Due to various industrial developments and artificial inputs, there are emerging environmental contaminats(ECs) of serious concern in a wide range of environmental media. With recent advancements in scientific knowledge and industrial technology, the definition of emerging environmental contaminats has expanded. Among them, emerging contaminants are typically present in trace amounts and pose serious ecological risks and potential hazards to human health, animals and plants, with cumulative effects on organisms. However, Traditional treatment techniques have proven ineffective in eliminating and preventing subsequent environmental problems from new pollutants such as microplastics, antibiotics and fluorocarbons. Consequently, extensive research has been conducted to address these issues. Effective removal methods prioritize not only removal efficiency, but also environmental friendliness and regenerative capacity. The purpose of this paper is to summarize the sources, forms of presence, environmental and human health hazards, and removal technologies of ECs, and to provide various examples of different sources.

In the face of the burgeoning electricity demands and the imperative for sustainable development amidst rapid industrialization, this study introduces a dynamic and adaptable framework suitable for policy-makers and renewable energy experts working on integrating and optimizing renewable energy solutions. While using a case study representative model for Sub-Saharan Africa (SSA) to demonstrate the challenges and opportunities present in introducing optimization methods to bridge power supply deficits and the scalability of the model to other regions, this study presents an agile multi-criteria decision tool that pivots on four key development phases, advancing upon established methodologies and pioneering refined computational techniques, to select optimal configurations from a set of Policy Decision Making Metrics (PDM-DPS). Central to this investigation lies a rigorous comparative analysis of variants of three advanced algorithmic approaches: Swarm-Based Multi-objective Particle Swarm Optimization (MOPSO), Decomposition-Based Multi-objective Evolutionary Algorithm (MOEA/D), and Evolutionary-Based Strength Pareto Evolutionary Algorithm (SPEA2). These are applied to a grid-connected hybrid system, evaluated through a comprehensive 8760-hour simulation over a 20-year planning horizon. The evaluation is further enhanced by a set of refined Algorithm Performance Evaluation Metrics (AL-PEM) tailored to the specific constraints. The findings not only underscore the robustness and consistency of the SPEA2 variant over 15 runs of 200 generations each, which ranks first on the AL-PEM scale but also validate the strategic merit of combining multiple technologies and empowering policymakers with a versatile toolkit for informed decision-making.

This study examines the environmental challenges faced by Malaysian industries in adhering to industrial effluent regulations with the research question, what are the challenges in complying with environmental legislations from industries? It investigates the primary factors contributing to non-compliance and the perspectives, knowledge, and needs of Malaysian industries regarding environmental compliance. This study recommends the best strategy for promoting self-compliance. Thirteen stakeholders from various industries with environmental management experience were interviewed. Over the past seven years, these industries have shown low com-pliance with the Industrial Effluent Regulation 2009, prompting an exploration of their adaptability to regulations. Challenges identified include cost, employee attitudes, technology, management support, public complaints, and jurisdictional issues. Responses varied from divergent to unified viewpoints, highlighting the complexity of compliance issues. Respondents suggested enhancing compliance through behavioral changes, including incentives, enforcement, awareness, guidance, industry ratings, management commitment, and public disclosure of emissions. Suggestions for improvement and innovative solutions emerged based on participants' experiences, emphasizing the importance of continuous improvement. The study emphasizes the government's crucial role in ensuring regulation adherence but underscores the need for analyzing barriers and exploring alternative approaches. Understanding industry perspectives and strategies is essential for progress. Compliance, however, requires an analysis of the current challenges and adopting adaptive measures. It is important to understand industries' perspectives and strategies to move forward.

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

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

Defining integrals over volume element in curved spacetime together with the mass and energy densities within that region of spacetime is apparently equivalent to the given energy and mass of that body or particle. With this in mind equations involving energies and mass can be rewritten in terms of their densities and the integral over the volume element. The idea find its place in the Hamiltonian formulations, and can be carried over into quantum mechanical frameworks systematically accounting for the effect of spacetime volume structures and gravity on dynamics of quantum systems. This article briefly explores this concept and runs through various frameworks and equations relevant to this idea, particularly the schrodinger-Newton equation and discusses the cosmological constant as a vacuum energy density.

The sound power LW of wind turbines (WTs) over the past decades has developed in relation to their electric power P as LW ∝ logP. The spectral distribution of the sound did not change significantly over time. This applies to the average performance of wind turbines, with differences between individual WT types. Because of the expected growth of onshore wind energy, a greater number of people will be living close to wind farms. This sustains the need for sound reduction. Sound reduction measures, such as serrations, reduced tip speed and low noise modes, may counteract the development of higher sound power from ever bigger WTs. To investigate this, the sound production of WT types over the last decades is analysed in relation to their size and electric power and the application of sound reduction measures. The analysis includes the broad band A-weighted and low frequency sound power levels as well as more detailed spectral distributions. Results show that the sound power level of wind turbines above 3 MW on average increases less with size than smaller turbines did. This is due to a lower blade tip speed and the use of sound reducing serrations. The spectral content of wind turbine sound, including the lower frequencies, has not changed significantly.

The experience of ego dissolution and self-transcendence induced by psychedelic substances offers a profound challenge to our conventional understanding of the self and our relationship with the natural world. This paper delves into the philosophical underpinnings and implications of this phenomenon, exploring how the temporary breakdown of ego boundaries during a psychedelic experience may foster a sense of profound interconnectedness with nature. Drawing from Western and Eastern philosophical traditions, as well as recent insights from neuroscience and consciousness studies, we examine the potential of psychedelic-induced self-transcendence to catalyze a shift in our perspectives on the human-nature relationship. The paper investigates the philosophical implications of this experience, including its resonance with deep ecological philosophies and its potential to inspire more ecocentric ethical frameworks. Furthermore, we explore the possible practical implications of fostering a sense of ecological connectedness through psychedelics, such as promoting environmentally sustainable behaviors and addressing the pressing challenges of climate change and ecological degradation. Ultimately, this exploration highlights the value of engaging with altered states of consciousness as a means to reconsider our place within the intricate web of life on Earth.

Globally, habitat fragmentation has increased the proximity between wildlife, humans, and emerging predators such as free-ranging dogs. In these fragmented landscapes, encounters between primates and dogs are escalating, with primates often falling victim to dog attacks while navigating patchy landscapes and fragmented forests. We aim to investigate how these primates deal with the simultaneous threats posed by humans and predators, specifically focusing on the adaptive strategies of Central Himalayan Langur (CHL) in the landscape of fear. To address this, we conducted a behavioral study on the CHL in an agro-forest landscape, studying them for a total of 3912 hours over two consecutive years. Our results indicate that, compared to their most common resting behavior, CHL allocate more time to feeding and locomotion, and less time to socializing in the presence of humans and predatory dogs. Additionally, they exhibit increased feeding and locomotion and reduced social behavior in agro-forest or open habitats. These behavioral patterns reflect adaptive responses to the landscape of fear, where the presence of predators significantly influences their behavior and resource utilization. This study suggests measures to promote coexistence between humans and wildlife through the integration of effective management strategies that incorporate both ecological and social dimensions of human-wildlife interactions.

This article presents multiple novel and compelling arguments to systematically disprove two widely accepted notions: one is that entropy is a measure of disorder, and the other is Schrödinger's notion of negative entropy (negentropy). These two notions have been cited hundreds of times annually in scientific literature for decades. To mathematically describe the second law of thermodynamics, the concept of entropy was created and defined in the 1860s as heat energy divided by thermodynamic temperature, and the entropy of an object increases when it absorbs heat. This is the uncontroversial and fundamental nature of entropy, which is pivotal to current thermodynamics and from which multiple facts are deduced. These facts consistently disprove the above two notions. Some biological facts, such as the one that life orderliness is encoded and provided by inherited genes rather than entropy decline, can also disprove Schrödinger's negentropy notion. Moreover, this article further clarifies the reasoning errors of the two notions. It also shows that the tendency of many natural or social systems to become more disordered over time does not result from the second law of thermodynamics.

The rise of fintech in the financial sector presents a transformative shift towards digitalization and sustainability, leveraging technologies like AI to minimize environmental footprint. Neobanks not only challenge traditional banking models but also offer innovative solutions that align with sustainable objectives. The purpose of this paper is to analyze the impact of neobanks on global sustainability, from economic, environmental, and social point of view. A comprehensive literature review of existing literature and current sustainable practices of neobanks was conducted. We have found that neobanks significantly positively contribute towards environmental sustainability with reduced paper use and logistics requirements of banking services. By offering more accessible and affordable banking services they importantly contribute towards higher financial inclusion, and with innovative products towards more competitive and innovative financial markets. AI-based tools they employ are increasing financial literacy and social inclusion. We also highlight concerns regarding electronic waste management, potential high energy consumption, required digital literacy and cybersecurity risks. We conclude that despite the mentioned risks, neobanks importantly contribute to global sustainability in many ways, and will even more in the future. Our findings can help neobanks shape sustainable practices and guide policymaking, as well as spread awareness of sustainable impact of banking services.

