is made to understand nuclear stability and binding energy. In this new approach, nuclear binding energy can be fitted with four simple terms having one unique energy coefficient with a formula, where is an estimated mean stable mass number. With this new approach, Newtonian gravitational constant can be estimated in a verifiable approach with a model relation of the form, where is the Fine structure constant. Estimated and is 62 ppm higher than the CODATA recommended It needs further investigation. Proceeding further, an attempt is made to fit the recommended quark masses.

The introduction of electrical vehicle charging infrastructure including EV charger, renewable energy resource at secondary feeder in distribution system has been increased as one of countermeasure for global environmental issues. However, the Electric Vehicle Charging (EVC) infrastructure may act as the peak load in distribution system, which can adversely impact on the voltage stability when the electric vehicle is quickly charged. Therefore, to keep within the limit capacity of secondary feeder and allowable limit for feeder voltage, this paper proposes a stabilization method by the Energy Storage System (ESS) control strategy at secondary feeder in order to be not violated over than lower and upper limit. Also, this paper presents the estimation method to keep the proper standard value of State of Charge (SOC). From the simulation results, the voltage stabilization operation by ESS should make the feeder voltages of the distribution system(secondary feeder) introduced EVC Infra keep better voltage conditions, also estimation method to keep the proper standard value is confirmed that the SOC of ESS when is the standby condition could be exactly kept within the proper reference range.

Machine learning (ML) methods has recently contributed very well in the advancement of the prediction models used for energy consumption. Such models highly improve the accuracy, robustness, and precision and the generalization ability of the conventional time series forecasting tools. This article reviews the state of the art of machine learning models used in the general application of energy consumption. Through a novel search and taxonomy the most relevant literature in the field are classified according to the ML modeling technique, energy type, perdition type, and the application area. A comprehensive review of the literature identifies the major ML methods, their application and a discussion on the evaluation of their effectiveness in energy consumption prediction. This paper further makes a conclusion on the trend and the effectiveness of the ML models. As the result, this research reports an outstanding rise in the accuracy and an ever increasing performance of the prediction technologies using the novel hybrid and ensemble prediction models.

Non-Orthogonal Multiple Access (NOMA) is the key technology promised to be applied in next-generation networks in the near future. In this study, we propose a multi-points cooperative relaying (MPCR) NOMA model instead of just using a relay as the previous studies. Based on the channel state information (CSI), the base station (BS) selects a closest user equipment (UE) and sends a superposed signal to this UE as a first relay node. We have assumed that there are N UEs in the network and Nth UE, which is farthest from BS, has the poorest quality signal transmitted from the BS compared other UEs. Nth UE received the forwarded signal from N-1 relaying nodes that are UEs with better signal quality. At the ith relaying node, it detect its own symbol by using successive interference cancellation (SIC) and will forward the composite signal to the next closest user, namely i+1th UE, and include an excess power which will use for energy harvesting (EH) intention at the next UE. By these, the farthest UE in network can be significantly improved. In addition, closed-form expressions of outage probability for users over both the Rayleigh and Nakagami-m fading channels are also presented. Analysis and simulation results performed by Matlab software which are presented accurately and clearly show that the effectiveness of our proposed model and this model consistents with the multi-access wireless network in future.

This paper presents a demonstration of the feasibility of fabricating micro-cantilever harvesters with extended stress distribution and enhanced bandwidth by exploiting an M-shaped two-degrees-of-freedom design. The measured mechanical response of the fabricated device displays the predicted dual resonance peak behavior with the fundamental peak at the intended frequency. This design has the features of high energy conversion efficiency in a miniaturized environment where the available vibrational energy varies in frequency. It makes such a design suitable for future large volume production of integrated self powered sensors nodes for the Internet-of-Things.

Hybrid carbon-silicon, carbon-nitrogen, and carbon-boron clathrates are new classes of Type I carbon-based clathrates that have been identified by first-principles computational methods by substituting atoms on the carbon clathrate framework with Si, N, and/or B atoms. The hybrid framework is further stabilized by embedding appropriate guest atoms within the cavities of the cage structure. Series of hybrid carbon-silicon, carbon-boron, carbon-nitrogen, and carbon-silicon-nitrogen clathrates have been shown to exhibit small positive values of the energy of formation, indicating that they may be metastable compounds and amenable to fabrication. In this overview article, the energy of formation, elastic properties, and electronic properties of selected hybrid carbon-based clathrates are summarized. Theoretical calculations that explore the potential applications of hybrid carbon-based clathrates as energy storage materials, electronic materials, or hard materials are presented. The computational results identify compositions of hybrid carbon-silicon and carbon-nitrogen clathrates that may be considered candidate materials for use as either electrode materials for Li-ion batteries or as hydrogen storage materials. Prior processing routes for fabricating selected hybrid carbon-based clathrates are highlighted and difficulties encountered are discussed.

Abstract: High step-up voltage gain nonisolated DC-DC converter have attracted much attention in photovoltaic, fuel cells and other renewable energy system applications. In this paper, by combining input current ripple-free boost cell with coupled-inductor voltage-doubler cell, an input current ripple-free high voltage gain nonisolated converter is proposed. In addition, passive lossless clamp circuit is adopted to recycle the leakage inductor energy and to reduce the voltage spike across the power switch. By utilizing voltage-doubler cell consisting of diode and capacitor, the voltage stress of switch is further reduced and the resonance between the leakage inductor and the stray capacitor of the output diode is eliminated. A low switch-on-resistance low-voltage-rated MOSFET can therefore be employed to reduce the conduction loss and cost. The reverse recovery loss of output diode is reduced, and the efficiency of converter can be improved. Furthermore, the proposed converter can achieve nearly zero input current-ripple and make the design of electromagnetic interference (EMI) filter easy. Steady state analysis and operation mode of the converter is performed. Finally, experimental results are presented to verify the analysis results of the proposed converter.

Gravitation is interpreted to be an “ontomathematical” force or interaction rather than an only physical one. That approach restores Newton’s original design of universal gravitation in the framework of “The Mathematical Principles of Natural Philosophy”, which allows for Einstein’s special and general relativity to be also reinterpreted ontomathematically. The entanglement theory of quantum gravitation is inherently involved also ontomathematically by virtue of the consideration of the qubit Hilbert space after entanglement as the Fourier counterpart of pseudo-Riemannian space. Gravitation can be also interpreted as purely mathematical or logical “force” or “interaction” as a corollary from its ontomathematical (rather than physical) realization. The ontomathematical approach to gravitation is implicit in general relativity equating it to operators in pseudo-Riemannian space obeying the Einstein field equation and also well-known by the “geometrization of physics”. Quantum mechanics shares the same by the separable complex Hilbert space and defining “physical quantity” by the Hermitian operators.

Low Power Wide Area Networks (LPWAN) enable a growing number of Internet-of-Things (IoT) applications with large geographical coverage, low bit-rate, and long lifetime requirements. LoRa (Long Range) is a well-known LPWAN technology that uses a proprietary Chirp Spread Spectrum (CSS) physical layer, while the upper layers are defined by an open standard - LoRaWAN. In this paper, we propose a simple yet effective method to improve the Quality-of-Service (QoS) of LoRa networks by fine-tuning specific radio parameters. Through a Mixed Integer Linear Programming (MILP) problem formulation, we find optimal settings for the Spreading Factor (SF) and Carrier Frequency (CF) radio parameters, considering the network traffic specifications as a whole, to improve the Data Extraction Rate (DER) and to reduce the packet collision rate and the energy consumption in LoRa networks. The effectiveness of the optimization procedure is demonstrated by simulations, using LoRaSim for different network scales. In relation to the traditional LoRa radio parameter assignment policies, our solution leads to an average increase of 6% in DER, and a number of collisions 13 times smaller. In comparison to networks with dynamic radio parameter assignment policies, there is an increase of 5%, 2.8%, and 2% of DER, and a number of collisions 11, 7.8 and 2.5 times smaller than equal-distribution, Tiurlikova's (SoTa), and random distribution, respectively. Regarding the network energy consumption metric, the proposed optimization obtained an average consumption similar to Tiurlikova's, and 2.8 times lower than the equal-distribution and random dynamic allocation policies. Furthermore, we approach the practical aspects of how to implement and integrate the optimization mechanism proposed in LoRa, guaranteeing backward compatibility with the standard protocol.

This study investigates the fundamental equations governing photon behaviour in external gravitational fields due to electromagnetic-gravitational interaction, emphasizing their energy, momentum, and wavelength relationships. Building upon the pioneering contributions of Max Planck and Louis de Broglie, the analysis highlights key equations such as E = hf, ρ = h/λ, and ℓp/tp = c, which elucidate the wave-particle duality and energy conservation principles applicable to photons. The conservation of photon energy in gravitational fields, expressed by Eg = E, underscores the symmetrical nature of photon interactions as they traverse strong gravitational environments. The observed phenomena of redshift and blueshift are interpreted within this framework, alongside a reinterpretation of gravitational lensing as a consequence of the momentum exchange between photons and the curvature of external gravitational fields. This perspective challenges conventional understandings and suggests that established theories may require refinement. The study advocates for the integration of alternative frameworks, such as quantum gravity and flat spacetime models, to address discrepancies between observed photon behaviour and current gravitational theories. By exploring these interactions, this research aims to enhance our understanding of the fundamental laws governing the universe, contributing to ongoing efforts toward a unified theory that reconciles quantum mechanics and gravity.

The main objective of the present study is to demonstrate the possibility of actively influencing the position of the bow shock wave and the main parameters of supersonic flow over a blunt body by organizing a gas discharge near the front surface, in the region between the body and the bow shock wave. The research is carried out using both experimental and numerical methods. The working gas was xenon. It is shown that the steady bow shock wave stand-off distance along with the current and power of the discharge, is associated with the change in the adiabatic index of the plasma created by the discharge, which, in turn, is determined by the plasma parameters, such as the degrees of nonequilibrium and the degree of ionization. It is shown that the adiabatic index with the power supplied to the impact zone in the range of 30-120 kW can both increase and de-crease in the range of 1.25-1.288. The study of the discharge created plasma zone was conducted and the correspondence between the discharge current and power, and the average parameters in the plasma zone created by the discharge is presented. A good agreement between the numerical and experimental data was shown. The results may be useful in developing control systems for high-speed civil aircrafts.

The increasing volume of Municipal Solid Waste (MSW), including biodegradable plant residues such as pruning, leaves, and kitchen waste, presents a substantial environmental challenge due to the limited availability of landfill space and the resulting environmental contamination. Sustainable waste management practices, encompassing recycling and waste-to-energy conversion through biological or thermochemical processes, are imperative. In the Municipality of Athens, Greece, significant quantities of green waste generated from public and private gardening activities provide a valuable opportunity for energy recovery and landfill waste reduction. In accordance with Directive 2008/98/EC, Athens emphasizes waste prevention, reuse, recycling, and recovery. This study examines alternative bio-waste and green waste management systems, with examples from Europe, focusing on the Athens Directorate of Urban Green Spaces and Urban Wildlife. It discusses methods for assessing the energy value of pruning residues, providing a definitive disposal framework. Additionally, it presents a technoeconomic study of one of the Municipal Swimming Pools in the Municipality of Athens, investigating the production and distribution of thermal energy to meet the heating needs of the pool facilities. This research identifies key constraints and their impact on decision-making, highlighting the potential for alternative green waste management. It advocates modern recycling techniques in line with national and Community legislation, demonstrating significant environmental and economic benefits.

This article explores the multifaceted argument for Scottish independence, emphasizing Scotland's historical context, cultural identity, and the potential benefits of rejoining the European Union (EU). It begins with a historical overview, tracing Scotland's deep roots in independence and its eventual union with England in 1707, which, despite economic benefits, subordinated Scottish interests to those of England. The article argues that Scotland's distinct identity and ongoing desire for autonomy justify a renewed push for independence. Reuniting with Europe is presented as a key advantage, offering Scotland access to the EU's single market, financial support, and a platform for political influence. Additionally, independence would empower Scotland to harness its renewable energy resources, develop tailored economic policies, and uphold its tradition of social justice. However, the article also acknowledges the unique challenges Scotland faces, particularly in formulating citizenship policies amidst the legacy of English imperialism. Ultimately, the article posits that despite these challenges, independence offers Scotland a path to realizing its full potential as a sovereign nation committed to democracy, equality, and cooperation.

Humanity is shifting its power generation to renewable energy, notably wind power. As more and more wind power plants are built, it has become important to improve the efficiency of wind power generation and reduce the manufacturing costs of wind power equipment. The mechanical multiplier gearbox is one of the most important parts of the wind power turbine, and it is now being built as a planetary gear train as these gearboxes offer a compact build capable of high power ratings in a relatively small package with coaxial input and output shafts. It is very important to select the right kinematic scheme and the other relevant parameters in the early design stages as the wrong kinematic scheme will result in a suboptimal solution. This article deals with the selection of the optimal gearbox solution for a 700 kW wind turbine application, taking into account both two-carrier and three-carrier gearbox solutions. As the optimal solution may be deducted only by systematic analysis, the proprietary 2-SPEED software has been developed for this purpose. The results of the analysis have been presented in this article, and optimal gear train solutions have been suggested for both two-carrier and three-carrier multiplier configurations.

These counterexamples have shown the relationships between the power of a Pythagorean equation and Pythagorean’s triples. There are three positive integers that satisfy Fermat’s equation when the power n is equal to 2 in the case of the Pythagorean theorem and it’s applicable relationships in right triangles. On the other hand, as the power varies from positive to negative integers or any integers other than 2, such as in the case of Fermat’s last theorem, the hypotenuse z of a right triangle tends to be equal to one of the sides x or y of the triangle and the other side tends to be equal to zero. And the application of this idea describes the behavior of a mass object in motion. Since the total energy of the object is the sum of its energy in motion and its rest energy, at a particular power n, the total energy of the object tends to be equal to either the rest energy or the photon energy.

The growing demand for clean energy transitions has become increasingly significant, with solar energy emerging as one of the most prominent clean energy resources contributing to this effort. However, there remains limited knowledge regarding the economic feasibility of solar project development across different geographic locations and scales. This study introduces a comprehensive economic analysis framework to assess the economic viability of residential and utility-scale solar projects, using California, Tennessee, and Texas as case studies. The economic assessment is conducted through a cost-benefit analysis that adopts a full life-cycle approach, encompassing phases from permitting to demolition for both scales of solar projects. We found that utility-scale solar projects generally offer more favorable investment return ratios compared to residential projects, despite the absence of land acquisition costs and lower initial capital expenditures for the latter. Furthermore, the incorporation of energy storage solutions, such as Battery Energy Storage Systems (BESS), is shown to be essential for improving the efficiency of residential solar energy usage, with efficiency gains of up to 50%. Finally, region-specific strategies, including net metering policies, electricity retail market structures, and the promotion of solar adoption, play a crucial role in enhancing the financial viability of solar projects for both residential and utility scales.

The minimum ignition energy (MIE) has been extensively studied via experiments and simulations. However, our literature review reveals little quantitative consistency, with results varying for f=1.0 from 0.324 to 1.349 mJ, and for f=0.9 from 0.22 to 0.944 mJ. Therefore, there is a need to resolve these discrepancies. This RANS study aims to partially address this knowledge gap. Additionally, it presents other flame evolution parameters essential for robust combustion design. Using the reactingFOAM solver we predict the threshold energy required to ignite the fuel mixture. For this, the single step using the Arrhenius law is selected to model ignition in the flame kernel of stochiometric and lean CH₄/air mixtures, allowing it to develop into a self-sustained flame. The ignition power density, an energy quantity normalised with volume is incrementally varied keeping the kernel critical radius r_s constant 0.5 mm in the quiescent mixture of two equivalence ratios fs 0.9, and 1.0, for varied operating pressures 1, 5 and 10 bar at constant initial temperature 300 K. The minimum ignition energy is validated with twelve independent 1 bar data sets both numerical and experiments. Finally, a mathematical formulation of MIE is devised, a function of pressure and equivalence ratio shows a slightly curved relationship.

This research investigates the energy consumption of buildings managed by traditional Building Management Systems (BMS) and proposes the integration of Internet of Things (IoT) technology to enhance energy efficiency. Conventional BMS often suffer from significant energy wastage and safety hazards due to sensor failures or malfunctions. These issues arise when building systems continue to operate under unknown conditions while the BMS is offline, leading to increased energy consumption and operational risks. The study demonstrates that integrating IoT systems with existing BMS can substantially improve energy efficiency in smart buildings. The research involved designing a system architecture prototype, performing MATLAB simulations, and real-life case study which revealed that IoT devices are effective in reducing energy waste, particularly in Heating, Ventilation, and Air Conditioning (HVAC) systems and lighting. Additionally, an auxiliary bypass system was incorporated in parallel with the IoT system to enhance reliability in the event of IoT system failures. Preliminary findings indicate that the integration of IoT systems with traditional BMS significantly boosts energy efficiency and safety in smart buildings. This integration offers a promising solution for advancing energy management practices and policies, thereby improving both operational performance and sustainability in building management.

In this paper, we make an attempt to estimate the famous Avogadro number with programming logics written in Python associated with advanced nuclear binding energy formulae. Average rest mass of nucleon, nuclear binding energy per nucleon and electron rest mass seem to play a vital role in estimating the unified atomic mass unit and Avogadro number. Interesting point to be noted is that, Avogadro number seems to be the inverse of the Unified atomic mass unit. With further study, it seems possible to estimate the unified atomic mass unit and Avogadro number accurately. Our interesting observation is that, short range strong nuclear force seems to have a vital role in deciding the accuracy of Avogadro number. For that purpose one may consider AI techniques along with newly observed atomic nuclides and their nuclear binding energies. For Z=6 to 118 and A_low=2Z and A_upper=3.5Z, estimated average value of Avogadro number is $N_{Average} \cong 6.01938 \times 10 ^{26}$. Considering the saturation of nuclear binding energy, at Z=26, $N_{Z=26} \cong \left(6.02229 \textrm{to} 6.02285\right) \times 10 ^{26}$. At academic level, our proposal can be given a chance as a case study. It is planned to develop a web application for this purpose.