Low energy consumption is a significant contribution of new and retrofitted buildings that place an emphasis on energy efficiency. Although the mandatory requirements of the U-factor and R-value are described in the Vietnamese National Technical Regulation on the energy efficiency of buildings—QCVN09:2017/BXD, these values are not widely publicized, leading to designers facing difficulties when choosing suitable materials at the design stage. This study focuses on the method used to declare the heat transfer values of building materials based on the energy labeling process in order to create an energy labeling program for building materials. To accomplish this objective, criteria and labeling procedures for windows, doors, walls, and building roofs have been developed. In addition, a case study of insulation product labeling was used to evaluate the applicability of the developed labeling program in the implementation phase.

Most existing coal-fired power plants were designed for sustained operation at full load to maximize efficiency, reliability, and revenue, as well as to operate air pollution control devices at design conditions. Depending on plant type and design, these plants can adjust output within a fixed range in response to the plant operating or market conditions. The need for flexibility driven by increased penetration of variable and non-dispatchable power generation such as wind and solar is shifting the traditional mission profile of thermoelectric power plants in three ways: more frequent shutdowns when market or grid conditions warrant, more aggressive load ramp rates (rate of output change), and lower minimum sustainable load, which provides a wider operating range and helps avoid costly plant shutdowns. Recent studies have shown that flexibility of a coal-fired power plant can be improved by energy storage. The objective of this work was to analyze a set of energy storage options and determine their impact on flexibility and economics of a representative coal-fired power plant. The effect of three energy storage systems integrated with a coal power plant on plant flexibility and economics was investigated. The results obtained in this project show that Energy Storage Systems integrated with a thermal power plant improves plant flexibility and participation in the Energy and Ancillary Services markets which improves plant financial performance. The study was funded by the U.S. Department Office of Fossil Energy FE-1 under Award Number DE-FE0031903.

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

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

Transition to renewable energy has been recognized as a crucial step to addressing climate change and achieving greenhouse gas reduction targets, but it can also cause energy sprawl if not planned properly. Clean renewable energy communities (CREC) are emerging globally as an approach for decentralized energy systems and an alternative to traditional centralized energy systems. CREC aims to lower the energy carbon footprint, enhance local energy resilience, and improve the quality of life of residents. Through a comprehensive literature review, this study reviews metrics that can assess the impact of energy transition plans and support decision-making to select technologies that create efficient, reliable, and accessible energy systems. It classifies these metrics into a five-dimensional sustainability approach: environmental, technical, social, economic, political and institutional. The paper proposes a conceptual framework to guide decision-makers in recognizing the role of sustainable land development, sustainable energy planning, and resiliency as an integrated approach to energy transition planning. This framework stresses mapping the place-based potential for clean renewable energy at various scales, highlights the importance of resilience in energy planning, and addresses challenges associated with energy source selection, built environment efficiency, and energy trade. While the framework can serve as a starting point for evaluating energy transition plans, further work is needed to address the limitations of existing metrics and identify additional evaluations for energy mixed land use that are critical to managing energy sprawl on ecosystem services and other land uses.

This paper investigates the effects of various process parameters, specifically the substrate temperature, on weld track geometry in Directed Energy Deposition (DED) processes. A specialized experimental setup integrated within a DED machine facilitates controlled thermal conditioning of sample sheets. Through Design of Experiments (DoE) methods, individual weld marks are generated and analysed to assess geometric characteristics. Regression models are constructed to predict machine parameters for desired weld geometry at different substrate temperatures. Validation experiments confirm the accuracy and reliability of the regression models. Results show a consistent trend towards target geometric features across a broad range of substrate temperatures. Despite deviations in measured values, successful fabrication is achieved, demonstrating robust bonding between weld and substrate. Contact angle predictions exhibit precision within a partial temperature range for proper deposition. The developed model offers insights for optimizing DED process parameters to achieve desired weld characteristics, advancing the capabilities and reliability of additive manufacturing technology. Future work aims to refine the regression model and explore additional mathematical relationships for enhanced accuracy. An implication of this work is the potential to vary the local mechanical properties of parts by controlling the temperature profile while maintaining consistent geometric characteristics. By manipulating the substrate temperature, it may be possible to tailor the microstructure and mechanical properties of fabricated components in the future to meet specific requirements in different regions of the part.

Previous research has proven that one of the fundamental requirements for ensuring increased profitability and economic competitiveness of offshore-based projects is co-locating different technologies within the same marine space. This paper presents a number of techno-feasibility analyses for floating offshore technologies for the Maltese Islands, located in the Central Mediterranean Sea. The first part compares the feasibility of offshore-based solar photovoltaic prices with those onshore, taking into consideration Malta’s land prices. The second part considers the use of a novel floating breakwater design that integrates energy storage. The breakwater is used to create a sheltered water area in deep waters for a multi-use marine park. Different revenue streams for the floating break water are considered, including renting the sheltered marine space out to operators of floating solar farms, aquaculture cages and vessel berthing facilities, and the provision of energy storage services. It is found that the combined income from the multiple revenue streams is still insufficient to justify the investment and that financially support from Government is essential to render the floating breakwaters viable.

The implementation of sustainable practices, such as the use of renewable sources and efficient technologies, is crucial for reducing climate change. Energy efficiency is highly important on a global scale due to its relationship with climate change, aiming to minimize environmental impact. In Spain, renewable energy policies have increased self-sufficiency and reduced the use of fossil fuels. Optimizing energy consumption in residences, buildings, and industries is essential for improving efficiency. This was taken into consideration for conducting this study, focusing on the residential sector. The desire to understand the level of energy efficiency in Extremadura drove this project, which focuses on collecting and analyzing data on a set of homes located in the au-tonomous community of Extremadura, with the purpose of evaluating their energy efficiency. To achieve this, a computer tool will be employed to provide a detailed view of the different levels of energy efficiency present in the community. In addition to data collection and analysis, research will be conducted to identify areas for improvement. This will allow proposing a series of specific measures that users can implement to optimize energy efficiency in their homes, adapting them to the particular characteristics of each residence.

The manuscript presents the use of three novel technologies for the implementation of wireless green battery-less sensors that can be used in agriculture. The three technologies, namely additive manufacturing, energy harvesting, and wireless power transfer from airborne transmitters carried from UAVs, are considered for smart agriculture applications. Additive manufacturing is exploited for the implementation of both RFID based sensors and passive sensors based on humidity sensitive materials. A number of energy-harvesting systems at UHF and ISM frequencies are presented which are in position to power platforms of wireless sensors, including humidity and temperature IC sensors used as agriculture sensors. Finally, in order to provide the wireless energy to the soil-based sensors with energy harvesting features, wireless power transfer (WPT) from UAV carried transmitters is utilized. The use of these novel technologies can facilitate the extensive use and exploitation of battery-less wireless sensors which are environmentally friendly and thus “green”. Additionally, it can potentially drive precision agriculture in the next era, through the implementation of a vast network of wireless green sensors which can collect and communicate data, to airborne readers so as to support with data the Artificial Intelligence and Machine Learning based, decision making platforms.

To achieve rapid post-earthquake repair of self-centering ribbed floor flat beam frame structures, a ductile hybrid joint consisting of dog bone weakened energy dissipating steel bars connected to the upper and lower column sections through high-strength threads based on the damage control design concept is proposed. By moving the ductile energy dissipating zone out to the locally weakened section of the energy dissipating steel bars and the locally unbonded prestressed steel bars in the core area, the residual deformation was limited and the seismic performance was improved. Based on the working principle of hybrid joints, low cycle loading tests were conducted on two joint specimens to analyze the influence of lateral prestress on the seismic performance of the hybrid joints. Numerical modeling methods were used to compare the position of the energy-consuming steel bars in the composite layer and the friction performance of joints. The research results indicated that the hybrid joint had stable load-bearing, deformation, and energy dissipation capabilities, with damage primarily concentrated on the energy-consuming steel bars. Even at an inter-story displacement angle of 5.5%, the upper and lower column segments remained elastic. After unloading, the connection seam at the joint was closed, and the self-centering performance was good. When the inter-story displacement angle reached 5.5%, the lateral prestress increased from 150 kN to 250 kN, the ultimate bearing capacity of the joint increased by 16.3%, and the cumulative energy consumption increased by 30.0%. The influence of the friction coefficient of the joint surface on the structural performance was set at a threshold of 0.7. When it was less than the threshold, the ultimate bearing capacity and initial stiffness of the joint increased with an increase in the friction coefficient. After reaching the threshold, the increase in the ultimate bearing capacity of the joint slowed down, and the rate of stiffness degradation gradually accelerated. This joint had excellent seismic performance and can also achieve post-earthquake repair of structures.