It is commonly held that gravitation is a major force field influencing matter. Existing models regard gravitational interaction as a singular weak force; the weakest among the four fundamental forces defined in physics. Recent experimental findings, in both controlled laboratory experiments and natural occurrences, nevertheless, have unveiled the presence of a gravitational repulsion alongside gravitational attraction in the universe. This series of studies reveals that the observed gravitational force results from two immensely powerful distinct forces—gravitational repulsion and attraction—nearly equal and opposing thus in a state of near equilibrium in nature. While the theory of 'Universal Gravitation' established the proportionality of the gravitational force to mass, the recognition of gravitational repulsion force proportional to the temperature as a manifestation of thermal energy has only emerged from present experimental insights. Furthermore, the imbalance between these two forces has been identified as the Newtonian force, initiating the motion of an object. It provides a compelling explanation for the accelerating expansion of the universe: during atomic fusion in stars, a portion of mass is converted into energy. This process increases the energy and decreases the mass of stellar objects. The increase in energy enhances the repulsive force among them, while the reduction in mass diminishes their gravitational attraction, leading to the accelerating expansion of the universe.This paper introduces a model elucidating the characteristics of gravitational forces and the transmission of energy within matter through the concept of 'Gravitational Currents.' A set of postulates is formulated to elucidate the interaction of gravitational fields with matter and the presence of gravitational currents. The discussion is supported by experimental evidence substantiating these concepts.In this series of experiments, a gyroscope - a standard apparatus in the scientific community with a spinning wheel mounted at one end of a freely pivoted rod having full degrees of freedom - is utilized. When the wheel is set in rotation, the rod carrying the wheel precesses[1] around the vertical axis at the pivoted end, while levitating in free space defying the Earth's gravitational attraction. This paper establishes that the conventional explanation involving the cross product of two vectors—the torque due to weight and the angular force (change of angular momentum) of the wheel—fails to account for the observed revolving and lifting forces. Instead, it is demonstrated that these forces result from the upward shear force (which is the lifting force in this case) generated within the axis of the rod and the wheel itself. This phenomenon is attributed to the flow of energy, conceptualized as gravitational current, within the axial rod in the Earth's gravitational field. The described process can be envisioned as a gravitational motor with gravitational current flowing through matter in a gravitational field.The results of the experiments substantiate the conclusion that there exist two fields defined as the intrinsic field and the natural force fields. The intrinsic gravity field is innate (linked) to every object, matter or entity in the universe, and it is dispersed in all directions in free space independent of other entities. The actual force fields manifest between any two objects in the universe once they become cognizant of each other's existence through their intrinsic fields.The inherent force field exhibits a preference/tendency for existence within a medium rather than in free space, akin to the way a magnetic field runs within ferromagnetic materials rather than in open space. If external force fields pass/runs through the medium, it affects the internal force fields of the medium, depending on the magnitudes and the directions of the external force fields and intrinsic force fields. This implies that energy moves through the force field, and under the influence of the gravitational field, this energy flow can be conceptualized as a gravitational current.Gravitational waves and electromagnetic waves share similarities in their roles in transmitting energy through open space. The potential for an analogy within a unified theoretical framework connecting electromagnetic fields and gravitational fields has surfaced, echoing Einstein's attempted unified theory proposed in 1916. The paper delves into the parallels between electromagnetic motors and gravitational motors.Furthermore, alongside the concept of gravitational currents addressed in this paper, the research also elucidated a precise definition of the [Newtonian/mechanical] “force” and mechanism for its origination and function, termed: Intrinsic Energy Spin Force (IESpinF). The analysis presented here demonstrates that the Newtonian/mechanical force arises from a perturbation or imbalance within the equilibrium of gravitational IESpinF, which includes both repulsion and attraction forces. [1] One of the main properties of gyroscopic action is “precession”. Precession is a change in the orientation of the rotational axis of a rotating body. If the axis of rotation of a body is itself rotating about a second axis, that body is said to be precessing about the second axis.

Microgrid (MG) control is essential for efficient, reliable, and sustainable energy management in distributed energy systems. Genetic Algorithm-based energy management systems (GA-EMS) can optimally control a MG by finding global optima and handling complex, non-linear, and non-convex problems, but they can be computationally intensive, making real-time control challenging. Model Predictive Control (MPC)-based EMS predicts future behaviour over a defined horizon, ensuring optimal performance and constraint satisfaction but typically relies on linear models. This paper proposes a novel Genetic Predictive Control (GPC) method, combining GA and MPC to enhance resource allocation, balance multiple objectives, and adapt dynamically to changing conditions. Integrating GA with MPC significantly improves the handling of non-linearities and non-convexity in the system model, leading to more accurate and effective control. Comparative analysis shows that GPC significantly reduces excess power production—surplus power generated beyond load demand—improving resource allocation efficiency. For instance, in the Mutation–Random Selection scenario, GPC reduced excess power to 76.0W compared to 87.0W with GA. Additionally, GPC balances cost, emissions, and power efficiency. In the Crossover-Elitism scenario, GPC achieved a daily cost of $113.94 compared to GA's $127.80, and carbon emissions of 52.83 kg CO2e compared to GA's 69.71 kg CO2e, demonstrating GPC's cost efficiency and environmental benefits. While MPC optimizes a weighted sum of objectives, designing appropriate weights can be challenging and may result in non-convex problems. GA handles multiple, conflicting objectives through multi-objective optimization, providing Pareto-optimal solutions. GPC's dynamic adaptability maintains optimal performance by forecasting future load demands and adjusting control actions. GPC consistently achieves lower emissions than GA across various scenarios and, although it sometimes incurs higher costs, such as $113.94 compared to $131.90 in the Crossover–Random Selection scenario, its holistic approach balances these costs with other metrics, making it cost-effective in the long run. By reducing excess power production and emissions, GPC contributes to economic savings and promotes sustainable practices. These findings underscore GPC's potential as a versatile, efficient, and environmentally beneficial optimization tool for power generation systems.

Effective solar forecasting has become a critical topic in the scholarly literature in recent years due to the rapid growth of photovoltaic energy production worldwide and the inherent variability of this source of energy. Due to the technological and econonomic limitations of energy storage solutions, using other, mosty conventional, sources to cover energy shortfalls and at the same time utilising solar surpluses production becomes necessary. The need to optimize energy systems, ensuring power continuity, and balancing energy supply and demand has led to the development of various forecasting methods and approaches based on meteorological data or photovoltaic plant characteristics. This article presents the results of a meta-review of the solar forecasting literature, including the current state of knowledge and methodological discussion. It presents a comprehensive set of forecasting methods, evaluates current classifications, and proposes a new synthetic typology. The article emphasizes the increasing role of artificial intelligence (AI) and machine learning (ML) techniques in improving forecast accuracy, alongside traditional statistical and physical models. It explores the challenges of hybrid and ensemble models, which combine multiple forecasting approaches to enhance performance. The paper addresses the emerging trends in solar forecasting research, such as the integration of big data and advanced computational tools. Additionally, from a methodological perspective, the article outlines a rigorous approach to the meta-review research procedure, addresses the scientific challenges associated with conducting bibliometric research, and highlights best practices and principles. This includes defining research questions, selecting eligibility criteria, literature search, data extraction, synthesis, and assessing bias and quality. The article contributes to the solar forecasting field by providing up-to-date knowledge, along with insights on the emerging trends, future research directions, and anticipating implications for the theory and practicce.

Modern building automation systems implement plenty of advanced control and monitoring functions considering various parameters like users’ activity, lighting, temperature changes etc. Moreover, new solutions based on Internet of Things and cloud services are also being developed for smart buildings to ensure comfort of use, user safety, energy efficiency improvements and integration with smart grids and smart city platforms. Such a wide spectrum of technologies and functions requires a new approach in building automation systems design to provide effective way of their implementation and flexibility during operation. At the same time, in the building design and operation industries, tools based on building information modeling and digital twins are being developed. In this paper, the authors discuss development directions and application areas of these solutions, identifying new trends and possibilities of their use in smart homes and buildings. In particular, the focus is on procedures for selecting automation functions, effective integration, and interoperability of building management systems with Internet of Things considering organization of prediction mechanisms and dynamic functional changes in buildings and smart networks. Chosen solutions and functions should consider the requirements from EN ISO 52120 standard and the guidelines defined for the Smart Readiness Indicator.

Wind energy is a kind of renewable energy with great potential for development. This study mainly investigated the application of shock waves generated by high-pressure gases (wind energy) for generating energy. In this study, we designed a new supersonic shock wave generator that can be reused without disassembling and assembling bolts and developed a supersonic shock wave monitoring system. This system monitored the velocity of the generated shock waves, which was Mach 3-5, and the output pressure was more than 100 times higher than the input pressure of the shock wave generator tank.Then, we developed a power generation system driven by supersonic shock waves based on the characteristics of the new shock wave generator, which can generate high-pressure and high-speed blast waves and can be reused. The shock wave generator can repeatedly generate high-pressure waves to drive the Tesla turbine and then the magnetic energy generator for power generation. We established a complete control process for power generation driven by shock waves by controlling the valve stem. The system can detect the tank pressure, output pressure, gas flow, rotation speed, voltage, and current during the control process for the performance analysis of power generation.

Buildings’ thermal energy needs are inherently linked to climate conditions. Consequently, it is crucial to evaluate how climate changes affect these energy demands. Despite extensive analysis, a comprehensive assessment involving a diverse range of building types has not been consistently conducted. The primary objective of this research is to perform a coherent evaluation of the influence of climate changes, construction element properties, and the Heating, Ventilation, and Air Conditioning (HVAC) system type of control on the energy requirements of six buildings (residential, services, and commercial). The buildings are considered located in a temperate Mediterranean climate. Our focus is on the year 2070, considering three distinct climatic scenarios: (i) maintaining the current climate without further changes, (ii) moderate climate changes, and (iii) extreme climate changes. The buildings are distributed across three different locations, each characterized by unique climatic conditions. Buildings’ envelope features a traditional External Thermal Insulation Composite System (ETICS) and expanded polystyrene (EPS) serves as thermal insulation material. Two critical design factors are explored: EPS thickness ranging from 0 (no insulation) to 12 cm; and horizontal external fixed shading elements varying lengths from 0 (absence) to 150 cm. Six alternative setpoint ranges are assessed for the HVAC system control: three based on the Predicted Mean Vote (PMV) and three based on indoor air temperature (Tair). Results were obtained with a validated in-home software tool. They show that, even under extreme climate conditions, the application of thermal insulation remains energetically favorable, however its relative importance diminishes as climate severity increases. Then, proper insulation design remains important for energy efficiency. The use of external shading elements for glazing (e.g., overhangs, louvers) proves beneficial in specific cases. As climate changes intensify, the significance of shading elements grows. Thus, strategic placement and design are necessary for good results. The HVAC system’s energy consumption depends on the level of thermal comfort requirements, on the climate characteristics and on the building’s type of use. As climate change severity intensifies, energy demands for cooling increase, while energy needs for heating decrease. However, it’s essential to recognize that the impact of climate changes on HVAC system energy consumption significantly depends on the type of building.

This paper presents a novel approach to power management techniques in energy storage system (ESS) interoperability with the energy power system (EPS) by inserting a SCADA controlled directional protection relay for improving the mode switching sequence. According with latest European standards, all necessary measures for re-synchronization and reconnection for health work of the system must be taken. The proposed approach intends to improve the “interface” between storage systems and electric power grid by using a directional relay which provides interoperability improvement by automatic recognizing and differentiating the switching sequence of the mode of operation from the fault mode. Simulated results from a small scale electrical generating system are provided. The results demonstrate that the proposed power management solution is technically ideal to achieve high quality energy while retaining the stability of the power grid network. The interoperability of PHS systems integrated with the electric power grid usually leads to perturbations in terms of frequency of the generated voltage, and for improving it we designed an automatic treating and re-connecting software module. This work regards the importance of producing electricity from green and renewable energy sources, while retaining the stability and reliability of the power grid. ESS systems are widely used to help balancing of intermittent forms of load demand on the electrical power grid at specific key moments. In this article, the pumped hydro storage (PHS) technologies are proposed as an economical way to utilize smoothly the off-peak energy or surplus energy, by pumping water to a reservoir at a higher level. During peak load periods, the stored water is discharged through the reversible pump-turbine to generate electricity to meet the peak demand controlled by designed SCADA application.

The continuous flowing spacetime forms a spacetime group G, one of its fundamental groups is the Poincare group PO(1,3), and the matter and interaction fields are representations of its intrinsic spacetime group. As a kind of quantized space-time unit, space-time group elements generate both space-time manifolds and matter. Matter and fields are aggregates of the quantum space-time within them and determine their type: the Lorentz group SO(1,3) represents a rotating spacetime corresponding to visible matter and the translation group P^1,3 represents a translational spacetime corresponding to dark matter and dark energy. The aggregation mode of space-time degrees of freedom in matter reveals that charge conjugation symmetry is the inverse symmetry of internal time of charged particles, and the external parity breaking of neutrinos is also due to their internal spatial aggregation mode.

The inherited ‘EIA’ process at Brexit is based on a ‘Project’ period from Inception tothe start of construction works. The ‘Incompleteness’ of the process covers andidentifies stages that will impact on the environmental cycle: construction period,operational life, de-commissioning and a return to acceptable environmental footprint.A master environment structure-plan framework is required to commence with theupgrading of the complete ‘EIA’ process, embracing separate limbs for the UK’spriority environmental targets for climate change, and other major adverse effectswhich result in serious ‘harm’ to the UK environment. The identification of the processfor ‘incompleteness’ requires effective sustainability, and inclusion of effectivemanagement tools, for the essential ‘monitoring/control/recording’ proceduresthroughout the project life and the natural environmental cycle. This will allow theopportunity for a new approach to a structured ‘Suite of EIAR Directives’, to enable a‘EIAR’ regime that ‘will remain fit and proper for UK purpose’.

Additive Manufacturing (AM) has been proving suitable to support or even replace traditional manufacturing in several industries, offering many advantages such as delivery time and reduction in terms of material waste, energy consumption and greenhouse gas (GHG) emissions. This study aimed to carry out a comparative assessment of the life cycle, from gate to gate, in the production of a low alloy carbon steel flange part using ER-90 wire. The methods utilized were Wire and Arc Additive Manufacturing (WAAM) and conventional manufacturing (CM) by forging, and comparative factors were energy demands, GHG emissions and generated solid waste. The total energy consumption in WAAM was 10,239.40 MJ, total carbon footprint in CO2 equivalent (CO2e) was 714.1 kgCO2e kg-1, and generated solid waste was 68.6 kg, respectively, 90%, 95% and 76% lower than consumption calculated in conventional manufacturing.

In this work, the author employs the quantum hydrodynamic formalism to achieve the geometrization of spacetime for describing the gravitational interaction within the framework of quantum theory. This approach allows for the development of an equation of gravity that is mathematically connected to the fermion and boson fields. This achievement is accomplished by incorporating two fundamental principles: covariance of the quantum field equations and the principle of least action. By considering these principles, a theory is established that enables the calculation of gravitational corrections to Quantum Electrodynamics, and potentially, to the standard model of particle physics as well. The theory also provides an explanation for two phenomena: the existence of a cosmological pressure density similar to quintessence, that is compatible with the small value of the observed cosmological constant, and the breaking of matter-antimatter symmetry at high energies offering insights into why there is an imbalance between the two in the early universe. In the cosmological modeling of the theory, there exists a proposal to account for the formation of supermassive black holes that are accompanied by their own surrounding galaxies, without relying on the process of mass accretion. The model, in accordance with recent observations conducted by the James Webb Space Telescope, supports the notion that galactic configurations were established relatively early in the history of the universe, shortly after the occurrence of the Big Bang.

Energy transition is a major structural change in the whole social system, and the energy system must be changed globally to replace fossil fuels. Hydropower is one of the largest renewable energy in the world. However the involuntary resettlees due to the construction of hydropower projects are suffering from being far away from their native land, losing the land cultivated for generations and the houses they live in, and losing the social relationship network based on geography and blood ties. Based on the system evaluation theory of reservoir resettlement and referring to relevant research findings, this paper constructs a comprehensive evaluation index framework for assessing the implementation effect of the PostRelocation Support (PReS) policy. The research region is located in Zhijin County, Bijie City, Guizhou Province, China. Accordingly, a combined method of a structural equation model and a fuzzy comprehensive evaluationary model is used in this paper to analyze the implementation of the PReS policy. The results show that the total score of implementing effects of the PReS policy is 4.4, with dramatic significance. The subindex scores of the resettlers’ family income, living conditions, and production conditions; the local economy; and social stability are 4.3, 4.6, 4.4, 4.6, and 4.3, respectively, with dramatic significance. This paper has analyzed and summarized the successful practices of implementing the PReS policy for reservoir resettlers in three dimensions: poverty alleviation, beautiful home construction and accelerating rural revitalization. Research shows that China's rural reservoir resettlers' PReS policy has been more effective in restoring the livelihoods of reservoir resettlers.

The broad acceptance of electromobility depends heavily on the performance and service life of the battery technology used. Lithium-ion battery technology is currently the most promising energy storage technology for mobile applications, but the performance and capacity of the cells is extremely temperature sensitive. Especially in these new complex and powerful applications there is a significant need for thermal management. Depending on the ambient conditions, part of the effective battery energy must therefore be used to temper the system. So far, mainly active components have been used for this task. This not only reduces the overall efficiency, but also increases the weight, volume and maintenance requirements of the system. In the present work, an alternative battery temperature management system (BTMS) was developed. A concept based on latent heat storage materials was created, which uses the advantages of thermal energy storage and the design freedom of additive manufacturing technology, and its suitability for use in battery applications was checked. On the one hand, the use of systems for storing thermal energy was researched and, on the other hand, an innovative cooling concept was created considering new production possibilities.

Liability to prevent consequences of an unhealthy situation due to accumulating toxic and hazardous emissions caused by open dumping of municipal solid waste with increasing urbanization has necessitated a renewed thinking on waste disposal. Grate fired incineration systems were adopted by urban managements in past and present but with criticisms due to formation of air borne emissions. Improved combustion methods like fluidized bed are now propagated because of current requirements like efficient energy recovery potential, stricter emission norms, adaptability with urban growth, adaptability to co-firing with other waste like biomass, edible oil wastes or industrial effluent and integration with conventional energy generation. Such a comprehensive and futuristic approach is more sustainable for the community. Multi-criteria decision-making tool is used to identify the best technology option among grate combustion and fluidized bed combustion for disposing and energy recovery from waste. Ten different collection and disposal options involving two combustion methods, namely, grate combustion and fluidized bed method are considered. Utilization of the energy is done for three end uses, namely, power generation, water distillation and district cooling. Two different regions in Saudi Arabia are considered for this study under two types of scenario, namely with recycling and without recycling. The different options are prioritized based on their overall ranking using five major performance factors.

Advancements in Parametric Design, Generative Design, and automation in Building Information Modelling (BIM) have opened new opportunities for architects and engineers working on complex buildings, such as offices. These developments allow designers to enhance their designs, increase project efficiency, improve performance, and reduce project time and costs. To address conflicting objectives that arise during the design process, genetic algorithms with multi-objective optimization (MOO) have been employed in architectural design. The GENIUS project aims to optimize building shape, apertures, and shading systems in the concept and design stages, with a focus on energy and daylight performance. The project integrates BIM and visual programming tools with Artificial Intelligence techniques like Genetic Algorithms and RBFOpt model-based optimization. Optimization algorithms are used to identify the best solutions that meet all design objectives, helping architects optimize their designs and achieve desired outcomes. The workflow was tested on a case study of a large office building, with MOO focused on maximizing daylight performance using Spatial Daylight Autonomy metric and minimizing energy consumption using Energy Use Intensity metric. The project provides architects with a method to improve their designs using Algorithm Aided Design tools, which help identify the best solutions for complex design problems.