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

Inverse gas chromatography at infinite dilution was used to determine the surface thermodynamic properties of silica particles and PMMA adsorbed on silica, and more particularly, to quantify the London dispersive energy γsd, the Lewis acid γs+ and base γs- polar surface energies of PMMA/silica composites as a function of the temperature and the recovery fraction θ of PMMA. The polar acid–base surface energy γsAB and the total surface energy of the different composites were then deduced as a function of the temperature. In this paper, the Hamieh thermal model was used to quantify the surface thermodynamic energy of poly methyl methacrylate (PMMA) adsorbed on silica particles at different recovery fractions. A comparison of the new results was carried out with those obtained by applying other molecular models of the surface areas of organic molecules adsorbed on the different solid substrates. An important deviation of these molecular models from the thermal model was proved. The determination of γsd, γs+, γs-, and γsAB of PMMA in both bulk and adsorbed phases showed an important non-linearity variation of these surface parameters as a function of the temperature. The presence of maxima in the curves of γsd(T) highlighted the second order transition temperatures in PMMA showing beta-relaxation, glass transition and liquid-liquid temperatures. These three transition temperatures depended on the adsorption rate of PMMA on silica. The proposed method gave a new relation between the recovery fraction of PMMA and its London dispersive energy showing an important effect of the temperature on the surface energy parameters of adsorption of PMMA on silica. A universal equation relating γsd(T,θ) of the systems PMMA/silica to the recovery fraction and the temperature was proposed.

As a result of increased energy consumption, global trade has surged, and serious environmental problems have arisen. The problem is made more complicated by the fact that either environmental damage or economic advancement cannot be compromised. The elements contributing to environmental contamination must be identified and dealt with accordingly if we are to have a healthier future. In this study, what causes CO₂ emissions in Malaysia are examined using the Autoregressive distributed lag (ARDL) model using time series data from 1995 to 2020. The paper also examines the impact of energy use and economic complexity on CO2 emissions. Firstly, it is noted that the Environmental Kuznets Curve (EKC) theory holds in Malaysia. Furthermore, energy consumption has a detrimental impact on reducing CO2 emissions. Furthermore, it has been noted that a greater degree of economic complexity leads to an elevated amount of CO2 emissions over an extended period. The findings suggest significant environmental policy implications for reducing CO2 emissions in Malaysia.

This article explores the cutting-edge advancement of gypsum and cement building boards infused with shape-stabilized n-octadecane, an organic phase change material (PCM). The primary focus is on improving energy efficiency and providing electromagnetic interference (EMI) shielding capabilities for contemporary buildings. The research investigates the integration of these materials into construction materials, using red-mud Carbon Foam as a stabilizer for n-octadecane (OD@CCF). Various analyses, including microstructural examination, porosity assessment, and additive dispersion, were conducted using X-ray microtomography and density measurements. Thermal conductivity measurements demonstrated the enhancement of composite boards as the OD@CCF content increased, while mechanical tests indicated an optimal additive content of up to 20%. The thermal-regulated capabilities of these advanced panels were evaluated in a custom-designed room model equipped with a homemade environmental chamber, illustrating a consistent temperature environment during heating and cooling cycles. The incorporation of OD@CCF into cement boards exhibited improved thermal energy storage properties. Moreover, the examined composite boards displayed efficient electromagnetic shielding performance within the frequency range of 3.2–7.0 GHz, achieving EMI values of approximately 18 and 19.5 dB for gypsum and cement boards, respectively, meeting the entry-level value required for commercial applications.

BACKGROUND AND OBJECTIVE: The use of biomass for cooking carries significant health implications and can lead to adverse environmental issues such as deforestation, greenhouse gas emissions, and erosion. Despite these concerns, there is a lack of information about the nature and extent of cooking emissions in many developing countries. To address this gap, a study was conducted to assess cooking emission levels and their associated health effects among households in Dodoma City, Tanzania. METHODS: A descriptive cross-sectional design was conducted, involving 285 households in the peri-urban area of Dodoma City, Tanzania. A combination of questionnaires, observational checklists, and sampling devices (Aeroqual series 500 for Carbon Monoxide and Temptop PMD 351 for Particulate Matters) were employed for data collection, adhering to established protocols. Additionally, lung function tests were conducted with consent from the primary household cooks. Collected data were entered into an Excel spreadsheet and analyzed using STATA 17 software. FINDINGS: Out of 285 participants, 74.7% predominantly use charcoal for cooking, with 68.4% having outdoor kitchen setups. Significant differences in pollutant concentrations were observed across various fuel types (P=0.0001), with firewood emitting higher levels of particulate matter and carbon monoxide. Carbon monoxide concentrations during cooking were 6 times higher for firewood, 5 times higher for charcoal-gas, and 3 times higher for charcoal compared to WHO daily average limits. Additionally, a positive correlation between pollutant concentrations was noted (P-value = 0.0000). Lung problems 17.8% followed by eye irritation 15.7% were mentioned by those who claimed to know the health effects associated with cooking emissions. In addition, the spirometry test indicated that the majority of the participants had % predicted >80 while only 19% had % predicted below 50. CONCLUSION: Charcoal and firewood remain the primary cooking fuels in the study area despite their significant negative impacts. Our findings highlight a lack of awareness among community members regarding the health effects of biomass cooking emissions and insufficient guidance on constructing healthy kitchens. To address this, enforcing building standards, raising health awareness, and ensuring affordable access to modern fuels are crucial steps. These measures are essential for promoting healthier cooking practices and mitigating the adverse effects on households.

The purpose of the evaluation of the Peruvian energy generation system is to project the electricity generation and demand until the year 2050. To achieve this, three alternative scenarios have been defined and analyzed using the LEAP (Long-range Energy Alternatives Planning) software. The scenarios are as follows: the first one, Business-as-Usual scenario, based on normal trends according to historical data and referencing projections made by Peruvian state entities; the second one is focused on Energy Efficiency, the highlighted characteristic is taking into consideration the efficient conditions in transmission and distribution of electric energy; and the third one, centered on Geothermal Energy, focused on the development of this type of energy source and prioritizing it. The primary purpose of this analysis is to identity advantages and disadvantages inherent in each scenario in order to get the best of each one. In this way, the intention is to propose solutions based on Peru’s national reality or possible uses of the country’s energy potential to supply its energy demand. Currently, Peru’s energy demand relies on fossil fuels, hydraulic, and thermal energy. However, there is the possibility of transforming this system into a sustainable one, by strengthening existing and growing energy sources such as solar and wind energy, and new technologies for hydraulic and thermal energy, in addition to considering geothermal energy as the main energy source in the third scenario. The new system mentioned satisfactorily indicate that the CO2 equivalent emissions decrease significantly in the third scenario, with a 15.8% reduction compared to the first scenario and a 9.7% reduction in comparison to the second. On the other hand, the second scenario shows a 5.6% decrease in CO2 emissions compared to the first, resulting from improvements in technology and energy efficiency without requiring significant modifications or considerable investments, as in the third scenario.

In the context of the minimally extended varying speed of light (meVSL) model, both the absolute magnitude and the luminosity distance of type Ia supernovae (SNe Ia) differ from those predicted by general relativity (GR). Utilizing the Pantheon+ data, we examine the plausibility of various dark energy models under meVSL. Both ωCDM and CPL parameterization dark energy (DE) models exhibit indications of cosmic variations in the speed of light at the 1-σ level. For Ωm0=0.30,0.31, and 0.32 with (ω0,ωa)=(−1,0), the 1-σ range of c˜˙0/c˜0(10−13yr−1) is (-8.76 , -0.89), (-11.8 , 3.93), and (-14.8 , -6.98), respectively. Meanwhile, the 1-σ range of c˜˙0/c˜0(10−12yr−1) for CPL dark energy models with −1.05≤ω0≤−0.95 and 0.28≤Ωm0≤0.32, is (-6.31 , -2.98). The value of c˜ at z=3 can exceed that of the present by 0.2∼3 % for ωCDM models and 5∼13 % for CPL models. Additionally, for viable models except for the CPL model with Ωm0=0.28, we find −25.6≤G˜˙0/G˜0(10−12yr−1)≤−0.36. For this particular model, we obtain an increasing rate of the gravitational constant within the range 1.65≤G˜˙0/G˜0(10−12yr−1)≤3.79.

This research focusing on the environmental impact of tire and brake pad wear constitutes a significant area of transport-related studies. These two key vehicle components are not only the most frequently worn, but also generate micro and nano pollutants (i.e., rubber, metal oxides) that potentially harm the environment. Over half of the globally produced natural and synthetic rubbers, which amounted to about 30 million tons in 2022, are used for tire production. According to Wagner et al.'s research, over 1.3 million tons of such particles are released due to wear and tear in the European Union alone. This work focuses on examining snow deposits from various locations in an urban agglomeration (Poznan, Poland) in the winter season. FT-IR and NMR spectroscopic studies, optical and electron scanning microscopy SEM-EDS, and particle size studies using the DLS technique were conducted for a detailed characterization of pollutants in the environment. The conducted particle separation methods allowed for the extraction of a fraction mainly containing gum residues with particle sizes less than 2 µm. The results of these studies are crucial for understanding the impact of vehicle part exploitation on the environment.