Traditionally there is a gap between reactor operation and the consideration of nuclear waste in the final disposal. Fuel is produced and fuel must be disposed of in the view of the reactor operator, fuel has to be cleaned in the reprocessing and new solid fuel has to be produced in the view of the chemist. iMAGINE is designed to overcome this separation through the breakthrough development applying an optimized, integrative approach from cradle to grave of nuclear energy production as a first step to come as close as possible to the vision of zero waste nuclear power. It is described here the first time all in three the steps: reactor, fuel cycle, waste, providing the ratio behind each of the choices taken to come to the overall solution to open the discussion and thinking process on what could be achieved by a really innovative approach to integrated nuclear energy production. The opportunities regarding the handling of the remaining waste will be discussed with a view on the expectation of the final disposal community, the study ‘Nuclear waste from small modular reactors’, and the IAEA report ‘waste from innovative types of reactors and fuel cycles - a preliminary study. The aim of the is not to find answers to each of the raised points, but to identify first potential approaches and potentially promising ways to go, as well as to stimulate a discussion among experts. In the best case this could lead to a change of track for nuclear to become an even more sustainable and at least as important, trusted technology to help solve the net-zero challenge.

This paper describes a novel concept of producing energy efficient ”Maroon enriched natural gas “ and then Pink hydrogen” from any hydrocarbon base. The key idea is the extraction of hydrogen from water in addition to that from the hydrocarbon in an optimal fashion. This has the benefit of higher water vapor to CO2 exhaust ratio than conventional carbonaceous fuels when generating energy via combustion, a prudent step in achieving Netzero goals in a shorter time, and creating energy independence in most places.. The process of production makes concentrated CO₂ available for use and or sequestration. The process also maximizes use of renewable electricity in hydrogen generation, and maximizes use of existing infrastructure, with a minimum capital cost by energy recycle in the process. The process design applies sound thermodynamic principles which evolved during the nineteenth century, and mimics the geochemical processes going on in some of the natural 'colorless hydrogen'.

The aim of this work is to introduce a mathematical model representing the evolution of the temperature in a vegetation cover and the ground underneath it. Vegetation, and its interaction with soil, plays a very important role in the protection of soil surface from the action of sun and precipitations. A reduction in the vegetated mass increase the risk of desertification, soil erosion or surface runoffs which which can give rise to soil loss and sediment retention. These processes can favour climate change and global warming, which are major concerns nowadays. The mathematical model presented takes into account the main processes involved in vegetation cover and the interaction with the soil, among which, we can mention the Leaf Area Index, which is a dimensionless quantity defined as the one-sided green leaf area per unit ground surface area, or albedo and co-albedo which are clearly influenced by the vegetation. It is also considered a nonlinear heat capacity in the soil which incorporates the latent heat of fusion, when the phase change takes place. The numerical technique used to solve the mathematical model is based on a finite volume scheme with Weighted Essentially Non Oscillatory technique for spatial reconstruction and the third order Runge-Kutta Total Variation Diminishing numerical scheme is used for time integration. Some numerical examples are solved to obtain the distribution of temperature both in the vegetation cover and the soil.

Solar radiation prediction is an important process in ensuring optimal exploitation of solar energy power. Numerous models have been applied to this problem, such as numerical weather prediction models and artificial intelligence models. However, well-designed hybridization approaches that combine numerical models with artificial intelligence models to yield a more powerful model can provide a significant improvement in prediction accuracy. In this paper, we propose novel hybrid machine learning approaches that exploit auxiliary numerical data. The proposed hybrid methods invoke different machine learning paradigms, including feature selection, classification, and regression. Additionally, numerical weather prediction (NWP) models are used in the proposed hybrid models. Feature selection is used for feature space dimension reduction to reduce the large number of recorded parameters that affect estimation and prediction processes. The rough set theory is applied for attribute reduction and the dependency degree is used as a fitness function. We investigate the effect of the attribute reduction process with thirty different classification and prediction models in addition to the proposed hybrid model. Then, different machine learning models are constructed based on classification and regression techniques to predict solar radiation. Moreover, other hybrid prediction models are formulated to use the output of the numerical model of Weather Research and Forecasting (WRF) as learning elements in order to improve the prediction accuracy. The proposed methodologies are evaluated using a data set that is collected from different regions in Saudi Arabia.

L-17 is a thiadiazine derivative with putative anti-inflammatory, neuroprotective, and antidepressant-like properties. In this study, we applied combined in silico, ex vivo, and in vivo electrophysiology techniques to reveal the potential mechanism of action of L-17. PASS 10.4 Professional Extended software suggested that L-17 might have pro-cognitive, antidepressant, and antipsychotic effects. Docking energy assessment with AutoDockVina predicted that the binding affinities of L-17 to the serotonin transporter (SERT) and serotonin receptors 3 and 1A (5-HT3 and 5-HT1A) receptors are compatible to the selective serotonin reuptake inhibitor (SSRI) fluoxetine and selective antagonists of 5-HT3 and 5-HT1A receptors, granisetron and WAY100135, respectively. Acute pre-treatment with L-17 robustly increased c-Fos immunoreactivity in the amygdala (central nucleus), suggesting increased neuronal excitability in this brain area after L-17 administration. Acute L-17 also dose-dependently inhibited of 5-HT neurons of the dorsal raphe nucleus (DRN). This inhibition was partially reversed by subsequent administration of WAY100135, suggesting the involvement of extracellular 5-HT. Based on in silico predictions, c-Fos immunohistochemistry, and in vivo electrophysiology, we suggest that L-17 is a potent 5-HT reuptake inhibitor and/or partial 5-HT1A receptor antagonist. Thus, L-17 might be a representative of a new class of antidepressant drugs. Since L-17 also possesses neuro- and cardio-protective properties, it can be useful in post-stroke and post-myocardial infarction (MI) depression. In general, combined in silico predictions and ex vivo neurochemical and in vivo electrophysiological assessment might be a useful strategy for early preclinical assessment of the affectivity and neural mechanism in action of the novel CNS drugs.

Abstract: Safety issues related to the electrification of more electric aircraft (MEA) need to be addressed because of the increasing complexity of aircraft electrical power systems and the growing number of safety-critical sub-systems that need to be powered. Managing the energy storage systems and the flexibility in the load-side plays an important role in preserving the system’s safety when facing an energy shortage. This paper presents a system-level centralized operation management strategy based on model predictive control (MPC) for MEA to schedule battery systems and exploit flexibility in the demand-side while satisfying time-varying operational requirements. The proposed online control strategy aims to maintain energy storage (ES) and prolong the battery life cycle, while minimizing load shedding, with fewer switching activities to improve devices lifetime and to avoid unnecessary transients. Using a mixed-integer linear programming (MILP) formulation, different objective functions are proposed to realize the control targets, with soft constraints improving the robustness of the model. Besides, an evaluation framework is proposed to analyze the effects of various objective functions and the prediction horizon on system performance, which provides the designers and users of MEA and other complex systems with new insights into operation management problem formulation.

Obesity-associated metabolic abnormalities comprise of a cluster of conditions including dyslipidemia, insulin resistance, diabetes, and cardiovascular diseases that has affected more than 650 million people all over the globe. Obesity results from accumulation of white adipose tissues mainly due to the chronic imbalance of energy intake and energy expenditure. Variety of approaches to treat or prevent obesity, including lifestyle interventions, surgical weight loss procedures and pharmacological approaches to reduce energy intake and increase energy expenditure have failed to substantially decrease the prevalence of obesity. Brown adipose tissue (BAT), the primary source of thermogenesis in infants and small mammals may represent a promising therapeutic target to treat obesity by promoting energy expenditure through non-shivering thermogenesis mediated by mitochondrial uncoupling protein 1 (UCP1). Since the confirmation of functional BAT in adult humans by several groups, approximately a decade ago and its association with a favorable metabolic phenotype, intense interest on the significance of BAT in adult human physiology and metabolic health has emerged within the scientific community to explore its therapeutic potential for the treatment of obesity and metabolic diseases. Substantially decreased BAT activity in individuals with obesity indicates a role for BAT in setting of human obesity. On the other hand, BAT mass and its prevalence has been reported to correlate with lower body mass index (BMI), decreased age and glucose levels, leading to lower incidence of cardio metabolic diseases. Increased cold exposure in adult humans with undetectable BAT was associated with decreased body fat mass and increased insulin sensitivity. Deeper understanding of the role of BAT in human metabolic health and its inter-relationship with body fat distribution and deciphering proper strategies to increase energy expenditure by either increasing functional BAT mass, or inducing white adipose browning holds the promise for possible therapeutic avenues for the treatment of obesity and associated metabolic disorders.

There is great importance and need of improving existing carbon materials fabrication methods. As such, this work proposes to discuss, interrogate, and propose viable hydrothermal, solvothermal, and other advanced carbon materials synthetic methods. The advanced carbon materials to be interrogated will include the synthesis of carbon dots, carbon nanotubes, nitrogen/titania-doped carbons, graphene quantum dots, and their nanocomposites with solid/polymeric/metal oxide supports. This will be done with special mind to microwave-assisted solvothermal and hydrothermal synthesis due to their favourable properties such as rapidity, low cost, and green/environmentally-friendliness. Thus, these methods are important during the current and future synthesis and modification of advanced carbon materials for application in energy, gas separation, sensing, and water treatment. Simultaneously, the work will pay special cognizance to methods reducing the fabrication costs and environmental impact while enhancing the properties as a direct result of the synthesis methods. As a direct result, the expectation is to impart a significant contribution to the scientific body of work regarding the improvement of the said fabrication methods.

An attempt is made to model the atomic nucleus as a combination of bound and free or unbound nucleons. Due to strong interaction, bound nucleons help in increasing nuclear binding energy and due to electroweak interaction, free or unbound nucleons help in decreasing nuclear binding energy. In this context, with reference to proposed 4G model of final unification and strong interaction, recently we have developed a unified nuclear binding energy scheme with four simple terms, one energy coefficient of 10.1 MeV and two small numbers 0.0016 and 0.0019. In this paper, by eliminating the number 0.0019, we try to fine tune the estimation procedure of number of free or unbound nucleons pertaining to the second term with an energy coefficient of 11.9 MeV. It seems that, some kind of electroweak interaction is playing a strange role in maintaining free or unbound nucleons within the nucleus. It is possible to say that, strong interaction plays a vital role in increasing nuclear binding energy and electroweak interaction plays a vital role in reducing nuclear binding energy. Interesting observation is that, Z can be considered as a characteristic representation of range of number of bound isotopes of Z. For medium, heavy and super heavy atoms, beginning and ending mass numbers pertaining to bound states can be understood with 2Z+0.004Z^2 and 3Z+0.004Z^2 respectively. With further study, neutron drip lines can be understood. Based on this kind of data fitting procedure and by considering the mass ratio of pions and electroweak bosons, existence of our 4G model of electroweak fermion of rest energy 584.725 GeV can be confirmed confidently.

Background (1) In the time of the 4th Industrial Revolution or Industry 4.0, a conglomerate of technical and social inventions, political contexts, socio-cultural circumstances, environmental policies, business models, and economic policies has emerged. Sustainability policy in theory and practice aims to deal with the effects of all these factors and to try to make decisions that ensure both social and economic development sustainably. The question is how to familiarize oneself with the current knowledge about the relationship between Industry 4.0 and sustainability?; (2) Methods: This research utilizes an automated content analysis method to analyses scientific journals, newspapers and magazines. The comparison of results of both research group shows that the scientific literature focuses more on changes in business models, production processes and technologies that enable sustainable development; (3) We found that the scientific literature focuses more on changes in business models, production processes and technologies that enable sustainable development. Newspapers and magazines articles write more about sustainable or green investment, sustainable standards and sustainable reporting. Newspapers and magazines articles write more about sustainable or green investment, sustainable standards and sustainable reporting. Newspapers, as well as some latest research journals, include articles of the COVID-19 outbreak and its effect on the economy and the environment. Indeed, the outbreak of the virus brings a new thought to the reorganization of the complex relationships between consumers, businesses and the state; (4) Conclusions: According to the comparison of the analyses of the results, it can is that the analyses of both types of literature, both scientific and professional, shows that there are common topics they write about, which are related to the field of clean production, emissions, renewable energy, climate change, sustainable investments and corporate sustainability. An urgent global issue that extends all over the world is the promotion of energy-saving technologies and reduction of carbon dioxide emissions.

As on 31.03.2020, 55.4 % (205135 MW) of total installed capacity (370106 MW) in India is through coal and lignite based power plants. These plants, set up by central, state and private utilities with substantial capital investment are facing consistently reducing Plant Utilization Factor (known as Plant Load Factor, PLF, in India). In the year 2019-20 the national average thermal power PLF stood at 55.4%, down from 78.6 % in 2007-08. On the other hand, the electricity demand is consistently rising in the country and there exists a peak and energy shortage at national level. In 2019-20 energy shortage was 0.7 % and peak shortage was 0.5 %. A disturbing paradox therefore exists here. On one hand, the country is power deficit, and on the other hand, a large amount of coal based affordable power, ready to be generated by thermal power generators, remains grossly unused. Looking into the fact that considerable investment has gone into developing these thermal power generation assets in the country, the falling PLF is a matter of concern for all the key stakeholders including the power producers, lenders, regulators and consumers. This paper identifies seven major factors that are affecting PLF of thermal power plants and then makes an attempt to project future scenario of PLF so that critical stakeholders can intervene through appropriate actions. Primary research with responses from power professionals has been used to find out the major factors. Future projection of PLF has been done using Partial Least Square (PLS) regression. Projection shows that in the Business As Usual case (Factors increasing at the current CAGR rate), the thermal power plants will face very low level of PLF (14.76 %) by 2024-25. This will mean that many plants will be shut down and many will run for only few hours in a day that too at very low loads. If the future generation mix is kept as indicated by Central Electricity Authority (CEA), a Govt. of India in its report (Draft report on optimal generation capacity mix for 2029-30- CEA- Govt of India) then the thermal power plant average PLF can sustain above 68 % until 2024-25. If followed, this path can be a breather for the thermal power plants.

During the last years our society was permanently disturbed by the coherent information waves of high amplitudes. These are waves of huge social energy. Often they are of the destructive character, a kind of information tsunami. But, they can carry as well positive improvements in the human society, as waves of decision making matching rational recommendations of societal institutes. The main distinguishing features of these waves are their high amplitude, coherence (homogeneous character of social actions generated by them), and short time needed for their generation and relaxation. We show that such social phenomenon can be modeled on the basis of the recently developed social laser theory. This theory can be used to model stimulated amplification of coherent social actions. ``Actions'' are treated very generally, from mass protests to votes and other collective decisions, as, e.g., acceptance (often unconscious) of some societal recommendations. We point to the main distinguishing features of the modern society simplifying social lasing: a) transformation of humans into social atoms - lost of individuality; b) generation by mass-media of powerful information fields leading to information overload of social atoms; c) creation of powerful social resonators based on internet Echo Chambers. In this paper, we analyze in very detail their functioning leading to increasing of the power fo the quantum information field as well as its coherence.

Temperature differences between the atmosphere and river water allow rivers to be used as a hydrothermal energy source. The river-water heat pump system is a relatively non-invasive renewable energy source; however, effluent discharged from the heat pump can cause downstream temperature changes which may impact sensitive fluvial ecosystems. In this study, the water temperature recovery distance of the effluent was estimated for a river section in the Han River Basin, Korea, using the heat transfer equation and the Environmental Fluid Dynamic Code (EFDC) model. Results showed that, compared to the EFDC model, the heat transfer equation tended to overestimate the water temperature recovery distance due to its simplified assumptions. The water temperature recovery distance could also be used as an objective indicator to decide the reuse of downstream river water. Furthermore, as the river system was found to support an endangered fish species that is sensitive to water environment changes, care should be taken to exclude the habitats of protected species affected by water temperatures within water temperature recovery distance.

We explore the possibility to form a physical theory in $C^4$. We argue that the expansion of our usual 4-d real space-time to a 4-d complex space-time, can serve us to describe geometrically electromagnetism and nuclear fields and unify it with gravity, in a different way that Kaluza-Klein theories do. Specifically, the electromagnetic field $A_\mu$, is included in the free geodesic equation of $C^4$. By embedding our usual 4-d real space-time in the symplectic 8-d real space-time (symplectic $R^8$ is algebraically isomorphic to $C^4$), we derive the usual geodesic equation of a charged particle in gravitational field, plus new information which is interpreted. Afterwards, we formulate and explore the extended special relativity and extended general relativity an $C^4$ or$R^8$. After embedding our usual 4-d space-time in $R^8$, two new phenomena rise naturally, that are interpreted as "dark matter" and "dark energy". A new cosmological model is presented, while the geometrical terms associated with "dark matter" and "dark energy" are investigated. Similarities, patterns and differences between "dark matter", "dark energy", ordinary matter and radiation are presented, where "dark energy" is a dynamic entity and "dark matter" reveal itself as a "mediator" betwen ordinary matter and "dark energy". Moreover, "dark matter" is deeply connected with "dark energy". Furthermore, the extended Hamilton-Jacobi equation of the extended space-time, is transformed naturally as an extended Klein-Gordon equation, in order to get in contact with quantum theories. By solving the Klein-Gordon equation analytically, we derive an eigenvalue for Higg's boson mass value at 125,173945 $Gev/c^{2}$. The extended Klein-Gordon equation, also connects Higg's boson (or vacuum) with Cosmology, due to the existence of our second "time" T (cosmological time), which serve us to connect quantum theories with Cosmology. Afterwards, in the general case, we explore the symmetries of the curved Hamilton-Jacobi equation locally, in order to investigate the consequences of a $C^4$ space-time in Standard Model. An extension to Standard Model is revealed, especially in the sector of strong nuclear field. The Stiefel manifold $SU(4)/SU(2)$ seems capable not only to describe the strong nuclear field but give us,as well, enough room to explore in the future, the possibility to explain quark confinment. Our extension, flavors firstly the unification of nuclear fields and afterwards the unification of nuclear fields with electromagnetic field. The desired grand unification, is achieved locally, through the symmetry group $GL(4,C)\simeq SO(4,4)\cap U(4)$ and we present a potential mechanism to reduce the existing particle numbers to just six. Afterwards,23 present the extended Dirac equation in $C^4$ space-time (Majorana-Weyl representation) plus a preliminary attempt to introduce a pure geometric structure for fermions. Finally, we consider a new geometric structure through n-linear forms in order to give geometric explanation for quantisation

In this paper, the active front-end (AFE) converter topology for the total harmonic distortion (THD) reduction in a wind energy system (WES) is used. A higher THD results in serious pulsations in the wind turbine (WT) output power and in several power losses at the WES. The AFE converter topology improves capability, efficiency and reliability in the energy conversion devices; by modifying a conventional back-to-back converter, from using a single voltage source converter (VSC) to use pVSC connected in parallel the AFE converter is generated. The THD reduction is done by applying a different phase shift angle at the carrier of digital sinusoidal pulse width modulation (DSPWM) switching signals of each VSC. To verify the functionality of the proposed methodology, the WES simulation in Matlab-Simulink® is analyzed, and the experimental laboratory tests using the concept of rapid control prototyping and the real-time simulator Opal-RT® Technologies is achieved. The obtained results show a type-4 WT with total output power of 6MVA, generating a THD reduction up to 5.5 times at the WES.