This study examines the optimization of ground source heat pump (GSHP) systems and energy piles for sustainable urban development, with a focus on Southeast Asia. GSHPs, which utilize geothermal energy for indoor HVAC needs, offer a sustainable alternative to traditional systems by utilizing consistent subsurface temperatures for heating and cooling. The study highlights the importance of understanding thermal movement within the soil, especially in soft marine clays prevalent in Southeast Asia, to improve GSHP system efficiency. Using a one-dimensional finite-difference model, the study examines the effects of soil thermal conductivity and density on system performance. The results show that GSHP systems, especially when integrated with energy piles, significantly reduce electricity consumption and greenhouse gas emissions, underscoring their potential to mitigate the urban heat island effect in densely populated areas. Despite challenges posed by the region's hot and humid climate, which could affect long-term effectiveness, the study highlights the need for further study, including field experiments and advanced modeling techniques, to optimize GSHP configurations and fully exploit geothermal energy in urban environments. The study's insights into soil thermal dynamics and system design optimization contribute to the advancement of sustainable urban infrastructure development.

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.

The literature shows that both in laboratory and in industrial conditions, photocatalytic oxidation method copes quite well with the degradation of the most organic substances, including environmental toxins and molecular components of pathogenic microorganisms. However, the effective utilization of photocatalytic processes for environmental decontamination and disinfection require significant technological advancement both in the area of semiconductor material synthesis and its application. Here we focused on the presence and ‘photocatalytic capability‘ of photocatalysts among soil minerals, and their potential contribution to the environmental decontamination in vitro and in vivo. (The issue is sketched from the perspective of chemists and environmental scientist.) Reactions caused by sunlight on the soil surface are involved in its normal redox activity. It appears that some of them may take part in the soil decontamination. However, their importance for decontamination in vivo cannot be overstated due to diversity of soils on the Earth caused by the environmental conditions, such as climate, parent material, relief, vegetation etc. The solar-light induced reactions are just a part of extremely complicated processes dependent on a plethora of environmental determinates. Such multiplicity of affecting factors, which we tried to sketch from the perspective of chemists and environmental scientist, makes us rather sceptical about the effectiveness of the photocatalytic processes in vivo. On the other hand, there is a huge potential of the soils as the alternative source of useful photocatalytic materials of unique properties

We introduce two symmetric concepts to physics: “distance” (space and time in one) and “wavematter” (electromagnetic wave packet and matter in one). We claim that physics has chosen the wrong concept of time: It is not aware that the time of a moving object flows in a direction other than my time. We provide 15 proofs for our claim by solving 15 mysteries of physics graphically! For example, we prove that length contraction and time dilation are actually geometrical effects in a 4D manifold that we call “Euclidean spacetime” (ES). We prove that the discrepancy in calculating the Hubble constant stems from a systematic error in the redshift measurement. We prove that what I deem wave, deems itself matter, which solves wave–particle duality. We even untangle quantum entanglement without the issue of non-locality. We finally understand why alternative theories of Euclidean relativity have failed: They are all based on four dimensions of space rather than distance. A huge amount of energy was injected into ES at a point that we take as origin. Ever since has this energy been moving radially away at the speed of light. We live in the 3D hypersurface of an expanding 4D hypersphere. Hyperspherical coordinates have the great advantage that they reduce all that is ever happening to just one formula. So, it is the Theory of Everything in these coordinates: “Energy is covering radial distance which, divided by Euclidean time, is equal to the speed of light.” Acceleration and force like gravitation emerge from a rotation of objects in ES and a subsequent projection to 3D space. Matching the symmetry simplifies physics.

Osteoporosis is considered a serious public health problem, particularly affecting the postmenopausal period. In 2018, in the Republic of Kazakhstan the total and primary incidence was 10 and 3.7 cases per 100,000 adults, respectively. The objective is to study osteoporosis prevalence and indicate main factors affecting low bone mineral density by screening adult population of Abay region, Kazakhstan. The target group were 641 respondents aged between 18 and 65 years old, Kazakh population living in Abay region since birth. All participants filled out questionnaire and had a bone mineral density measurement by dual energy X-ray absorptiometry (DXA) between July 15, 2023 and February 29, 2024. Logistic regression analysis was conducted to assess the association between low bone mineral density and key demographic characteristics, aforementioned lifestyle factors and nutrition habits. We identified the prevalence of low bone density and osteoporosis at the level of 34.1% with the highest prevalence in the older population group (50+ years) - 48.3%. Regression analysis revealed a number of indicators associated with the likelihood of bone sparing. However, only 4 of these showed significance in the final multivariate model (R2=22.4%). These included age (AOR 1.05), body mass index (AOR 0.92), fracture history (AOR 1.64), consumption of nuts and dried fruits were associated with lower prevalence of osteoporosis (AOR 0.48). Our study was the first in Kazakhstan that investigates the association of key demographic, behavior and anamnestic factors with low mineral density.

The rehabilitation of abandoned mining sites is an increasingly pressing issue in the context of sustainable development. Recent research has emphasized the need for a holistic approach to the abandoned mining sites and their environmental rehabilitation. Based on field analysis, environmental assessments, satellite imagery processing and geographic information operations, this paper pushes forward the existing knowledge by doing a comprehensive assessment of abandoned mining sites in the Romanian Carpathians and by proposing innovative and sustainable rehabilitation solutions. Our findings highlight that abandoned mining sites and their surrounding territories in the Romanian mountains have significant ecological imbalances and complex socio-economic issues. The findings also suggest that by adopting innovative, integrated, and sustainability-oriented approaches, territories affected by mining can be transformed into valuable and sustainable spaces to meet human needs. We conclude by presenting the importance of innovation in ecological reconstruction and spatial-functional reintegration of mining sites in mountain areas as a useful tool in making fair decisions, both in the context of implementing appropriate development policies as well as for resilience and environmental sustainability of mining-affected mountain areas.

The Double U-pipe ground heat exchanger, recognized for its straightforward process, cost-effectiveness, high heat exchange efficiency, and low thermal resistance, stands as the predominant ground heat exchanger type in today's shallow geothermal energy development and utilization. Recent years have seen significant research into the heat transfer influencing factors and heat exchange performance of Double U-pipe ground heat ex-changers via experimental testing methods. Yet, studies integrating numerical simulation with in-situ testing have been less frequent. Drawing on the cylindrical heat source model theory and the outcomes of regional in-situ thermal response tests, this paper develops a Double U-pipe ground heat transfer model by establishing physical, mathematical, and heat transfer geometric models. It assesses the impact of varying inlet temperatures, flow rates, and initial ground temperatures on heat exchange efficiency under heating conditions. The results validate the precision of the double U-pipe ground heat exchanger model based on in-situ testing. They show that enhancing the temperature differential between the inlet and initial temperatures, elevating the initial ground temperature, and moderately increasing the flow rate can boost the system's heat exchange efficiency.

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

This paper describes an entropy equation that can be used for measuring energy. It originated from measuring economy in AI models, where the assumption would be that any organic system makes use of energy efficiency to form its structures. Looking at clustering and cohesion resulted in the equation E = (mean * variance). It was apparent however, that it was a very generic type of equation and it could be adjusted so that distance represents mean. This new version was applied to the domain of physics and the universe, when the equation can support the idea that work is done through the energy released by the 'change' in entropy. A comparison with Einstein's relativity equation is made and also the audacious suggestion that a black hole has only potential energy inside, which converts to kinetic energy after a Big Bang, for example. From that suggestion, a universal theory about state change can be made.

The results shown in this paper extend our research group's previous work, which presents the theoretically achievable hydrogen engine-out NOx (H2-NOx) Pareto front of a hydrogen hybrid electric vehicle (H2-HEV). While the Pareto front is calculated offline, which requires significant computing power and time, this work presents an online-capable algorithm to tackle the energy management of a H2-HEV with explicit consideration of the H2-NOx trade-off. Through the inclusion of realistic predictive data on the upcoming driving mission, a model predictive control algorithm (MPC) is utilized to effectively tackle the conflicting goal of achieving low hydrogen consumption while simultaneously minimizing the NOx. In a case study it is shown that the MPC is able to satisfy user-defined NOx limits over the course of various driving missions. Moreover, a comparison to the optimal Pareto front highlights the MPC's ability to achieve close-to-optimal fuel-performance for any desired cumulated NOx target on four realistic routes for passenger cars.

Esterquats constitute a unique group of quaternary ammonium salts (QASs) that contain an ester bond in the structure of the cation. Despite the numerous advantages of this class of compounds, only two mini-reviews discuss the subject of esterquats: the first one (2007) briefly summarizes their types, synthesis, and structural elements required for a beneficial environmental profile and only briefly covers their applications whereas the second one only reviews the stability of selected betaine-type esterquats in aqueous solutions. The rationale for writing this review is to critically reevaluate the relevant literature and provide others with a “state-of-the-art” snapshot of choline-type esterquats and betaine-type esterquats. Hence, the first part of this survey thoroughly summarizes the most important scientific reports demonstrating effective synthesis routes leading to the formation of both types of esterquats. In the second section, the susceptibility of esterquats to hydrolysis is explained, and the influence of various factors, such as the pH, the degree of salinity or the temperature of the solution, was subjected to thorough analysis that includes quantitative components. The next two sections refer to various aspects associated with the ecotoxicity of esterquats. Consequently, their biodegradation and toxic effects on microorganisms are extensively analyzed as crucial factors that can affect their commercialization. Then, the reported applications of esterquats are briefly discussed, including functionalization of macromolecules, such as cotton fabric as well as their successful utilization on a commercial scale. The last section demonstrates the most essential conclusions and reported drawbacks that allow us to elucidate future recommendations regarding the development of these promising chemicals.

This study analyses the changes in land use in the Sado estuary (West-Central Portugal) based on a multitemporal analysis of cartographic data from the 19th century and remote sensing land use maps from the 21st century, updated by field work. A GIS plotting of land-use evolution is summarized in a quantitative table. The comparison shows the changes in land use, with increasing occupation by human economic activities, including extensive agriculture and forestry, as well as localized urbanization and industrialization. The main elements of the landscape impacted by anthropogenic uses were: i) hydrography - river dams affected the flow dynamics and sedimentary processes in the estuary; ii) vegetation – increasing agriculture and forestry reduced the areas of native vegetation, nowadays mostly occupied by vineyards, pine forests and cork oaks. iii) wetlands - tidal and alluvial plains are being occupied by rice cultivation, aquaculture, industries, and ports; iv) coastal dunes – new developments are occupying large areas of Holocene coastal dunes; v) natural environment – mining and dredging affected some habitats and biodiversity. This analysis is intended to help the territorial organization of present and future economic activities, as well as to reduce environmental and social problems, promoting long-term sustainability of this rapidly evolving region.

This research explores and analyzes the challenges and opportunities due to globalization's impact on sustainable strategic management. The research uses a mixed-method design, combining primary and secondary data collection methods. Secondary data is sourced from various credible publications and analyzed through an extensive literature review. A case study approach is adopted, involving semi-structured interviews with six experienced managers from Tazweed Venture Capital in Jordan. The study employs a qualitative, descriptive, and analytical approach to develop a conceptual framework by exploring managers' experiences and perspectives on Globalization and its impact on Sustainable Strategic Management. The findings identify challenges of environmental degradation, economic inequality, transportation and logistics pressures, and compliance challenges for sustainability. While implementing sustainable practices incurs upfront costs, accessing renewable energy markets and financial support presents opportunities. Tazweed successfully implements sustainable strategic management, emphasizing stakeholder engagement and collaboration across departments. This research offers valuable insights and guidance for companies navigating globalization's impact on sustainability strategic management.

Digital health has added numerous promising solutions to enhance the health and wellness of people with neurocognitive disorders (NCDs) and their informal caregivers: (1) Background: It is important to get a comprehensive view of currently available technologies, their outcomes, and conditions of success to inform recommendations regarding digital health solutions for people with NCDs and their caregivers. This environmental scan was performed to identify the features of existing digital health solutions relevant to the targeted population. This work reviews currently available digital health solutions and their related characteristics to develop a decision support tool for older adults living with mild or major neurocognitive disorders and their informal caregivers. This knowledge will inform the development of a decision support tool to assist older adults and their informal caregivers in their search for adequate digital health solutions according to their needs and preferences, based on trustable information.; (2) Methods: We conducted an environmental scan to identify digital health solutions from a systematic review and targeted searches in grey literature covering the regions of Canada and Europe. Technological tools were scanned based on a preformatted extraction grid. We assessed their relevance based on selected attributes and summarized findings; (3) Results: We identified 100 available digital health solutions. The majority (56%) were not specific to NCDs. Only 28% provided scientific evidence of their effectiveness. Remote patient care, movement tracking, and cognitive exercises were the most common purposes of digital health solutions. Most solutions were presented as decision aid tools, pill dispensers, apps, web, or a combination of these platforms. (4) Conclusions: This environmental scan allowed the identification of current digital health solutions for older adults with mild or major neurocognitive disorders and their informal caregivers. Findings from the environmental scan highlight the need for additional approaches to strengthen digital health interventions for the well-being of older adults with mild and major NCDs and their informal and formal healthcare providers.

This paper presents a theoretical framework aimed at improving IoT network cybersecurity by AI-driven anomaly detection in the context of rapid urbanization and the development of smart cities. The framework draws upon the Complex Adaptive Systems Theory, Theory of Planned Behavior, the Technology Acceptance Model, and the Socio-Technical Systems Theory, and intri-cately examines how AI might be integrated into the intricate ecosystem of smart cities to detect and mitigate cyber threats. It emphasizes AI-driven anomaly detection methods as pivotal in-struments that impact cybersecurity enhancement in smart city infrastructures. The proposed framework also highlights the crucial role that human-related factors, including user behavior and adoption, play in determining how effective AI applications are in enhancing cybersecurity in smart cities. It also recognizes the important moderating roles played by outside factors like legislative frameworks, environmental contexts, and technological breakthroughs in the relationship between AI-enabled anomaly detection and enhanced cybersecurity. The goal of this research is to shed light on the interactions between technology and socio-technical dynamics by offering a thorough theoretical understanding of AI's potential in smart city cybersecurity. It highlights the significance of taking into account a variety of contextual aspects when employing AI to strengthen the digital security of urban areas, and provides a strategic direction for future research and practical implementation.

This research was devoted to study the effect of the tacticity of PMMA on the surface physicochemical properties such as the London dispersive component of the surface energy of the polymer, the polar and dispersive free energies, the Lewis’s acid-base surface parameters, and the Lewis acid and base surface energies of atactic, isotactic and syndiotactic PMMAs as a function of the temperature. Inverse gas chromatography (IGC) at infinite dilution was used to determine the surface thermodynamic properties of PMMA at different tacticities. The experimental values of the net retention time and volume of model organic molecules adsorbed on the atactic, isotactic and syndiotactic PMMAs, were obtained by IGC technique at infinite dilution. The London dispersion interaction energy was used for the separation of the polar and dispersive energy of the different n-alkanes and polar solvents adsorbed on the different PMMA surfaces. The London dispersive surface energy γ_s^d (T) of PMMAs was determined by applying the Hamieh thermal model that took into account the effect of the temperature on the surface area of adsorbed molecules. The obtained results showed non-linear variations of γ_s^d (T) of atactic, isotactic, and syndiotactic PMMAs with three maxima characterizing the three transition temperatures of PMMAs, T_g, T_g and T_(liq-liq) with a shift of these temperatures with the isotactic and syndiotactic PMMAs. It was showed that the polar interaction free energy ∆G_a^p (T) also showed the presence of the three above transition temperatures of the polymers. The study showed an important non-linearity variation of the different acid-base parameters in the various polymer surfaces proving the highest effect of the temperature and the tacticity on these parameters. The determination of the enthalpic and entropic Lewis’s acid-base parameters showed an amphoteric character for the different PMMAs. The basicity of the atactic PMMA was about four times larger than its acidity outside the neighborhood of the transition temperatures of the polymer. Whereas, the isotactic PMMA was about 2 to 2.5 times more basic than acid, while the syndiotactic PMMA exhibited the highest basicity by showing a surface 5 to 8 times more basic than acid. However, the Lewis acid-base parameters strongly depended on the temperature and sudden variations of these surface parameters were observed around the transition temperatures largely depending on the PMMA tacticity. The determination of the polar acid and base surface energies of the three PMMAs led to the same previous transition temperatures with an important effect of the tacticity of PMMA on the values of these acid-base surface energies.

Abstract: : 2,3-dihydro-5,6,7,8-tetranitro-1,4-benzodioxine (TNBD), molecular formula =C8H4N4O10 is a completely nitrated in aromatic ring 1,4-benzodioxane derivative. The con-venient method of TNBD synthesis was developed (yield=81 %). The detailed structure of this compound has been investigated by X-ray crystallography. The results of differential thermal analysis (DTA) obtained with twice re-crystallized material showed onset at 247 and isoterm at 288 0C, with further total degradation at 300 0C. The experimental density 1,85 g/cm3 of TNBD was determined by X-ray crystallography. The spectral properties of TNBD (NMR, FT-IR, Ra-man) were explored. The detonation properties of TNBD calculated by EXPLO 5 code was slightly superior in comparison to standard high energy material - tetryl (detonation velocity of TNBD - 7727 m/s; detonation pressure - 278 kbar; tetryl – 7570 m/s and 226.4 kbar at 1.614 g/cm3, or 260 kbar at higher density - 1.71 g/cm3. The obtained preliminary results might suggest TNBD can be a potential thermostable high energy and density material (HEDM).