The main foundations of the standard $\Lambda $CDM model of cosmology are that: 1) The redshifts of the galaxies are due to the expansion of the Universe plus peculiar motions; 2) The cosmic microwave background radiation and its anisotropies derive from the high energy primordial Universe when matter and radiation became decoupled; 3) The abundance pattern of the light elements is explained in terms of primordial nucleosynthesis; and 4) The formation and evolution of galaxies can be explained only in terms of gravitation within a inflation+dark matter+dark energy scenario. Numerous tests have been carried out on these ideas and, although the standard model works pretty well in fitting many observations, there are also many data that present apparent caveats to be understood with it. In this paper, I offer a review of these tests and problems, as well as some examples of alternative models.

The present review is related to the novel approach for improvement of the optical properties of wide bandgap metal oxides, in particular TiO2, based on the formation of the inorganic-organic hybrids that display absorption in the visible spectral range due to the formation of interfacial charge transfer (ICT) complexes. We outlined the property requirements of TiO2-based ICT complexes for efficient photo-induced catalytic reactions, emphasizing the simplicity of the synthetic procedure, the possibility of the fine-tuning of the optical properties supported by the density functional theory (DFT) calculations, and the formation of a covalent linkage between inorganic and organic components of hybrids, i.e., the nature of the interface. In addition, this study provides a comprehensive insight into potential applications of TiO2-based ICT complexes in photo-driven catalytic reactions (water splitting and degradation of organic molecules), including the identification of reactive species that participate in photocatalytic reactions by the spin-trapping electron paramagnetic resonance (EPR) technique. Considering the practically limitless number of combinations between inorganic and organic components capable of forming oxide-based ICT complexes and with the knowledge that this research area is unexplored, we are confident it is worth studying, and we emphasized some further perspectives.

A theory for the micelle formation of nonionic head-tail amphiphiles (detergents) in aqueous solutions is derived based on the traditional molecular thermodynamic modeling approach and a variant of Flory-Huggins theory that goes beyond lattice models. The theory is used to analyze experimental values for the critical micelle concentration of n-alkyl-ß-D-maltosides within a mass action model. To correlate those parts of the micellization free energy, that depend on the transfer of hydrophobic molecule parts into the aqueous phase, with molecular surfaces, known data for the solubility of alkanes in water are reanalyzed. The correct surface tension to be used in connection with the solvent excluded surface of the alky tail is 30 mN/m. This value is smaller than the measured surface tension of a macroscopic alkane-water interface, because the transfer free energy contains a contribution from the incorporation of the alkane or alkyl chain into water representing the change in free volume of the aqueous phase. Flory-Huggins theory works well, if one takes into account the difference in liberation free energy between micelles and monomers, which can be described in terms of the aggregation number as well as the thermal deBroglie wavelength and the free volume of the detergent monomer.

The hetero Diels-Alder (HDA) reaction between the ambident heterodiene 3-methylene-2,4-chromandione (MCDO) and the non-symmetric methyl vinyl ether (MVE) is investigated within the Molecular Electron Density Theory (MEDT) at the B3LYP/6-311G(d,p) computational level. The aim of this study is to gain insight into the molecular mechanism and to elucidate the factors that control the selectivity found experimentally. DFT-based reactivity indices reveal that MCDO exhibits strong electrophilic character, while MVE displays a strong nucleophilic character. Meanwhile, Parr function explains the ortho regioselectivity of this HDA reaction. The highly polar nature of this HDA reaction, supported by the high global electron density transfer (GEDT) taking place at the transition state structures (TSs), accounts for the very low activation energy associated with the most favorable TS-4on. The ambident nature of MCDO allows the formation of two constitutional isomeric cycloadduct. In the case of MVE, the pseudocyclic selectivity is attained by a thermodynamic control. This polar HDA reaction displays an endo stereoselectivity and a complete ortho regioselectivity. A comparative Relative Interacting Atomic Energy (RIAE) analysis of the two diastereomeric TS-4on and TS-6on indicates a highly likeness between them, which explains the low pseudocyclic selectivity under kinetic control.

Tidal energy, with its potential to provide a consistent energy output and reduce carbon emis-sions, has garnered significant interest. This study, which is the first to evaluate the performance of tidal turbines in seawater conditions involving sand particles, presents a novel approach. A slurry rig was developed to examine composite materials, and a glass fibre reinforcement poly-meric material was tested over a range of particle size, velocity, impact angle, and exposure time. The results, which show significant changes in the mass loss materials as a function of these variables, have profound implications for the design and performance of tidal turbines. The study also utilized a scanning electron microscope (SEM) and depth profiling analysis, and erosion maps were generated to demonstrate the changes in erosion mechanisms. These tools can be used to optimize such materials in tidal turbine conditions.

This paper describes a Long Short-Term Memory (LSTM) neural network model used to simulate the dynamics of the OC3 reference design of a Floating Offshore Wind Turbine Spar unit. It crafts an advanced neural network with an encoder-decoder architecture capable of predicting the Spar’s motion and fairlead tensions time series. These predictions are based on wind and wave excitations across various operational and extreme conditions. The LSTM network, trained on an extensive dataset from over 300 fully coupled simulation scenarios using OpenFAST, ensures a robust framework that captures the complex dynamics of floating platform under diverse environmental scenarios. This framework’s effectiveness is further verified by thoroughly evaluating the model’s performance, leveraging comparative statistics and accuracy assessments to highlight its reliability. This methodology contributes to substantial reductions in computational time. This research aims to provide critical insights that facilitate the optimization of offshore wind turbines, marking a step forward in the quest for more efficient and dependable renewable energy solutions.

The paper addresses the energy consumption minimization problem in wireless powered communication networks (WPCNs) and proposes a DT-SWIPT-assisted time allocation scheme, named DaTA, such that the wireless station can share the remaining energy after transmission to the HAP to those who have not transmitted to the HAP to minimize the energy consumption of the network. In addition to proposing a new frame structure, the paper also considers the SNR (Signal-to-Noise) constraint to guarantee that the HAP can successfully receive data from wireless stations. In the paper, the energy consumption minimization problem is formulated as a nonlinear programming model. We employ the SQP (Sequential Quadratic Programming) algorithm to figure out the optimal solution. Moreover, a heuristic method is proposed as well to obtain a near-optimal solution in a shorter time. Simulation results showed that the proposed scheme can have better performance than the related work in terms of energy consumption and energy efficiency.

This paper introduces a structured design for an effective power-sharing technique among converter-interfaced distributed generation (DG) units within a microgrid that operates without a synchronous generator. The proposed power-sharing technique leverages the battery energy storage system (BESS) to promptly respond to network changes. The real power output of each commercial distributed energy resources (CDER) unit is governed by a frequency-droop characteristic and a complementary frequency restoration strategy. Deloading techniques are employed by solar and wind power generators to enhance response during power supply or demand disturbances. To ensure microgrid stability, small-signal analysis is conducted for controller design, including the determination of stability margins. Initial tuning of the power-sharing technique parameters is achieved using the Ziegler-Nichols Method, followed by further optimization through a meta-heuristical algorithm to enhance the response time of energy sources. The proposed power-sharing technique's performance is evaluated on a benchmark medium voltage network using industry-standard commercial software. The test results demonstrate the precise and rapid power-sharing capabilities among DGs facilitated by the proposed technique, highlighting its effectiveness in dynamic microgrid environments.

This paper investigates if the polar groups induced by a plasma treatment can increase the lap shear strength of laser joined metal and plastic hybrids. Optimal laser joining parameters for cold-rolled AISI304 – Polyamide 6.6 and sandblasted AISI304 - Polypropylene hybrids are developed. The OWRK-method was utilized to identify the change in surface free energy of a low-pressure plasma treatment. Plasma treated samples were joined and tested. The fractured surfaces were investigated via light microscopy and SEM. The arithmetic means of the plasma treated hybrids lap shear strength with polyamide 6.6 varied slightly but all measured values were within the range of the untreated samples. The lap shear strengths of the polypropylene hybrids were significantly reduced. This was attributed to an overaging and the development of low molecular weight oxidized materials which lead to a weak boundary layer. No correlation between surface free energy and the lap shear strength could be found.

This study investigates the effectiveness of a range of timber-based solutions for seismic and energy retrofitting of existing masonry buildings. These solutions are designed not only to prevent structural collapse during earthquakes but also to create integrated interventions that enhance thermo-physical performance and reduce emissions in existing buildings. Various case scenarios were considered and both mechanical and energetic behavior post-intervention were evaluated. Timber-engineered products serve as foundational components for the retrofit approach, encompassing one-dimensional vertical elements (strong-backs) and various types of panels (cross-laminated timber panels, laminated veneer lumber panels, and oriented strand board panels). The analyzed retrofit techniques share a common principle, involving the attachment of these timber-based elements to the building's wall surfaces through mechanical point-to-point connections. The proposed solutions integrate strong-backs and timber panels with membranes and insulation layers, yielding cohesive and highly effective interventions. Finite element modeling was employed to analyze the mechanical and thermal responses of the retrofitted walls. A comprehensive comparative analysis of various techniques was conducted to determine the most effective solution for each specific scenario.