Air quality is a topic of growing relevance on the global agenda. Two key indicators of air quali-ty, nitrogen dioxide (NO2) and carbon monoxide (CO), represent significant hazards to human health and the environment putting the sustainability of natural resources at risk. Therefore, it is imperative to regularly monitor and reduce atmospheric pollutant concentrations to mitigate their harmful consequences. This study presents an analysis of NO2 total and CO emissions in Argentina, utilizing remote sensing data. The research aims to determine the spatiotemporal distribution of NO2 and CO emissions in Argentina from 2019 to 2021. Subsequently, it seeks to establish the influence of land uses and land cover on the emission of NO2 and CO through dif-ferent climatic, anthropic, and natural indicators. The study was carried out in Argentina during the period 2019-2021, where random points were placed for the different land covers with a total of 800 points surveyed. The year with the highest CO concentration (mol/m-2) was 2020. The values were highest for tree covers and herbaceous wetland coverage in the northern part of the country. For total NO2, the highest concentrations were reached during the years 2020 and 2021. Regarding its distribution, throughout the evaluated period, the highest concentrations of total NO2 were found in the built-up and cropland coverages, with the capital of the country and the northern region of the Buenos Aires province being the most affected areas. In addition, the concentration of CO was influenced by climatic variables (atmospheric pressure, wind speed, maximum environment temperature, Palmer index), natural (height, humidity, NDVI), and ur-ban variables (distances to mining extraction, airports, power plants, urban index) for the differ-ent uses and land covers. Finally, the concentrations of total NO2 were influenced by climatic variables (Palmer index and wind speed), natural (height and NDVI), and urban variables (dis-tance to airports, power plants, industries, service stations, and open dumpsites) for the differ-ent uses and land cover. This study contributes to sustainable environmental management, ena-bling the formulation of effective strategies for mitigating emissions and promoting the long-term health and well-being of communities.

The conventional measure of cosmic acceleration, denoted as \( q \), relies heavily on the frame of reference and operates within a 3D space-like coordinate system, potentially leading to misinterpretations of underlying physics. In this study, we propose a novel measure, \( q_E \), grounded in distances between causal events in 4D null space. We compare \( q_E \) with the standard \( q \) using observational data from supernovae (SN) and radial galaxy/quasar (QSO) clustering (BAO) to find a better alignment of data with \( q_E \). Our analysis indicates that cosmic expansion, when viewed in the rest frame, is decelerating, with events confined by an Event Horizon akin to that of a Black Hole interior. Rather than invoking new dark energy or modified gravity, we propose that \( \Lambda \) corresponds to a boundary term exerting an attractive influence, analogous to a rubber band resisting further expansion and preventing horizon crossing of events. Contrary to prevailing notions, interpreting current cosmic expansion measurements as deceleration, rather than acceleration, offers a more accurate depiction of observed phenomena and the underlying physics. This reevaluation prompts further investigation into the nature of cosmic expansion, as well as the exploration of alternative frameworks and measures in cosmology.

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

The work aims to improve the battery performance in hybrid electric vehicles (HEVs) by reducing the vehicle speed. We develop a specific protocol for managing battery use and optimizing the energy consumption rate to achieve this goal. The protocol automatically controls the driving operation, avoiding incompatible driving patterns with energy-saving mode and performance improvement. The protocol is submitted to a simulation process to predict the energy rate lowering and battery performance enhancement. The proposed protocol applies to any hybrid electric vehicle type and route conditions since it uses vehicle mass, drag and rolling coefficients, and road slope as variable parameters to determine the minimum energy consumption rate. We run experimental tests to validate the simulation data and the proposed protocol. Furthermore, the protocol applies to variable starting vehicle speeds, from 10 to 50 km/h, corresponding to the current driving patterns, sport, normal, and eco, set up by car manufacturers. A reduction of 10% in vehicle speed in urban and peripheral routes achieves a minimum energy rate, enhancing battery management. Current vehicle speed shows a deviation from optimum management of 18% while applying the vehicle speed reduction limits the deviation to 0.2%. Experimental results show a good agreement with simulation data with 94% accuracy. We tested the protocol for urban and peripheral routes with maximum vehicle speed limits of 60 and 90 km/h.

The study is dedicated to analyzing the complex interaction between Artificial Intelligence (AI) and the Internet of Things (IoT) with institutional structures in the context of sustainable development. This work examines the impact of these technologies on economic and social development, identifying their potential advantages and risks. Methodologically, the research relies on information gathering and case study analysis, assessing the impact of technology in various domains, from smart cities to the manufacturing sector. The findings emphasize the necessity of integrating technological innovations into broader social and environmental initiatives, highlighting the importance of institutional transformations for achieving environmental sustainability.

Retiring coal power plants can reduce air pollution and health damages. However, the spatial distribution of those impacts remains unclear due to complex power system adjustments and pollution chemistry and transport. Focusing on coal retirements in Pennsylvania (PA), we analyze six counterfactual scenarios for 2019 that differ in retirement targets (e.g., reducing 50% of coal-based installed capacity vs. generation) and priorities (e.g., closing plants with higher cost, closer to Environmental Justice Areas, or with higher CO₂ emissions). Using a power system model of the PJM Interconnection, we find that coal retirements in PA shift power generation across PA and the Rest of PJM region leading to scenario-varying changes in the plant-level release of several air pollutants. Due to air pollution chemistry and transport and socio-demographics, these changes in turn give rise to a reduction of 10 to 182 PM_2.5-attributable deaths in PJM across the six scenarios, with most reductions occurring in PA. Scenarios that reduce more coal power generation yield greater aggregate health benefits due to air quality improvements in PA and adjacent downwind regions. In addition, vulnerable populations—in both PA and Rest of PJM—benefit most in scenarios that prioritize plant closures in PA near Environmental Justice Areas. These results demonstrate the importance of considering cross-regional linkages and socio-demographics in designing equitable retirement strategies.

Purpose of publication: - Preparation of bibliometric data exported from the Scilit platform on energy efficiency and conservation for further analysis to identify relevant research topics. - To identify potential issues in the processing of data exported from the Scilit platform. - Providing colleagues with the opportunity to use the prepared data and examples of their analysis for independent research on topical issues of energy efficiency and energy conservation using materials provided by the Scilit platform. Research Materials: Files in CSV and RIS formats exported from Scilit for the query "energy conservation OR efficiency" in Common Fields [Title, Abstract, Keyword], using filters: Content Type → Journal Article; Year→2021-2023; Subject → Industrial Engineering (29.8K), Energy and Fuel Technology (9.8K), Manufacturing Engineering (9.2K). A total of 30K records sorted by their relevance (10K for each year) were exported. Data are current as of 14-03-2024. Methods: Preprocessing of title, annotation, and keyword field texts using lemmatization dictionaries collected on GitHub, removal of keywords taken from GATE and spaCy, and "manual" editing. Using VOSviewer to analyze publication topics by clustering keywords based on their co-occurrence. Using Scimago Graphica to build bubble diagrams.Application of the GSDMM algorithm for clustering bibliometric records by title and annotation texts. Creation of a dictionary for this algorithm using the keyword field.Use of the Carrot2 demo version and the NMF algorithm for a more detailed analysis of the topics of the record clusters obtained from GSDMM. Results: are presented in the form of initial and interim tables and graphs obtained in the course of this study. The full tables are provided as references to the attached materials. Supplementary material for this preprint on figshare: Chigarev, Boris (2024). Supplementary material for preprint "Analyzing the Possibilities of Using the Scilit Platform to Identify Current Energy Efficiency and Conservation Issues". figshare. Dataset. https://doi.org/10.6084/m9.figshare.25574058.v1

The reduction of PV prices and interest in energy independence accelerate the adoption of residential battery storage. This storage can support various functions of an energy system undergoing decarbonization. In this work, operative benefits of the storage from the system perspective, namely, generation cost reduction and congestion mitigation, are investigated. Germany is chosen as a case study due to its strong reliance on variable renewable energy. For the analysis, an economic dispatch model with a high spatial resolution is coupled with a Pan-European transmission grid model. It is shown that the system's generation costs are highest when the assets are used only to maximize the PV self-consumption, and the costs are lowest when the storage also reacts to the market dynamics. This amounts to 6% cost reduction. Both operation strategies result in an equal level of grid congestion and infrastructure loading. This is improved with a strategy that accounts regional peak reduction as a secondary objective. The high congestion level emphasizes the grid expansion need to keep pace with the generation and electrification expansion necessary to decarbonize other sectors. Lastly, policymakers should enable multipurpose utilization, e.g., via the introduction of market-oriented retail electricity prices with intervention options for grid operators.

Observation of the distribution of the velocity of galactic rotation curves differed from their expected centripetal form and lead to the notion of Dark Matter or modifications to Newtonian and General Relativity, such as MOND, TeVeS and the like and even Quantised Inertia. We aim to show that General Relativity with Dark Energy/the Cosmological Constant is all that is needed, with the proviso that the Cosmological Constant can increase in the presence of a light flux or some other factor from galaxies and become gravitating; the need for Dark Matter may be abated.