As renewable energy generation prediction systems have been introduced into the energy trading market, accurate prediction of solar photovoltaic (PV) energy generation has become a crucial challenge for ensuring stable trade of variable energy. Therefore, it is essential to quantitatively investigate and analyze current prediction technology and develop more advanced prediction systems. In this study, three models for predicting PV energy generation were investigated. Multiple regression, random forest, and gradient boosting machine (GBM) models were con-structed for 15 utility-scale power plants throughout South Korea. Model performance was evaluated in terms of root mean square error (RMSE) and mean absolute error (MAE). The multiple regression-based model had an RMSE of 12.00% and MAE of 9.06%. The random forest model had an RMSE of 11.69% and MAE of 8.61%. The GBM model had an RMSE of 11.34% and MAE of 8.18%, indicating its superior accuracy among the three models in predicting PV energy generation. These findings provide valuable insights that may contribute to the development of advanced PV energy generation models and their application in grid operations.

The epistemology of the traditional risk assessment examined has a taxonomy based upon deterministic, behaviouristic and compatibilist methodologies which are likely driven by neo-liberal market related requirements for bigger, faster cheaper wind-turbines. Analysis of available risk assessments suggested that there is no conscious effort to deceive the reader although the intended audience is unclear. The language, and scoring mechanisms utilized indicates the presence of conformity bias, confirmation bias, and numerical inconsistency leading to data ossification. By reverse engineering risk assessment content, Pragmatic and Social Psychological aspects can be investigated, and the adequacy of the document can be evaluated using evidence-based models.

In Germany, as in many developed countries, over 60% of buildings were constructed before 1978, where most are in critical condition, requiring either demolition with plans for redevelopment or renovation and rehabilitation. Given the urgency of climate action and relevant sustainable development goals set by the United Nations, more attention must be shifted toward the various sustainability aspects when deciding on the strategy for renovation or redevelopment of existing buildings. To this end, this study focused on developing a smart decision support framework for aging buildings based on lifecycle sustainability considerations. The framework integrated digital technological advancements, such as building information modeling (BIM), point clouds processing with field information modeling (FIM)®, and structural optimization, together with life-cycle assessment to evaluate and rate the environmental impact of different solutions. Three sustainability aspects, namely, cost, energy consumption, and carbon emissions, were quantitatively evaluated and compared in two scenarios, namely, renovation, and demolition or deconstruction combined with redevelopment. A real building constructed in 1961 was the subject of the experiments to validate the framework. The result outlined the limitations and advantages of each method in terms of economics and environmental impact. It was further observed that optimizing the building design with the goal to reduce embodied energy and carbon in compliance with modern energy standards, was crucial to improve overall energy performance. This work demonstrated that the developed BIM-based framework to assess the environmental impact of rehabilitation work in aging buildings can provide effective ratings to guide decision-making in real-world projects.

We report a preliminary exploration on the low-pressure Ar-O2 plasma generated by low-frequency alternating current (AC) power supply in the low-temperature Plasma Experimental Power Supply (CTP-2000S) for the first time. The electron density 〖(n〗_e), the electron temperature 〖(T〗_e) and the electron energy distribution function (EEDF) are measured by the single Langmuir probe in this experiment. Experimental results show that the ne increases with gas pressure rising, while the ne decreases with the oxygen concentrations rising. And, a plasma density peak is also observed with the AC power supply increase. A comparison between this work and the previous results by RF source suggests that the low-frequency AC power supply may be very fruitful exploration to generate the low-pressure plasma.

Material identification based on R_value (transparency natural logarithm ratio of low-energy to high-energy) of line-scan dual-energy X-ray transmission (DE-XRT) has a good prospect for industrial application. Unfortunately, the DE-XRT signals before attenuation cannot be directly measured, whereas their precision is very important to R_value. Therefore, a context-based signal synthesis method which takes the filtered signals that remove high-frequency noises and retain low-frequency actual fluctuations as the reference value, and takes into account the vertical (forward/column) direction and horizontal (scanning/row) direction anisotropy of line-scan images was proposed. The vertical is a time series with continuity of signal trend; the horizontal is a spatial characteristic with the fluctuation synchronization within the same row signals. The special synthesis evaluations of curve synthesis difference and surface synthesis difference were also proposed. Experimental results show that the tow evaluations are both only about 0.0007, and it only takes 35 ms to complete the surface synthesis of 119×119 pixels on the CPU with 3.4 GHz main frequency. The presented method can achieve high signal synthesis precision and calculation real-time, so as to facilitate DE-XRT material identification. It can be extended to improve the precision of numerical synthesis in other line-scan uncomplete signals.

Nuclear technologies have a strong potential and a unique role to play in delivering reliable low carbon energy for a future net-zero society. However, to assure the sustainability required for the long-term success, nuclear will need to deliver innovative solutions as proposed in iMAGINE. One of the most attractive features, but also a key challenge for the envisaged highly integrated nuclear energy system is the need for a demand driven salt clean-up system. The work described provides an insight into the interplay between a potential salt clean-up system and the reactor operation in a plutonium started core in a dynamic approach. The results presented will help to optimize the parameters for the salt clean-up process as well as to understand the differences which appear between a core started with enriched Uranium and Plutonium as the fissile material. The integrated model is used to investigate the effects of the initial fissile material on core size, achievable burnup, and long term operation. Different approaches are tested to achieve a higher burnup in the significantly smaller Pu driven core. The effects of different clean-up system throughputs on the concentration of fission products in the reactor salt and its consequences are discussed for general molten salt reactor design. Finally, an investigation of how a plutonium loaded core could be used to provide fuel for future reactors through fuel salt splitting is presented with the outcome that one Pu started reactor of the same size as a uranium started core could deliver fuel for 1.5 new cores due to enhanced breeding. The results provide an essential understanding for the progress of iMAGINE as well as the basis for inter-disciplinary work required for optimizing iMAGINE.

The steel damper column is an energy-dissipating member that is suitable for reinforced concrete (RC) buildings, and those used for multistory housing in particular. However, the effectiveness of steel damper columns may be affected by the behavior of surrounding members, and this effect can be severe in the case of seismic sequences. This article investigates the nonlinear response of building models having an RC moment-resisting frame (MRF) with and without steel damper columns under seismic sequences. The applicability of the concept of the momentary energy input to the prediction of the peak response of RC MRFs with damper columns under seismic sequences is also investigated. The main findings of the study are summarized as follows. (1) The peak response of RC MRFs with damper columns subjected to sequential accelerations is similar to the peak response obtained considering only the mainshock, whereas the cumulative strain energy of RC MRFs accumulates more for sequential accelerations. (2) The steel damper column is effective in reducing the peak and cumulative responses of RC MRFs in the case of sequential seismic input. (3) The relation of the hysteretic dissipated energy during a half cycle of the structural response and the peak displacement of the first modal response can be properly evaluated using the simple model proposed in this study.

The article presents a method of generating Key Performance Indicators related to electric motor energy efficiency on the basis of Big Data gathered and processed in frequency converter. The authors proved that using the proposed solution it is possible to specify the relation between the control mode of an electric drive and the control quality-energy consumption ratio in the start-up phase as well as in the steady operation with various mechanical loads. The tests were carried out on a stand equipped with two electric motors (one driving, the other used to apply the load by adjusting the parameters of the built-in brake). The measurements were made in two load cases, for motor control modes available in industrially applied frequency converters (scalar V/f, vector Voltage Flux Control without encoder, vector Voltage Flux Control with encoder, vector Current Flux Control and Vector Current Flux Control with torque control). During the experiments values of current intensities (active and output), the actual frequency value, IxT utilization factor, relative torque and the current rotational speed were measured and processed. Based on the data the level of the energy efficiency was determined for various control modes.

Space-time evolution is briefly explained by using the 3-dimensional quantized space model (TQSM) based on the 4-dimensional (4-D) Euclidean space. The energy (mass), charges and absolute time are newly defined based on the 4-D Euclidean space. The photons and gravitons are understood as the 2-D space fluctuations along the space axes and 1-D time fluctuations along the time axis, respectively. This indicates that the electromagnetic (EM) and gravitational (G) waves can be unified into the so called gravityelectromagnetic (GEM) wave which has both space and time fluctuations. The photon with zero force fields is the 2EM wave because an EM wave corresponds to a charged fermion. The dark matter bosons, weak force bosons, strong force bosons are the 1-D time fluctuations which can be expressed by the G waves. This indicates that all five forces are unified by the GEM wave. It is called as the super unification theory in the present work. And the force carrying bosons and mesons are, for the first time, proposed as the possible candidates of the magnetic monopoles like the fermions and baryons are the electric monopoles. The signs of the magnetic charges quantized as q_m=cq are newly defined. The big bang is understood by the space-time evolution of the 4-D Euclidean space but not by the sudden 4-D Minkowski space-time creation. The big bang process created the matter universe with the positive energy and the partner anti-matter universe with the negative energy from the CPT symmetry.

Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Risks are increasing and conditions deteriorating. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached and understood. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory that is intended to serve as the foundation for the R&D program.