Microgrids (MGs) have evolved as critical components of modern energy distribution networks, providing increased dependability, efficiency, and sustainability. Effective control strategies are essential for optimising MG operation and maintaining stability in the face of changing environmental and load conditions. Traditional rule-based control systems are extensively used due to their interpretability and simplicity. However, these strategies frequently lack the flexibility for complex and changing system dynamics. This paper provides a novel method called hybrid intelligent control for adaptive MG that integrates basic rule-based-control and deep learning techniques, including gated recurrent units (GRU), basic recurrent neural network (RNN) and long short-term memory (LSTM). The main target of this hybrid approach is to improve MG management performance by combining the strengths of basic rule-based systems and deep learning techniques. These deep learning techniques readily enhance and adapt control decisions based on historical data and domain-specific rules, leading to increasing system efficiency, stability, and resilience in adaptive MG. Our results show that the proposed method optimises MG operation, especially under demanding conditions such as variable renewable energy supply and unanticipated load fluctuations. This study investigates special RNN architectures and hyper-parameter optimization techniques with the aim of predicting power consumption and generation within the adaptive MG system. Our promising results show the highest-performing models indicating high accuracy and efficiency in power prediction. The finest-performing model accomplishes an R2 value close to 1, representing a strong correlation between predicted and actual power values.

Recent research has specifically targeted the decision-making process of eco-friendly individuals, emphasizing the significance of recycling and its impact on sustainability. Our study extends this inquiry by examining the correlation between recycling participation and pro-environmental behavior among consumers, integrating the concepts of self-efficacy, feelings of pride, and social pressure into our analysis. Utilizing Partial Least Squares-Structural Equation Modeling (PLS-SEM), we aimed to explore the intricate relationships that underpin these behaviors. Results suggest that self-efficacy and feelings of pride significantly influence individuals' recycling behaviors, highlighting the role of psychological and social factors in promoting environmental sustainability. Interestingly, it was concluded that social pressure did not have the expected moderating effect on increasing consumers' feelings of pride and self-efficacy toward recycling activities.This study not only sheds light on the underlying mechanisms that drive pro-environmental actions but also contributes to understanding sustainability promotion through recycling and offers insights for policymakers and environmental advocates to foster environmental responsibility and behavior change.

Membrane gas absorption technology and solar-assisted regeneration system are two promising approaches to reduce high energy consumption associated with carbon dioxide capture from coal fired power plants. In the present study, a solar-assisted hollow fiber membrane contactor (SOL-HFMC) power plant is proposed to capture and desorb CO₂ in hollow fiber membrane contactors with the assistance of solar thermal collectors. Techno-economic assessment and sensitivity analysis of the proposed system is carried out in three studied locations with different weather conditions for a 580 MWe pulverized coal power plant. Research results show that, the output capacity and net efficiency of the SOL-HFMC power plant are significantly higher than those of the reference power plant regardless whether TES system is applied or not. In addition, CEI of the SOL-HFMC power plant with TES system is 4.36 kg CO₂/MWh, 4.45 kg CO₂/MWh and 4.66 kg CO₂/MWh lower than that of the reference power plant. The prices of membrane, vacuum tube collector and phase change material should be reduced to achieve lower LCOE and COR values. Specifically for SOL-HFMC power plant with TES system, the corresponding vacuum tube collector price shall be lower than 25.70 $/m² for Jinan, 95.20 $/m² for Xining, and 128.70 $/m² for Lhasa, respectively. To be more competitive than solar-assisted ammonia-based post-combustion CO₂ capture power plant, the membrane price in Jinan, Xining and Lhasa shall be reduced to 0.012 $/m, 0.015 $/m and 0.016 $/m for the sake of LCOE, and 0.03 $/m, 0.033 $/m and 0.034 $/m for the sake of COR, respectively. The findings can provide guidance for decision-making and risk management strategies.

In order to investigate the vertical distribution pattern of soil fauna community in low-altitude mountain areas. On July 8th, 2022, a low hill was selected as the study area to collect soil arthropods were collected through trap. Leaf litter, vegetation type and distribution quantity were investigated at each sampling site while soil fauna were collected. Also, the soil physical and chemical parameters were measured simultaneously. The results of one-way ANOVA showed that there were significant differences (P

It is already known that a simple nonlocal de Sitter gravity model, which we denote as dS gravity, contains an exact vacuum cosmological solution which mimics dark energy and dark matter and is in very good agreement with the standard model of cosmology. This success of dS gravity motivated us to investigate how it works at lower than cosmic scale – galactic and the solar system. This paper contains our investigation of the corresponding Schwarzschild-de Sitter metric of the dS gravity model. To get exact solution, it is necessary to solve the corresponding nonlinear differential equation, what is a very complicated and difficult problem. What we obtained is a solution of linearized equation, which is related to space metric far from the massive body, where gravitational field is weak. The obtained approximate solution is of particular interest for examining the possible role of non-local de Sitter gravity dS in describing the effects in galactic dynamics that are usually attributed to dark matter. The solution has been tested on the Milky Way and the spiral galaxy M33 and is in good agreement with observational measurements.

When asked to estimate the carbon footprint of a bundle of relatively low carbon footprint items and relatively high carbon footprint items, people typically report a lower value compared to estimating the high carbon footprint items alone. This finding is called the negative footprint illusion and suggests people report the average rather than sum of the combined items’ carbon footprint. In a recent paper by Gorissen et al. (2024), the authors claimed that people are immune to this illusion if the question is framed differently. Specifically, they found that estimates of the environmental friendliness of a set comprising a burger (high carbon footprint) and an organic apple (low carbon footprint) was higher than for a set comprising the burger alone, whereas no difference was found between the two sets when participants were asked to estimate how environmentally damaging they were. Using larger item categories wherein the degree of the items’ environmental impact is clearly communicated, here we show it does not matter whether participants are required to estimate how friendly or damaging the items are. The roles of attribute substitution, dependent variables, and independent variables (stimulus characteristics) in modulating the negative footprint illusion is discussed.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

The scope of this work is to empirically check and prove the practical applicability of the Primordially Hydridic Earth (hereinafter PHE) concept for early exploration of the resources of naturally occurring hydrogen. With the PHE concept postulates interpreted within the local geological, tectonic, petrological and geophysical context, the reconnaissance plan, as well as the field exploration and data acquisition programs, were put together and implemented in the field. The results obtained from the surface (

Differences between the quantum mechanical and relativistic concepts of time observed in GPS satellites are accounted for by applying the equivalence principle to the transitioning electron of an atomic clock. It allows a differential equation of motion to be derived for the electron in the Minkowski space between electron shells. Using Hamilton’s principle we transform the differential equation relativistically into an integral equation of motion, the time integral of a Lagrangian. This newly derived equation accounts for the abstract mathematics of the more familiar non-relativistic model by means of a physical interpretation. Abstract rotations in Hilbert space are replaced by the rotations of real particle field geometries in Minkowski space. Because the properties of energy are universal the same equations are then used to describe the field geometry of galaxies despite vast differences in lifetime. They reveal a symmetry between the electromagnetic fields of atoms and the gravitational fields of galaxies due to similarities in the exchange of energy by radial and transverse fields. Our analysis reveals that the conjugate variables energy and time permit differences between atomic and galactic structure to be compared in a more intuitive way than by means of the differential equations of motion which use the conjugate variables position and momentum.

The main source of electricity worldwide stems from fossil fuels, contributing to air pollution, global warming, and associated adverse effects. This study explores wind energy as a potential alternative. Nevertheless, the variable nature of wind introduces uncertainty in its reliability. Thus, it is necessary to identify an appropriate machine learning model capable of reliably forecasting wind speed under various environmental conditions. This research compares the effectiveness of artificial neural networks (ANN) and convolutional neural networks (CNN) in predicting wind speed across three locations in South Africa, characterised by different weather patterns. Empirical results show that CNN outperforms ANN in accurately forecasting wind speed under different weather conditions. This superiority is likely due to the inherent architectural attributes of CNNs, including feature extraction capabilities, spatial hierarchy learning, and resilience to spatial variability. These results could be useful to decision-makers in the energy sector.

The number of engineers who are transitioning into environmental sustainability careers is growing, though a gap still exists between supply and demand. This presents an opportunity for undergraduate engineering students to fulfill the demand as environmental sustainability professionals. This qualitative exploratory study investigated environmental sustainability learning experiences and future career interests in environmental sustainability. The social cognitive theory (SCCT) was utilized as a theoretical lens, exploring undergraduate students’ environmental sustainability interests, related learning experiences and their interest in pursuing a future career in environmental sustainability. Twenty-five undergraduate engineering students in various engineering disciplines were interviewed for this study. Data were analyzed to (1) identify students’ interest in pursuing a career in environmental sustainability, (2) determine if students’ interests have changed since they began their undergraduate studies, and (3) explore how learning experiences have impacted students’ future career choice. The findings posit that exposure to environmental sustainability learning experiences is impactful and plays an important role, impacting students' interests in pursuing careers in sustainability. Results reveal that elements such as personal beliefs and salary considerations inspire career choices. This research contributes to addressing the demand for additional working professionals who are prepared to tackle environmental sustainability issues, highlighting the role of learning experiences in shaping students' career interests.

The social- and self-directed behaviours of two golden lion tamarins (Leontopithecus rosalia) was investigated while having residence in the tropical house of Aalborg Zoo, Denmark. The behaviour of the female had been distinct from the male since 2018. Despite several diagnostic examinations and medicinal treatments, the cause of the aberrant and apparently stereotypical behavioural patterns remained undetermined, which initiated this study. The pair were recorded throughout a predetermined observation period and these recordings were analysed to illuminate the behaviours of the individuals. The results showed that there were differences in the type, frequency, and durations of both social- and self-directed behaviours between the sick female and the healthy male. The female expressed both social- and self-directed behaviours more frequently and for longer durations, while the male were more socially reserved and did not engage in social behaviours as frequently. Furthermore, subsequent necropsy of the female revealed uro-genital disease.

Dealing with and maintaining high-quality standards in the design and construction phases is challenging, especially for on-site construction. Issues like improper implementation of building components and poor communication can widen the gap between design specifications and actual conditions. To prevent this, particularly for energy-efficient buildings, it's vital to develop resilient, sustainable strategies. These should optimize resource use, minimize environmental impact, and enhance livability, contributing to carbon neutrality by 2050 and climate change mitigation. Traditional post-occupancy evaluations, which identify defects after construction, are impractical for addressing energy performance gaps. A new, real-time inspection approach is necessary throughout the construction process. This paper suggests an innovative guideline for prefabricated buildings, emphasizing digital 'self-instruction' and 'self-inspection'. These procedures ensure activities impacting quality adhere to specific instructions, drawings, and 3D models, incorporating relevant acceptance criteria to verify completion. This methodology, promoting alignment with planned energy-efficient features, is supported by BIM-based software and Augmented Reality (AR) tools, embodying Industry 4.0 principles. BIM and AR bridge the gap between virtual design and actual construction, improving stakeholder communication and enabling real-time monitoring and adjustments. This integration fosters accuracy and efficiency, key for energy-efficient and Nearly Zero-Energy Buildings, marking a shift towards a more precise, collaborative, and environmentally sensible construction industry.

In today's world, the significance of reducing energy consumption globally is increasing, making it imperative to prioritize energy efficiency in the 5th Generation (5G) networks. However, it is crucial to ensure that these energy-saving measures do not compromise the Key Performance Indicators (KPIs) such as user experience, quality of service (QoS), or other important aspects of the network. To address this challenge, advanced wireless technologies have been incorporated into the design of 5G networks across various network layers. Given the rapid advancements in Artificial Intelligence (AI) and emerging technology trends such as Machine Learning (ML), which is considered a subset of AI, the integration of such trends into 5G networks has become a significant area of research. The primary objective of this survey is to analyze AI integration into 5G networks for enhanced energy efficiency. By exploring this intersection between AI and 5G, we aim to identify potential strategies and techniques for optimizing energy consumption while maintaining the desired network performance and user experience.

The adoption of environmental conservation agriculture (ECA) in Nepal is aligned with the country's goal to achieve carbon neutrality by 2045, as ECA practices have been proven to effectively reduce greenhouse gas emissions. Nepal's agricultural sector faces numerous challenges, including labor shortages, climate change impacts, and the necessity for environmentally friendly farming methods, making the adoption of ECA practices even more crucial. This paper thus explored farmer perspectives on the sustainability of ECA practices in Namobuddha municipality, Nepal, which is renowned as a leading hub of organic farming. A cross-sectional survey was conducted, together with key informant interviews and onsite observations. By analyzing various farmer perspectives, the study presents an analytical framework that highlights the economic, environmental, and social pillars of ECA's sustainability. The findings underscore the significance of economic viability for farmers, as damages to crops and farm products negatively drive their perception of ECA sustainability. Conversely, factors such as increased agriculture-related income, favorable prices, and sustainable productivity positively shape farmers' perceptions. In terms of environmental sustainability, farmers prioritize enhancing the local and global environment, viewing their farming methods as climate-smart and actively working towards reducing greenhouse gas emissions. The study emphasizes the importance of strategic communication to effectively convey the benefits of ECA to rural communities. Overall, this research contributes to filling the knowledge gap concerning farmers' perceptions of ECA sustainability. The insights gained from this study have the potential to inform policy decisions and promote the widespread adoption of environmentally friendly farming practices in Nepal.

Smart manufacturing encompasses a category of manufacturing that employs computer-integrated capabilities and technologies to enhance supply chain optimization, production efficiency, and recyclability. Yet limited studies have been conducted to optimize these prospects from the perspective of low resource countries where such innovative studies have not been adequately explored. This paper aims to examine the implications of smart manufacturing practices (Smart Procurement, Smart Supply Chain, Smart Production Planning and Control, Automation and Industrial Robot, and Supply Chain Configuration) on pro-environmental behaviour and develop a baseline moderated mediation model to explain the relationship between smart manufacturing and pro-environmental behaviour with a role of green dynamic capability, and environmental orientation. This study is anchored on quantitative research approach, deductive reasoning, and explanatory design. Cross – sectional survey data have been obtained from 382 manufacturing companies in Ghana. Our hypotheses have been tested using Structural Equation Modelling and SMART-PLS version 3.8.9. The study has revealed that smart manufacturing practices significantly and positively relate to pro-environmental behaviour. Moreover, green dynamic capability and environmental orientation moderate the relationship between smart manufacturing and pro-environmental behaviour. The implications of the study include the emergence of a baseline model to guide policymakers, practitioners, and academicians to explain the relationship between smart manufacturing and sustainable manufacturing in the context of developing countries. Again, the social implication of the study includes the realisation of decent job and economic growth, responsible consumption and production as well as actions taken to combat climate change.

Hybrid Renewable Energy Systems (HRES) integrate renewable sources, storage, and optionally conventional energies, offering an eco-friendly solution to fossil fuels. Microgrids (MGs) bolster HRES integration, enhancing energy management, resilience, and reliability at various levels. This study, emphasizing the need for refined optimization methods, investigates three themes: renewable energy, microgrid, and multiobjective optimization (MOO), through a bibliometric analysis of 470 Scopus documents from 2010-2023, analyzed with SciMAT software. It segments the research into two periods, 2010-2019 and 2020-2023, revealing a surge in MOO focus, especially in the latter period, with a 35% increase in MOO-related research. This indicates a shift towards com-prehensive energy ecosystem management that balances environmental, technical, and economic elements. The initial focus on MOO, genetic algorithms, and energy management systems has expanded to include smart grids and electric power systems, with MOO remaining a primary theme in the second period. The increased application of Artificial Intelligence (AI) in optimizing HMGS within the MOO framework signals a move towards more sustainable, intelligent energy solutions. Despite progress, challenges remain, including high battery costs, the need for reliable MOO data, the intermittency of renewable energy sources, and HMGS network scalability issues, highlighting directions for future research.

Dysregulation of the Cyclin-dependent kinase 8 (CDK8) activity has been associated to many diseases including the colorectal and breast cancer. As usual in the CDK family, the activity of CDK8 is controlled by a regulatory protein called cyclin C (CycC). But while human CDK family members are generally activated in two steps that is, the binding of the cyclin to CDK and the phosphorylation of a residue in the CDK activation loop, CDK8 does not require the phosphorylation step to be active. Another peculiarity of CDK8 is its ability to be associated to CycC while adopted an inactive form. These specificities raise the question of the role of CycC in the complex CDK8-CycC, which appears to be more complex than for the other members of CDK family. Through MD simulations and binding free energy calculations, we investigated the effect of CycC on the structure and dynamics of CDK8 on the one hand, and the structural molecular basis of the protein-protein interaction between the two partners on the other hand. We found that CycC has a stabilizing effect on CDK8 and identified specific interaction hotspots within its interaction surface compared to other human CDK/Cyc pairs. Targeting these specific interaction hotspots could be a promising approach in terms of specificity, to effectively disrupt the interaction between CDK8. The simulation of the conformational transition from the inactive to the active form of CDK8 suggests that the residue Glu99 of the CycC may assume the role of the missing phosphorylation step in the activation mechanism of CDK8. In a more general view, these results point the importance of keeping the CycC in computational studies when studying the human CDK8 protein in both the active and the inactive form.

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

Ultrasound, as mechanical waves with frequencies exceeding 20 thousand hertz, has found wide applications in medicine, physiotherapy, and more recently in agriculture. This study aimed to investigate the impact of ultrasound on potato yield and its parameters, particularly on seed potato yield, quantity, mass, and multiplication coefficient of potato tubers. The research was based on a three-year field experiment, utilizing the randomized block design in a split-split-plot arrangement, in the central-eastern region of Poland. The primary factor were technologies: a) technology with employing ultrasonic pre-planting treatment, b) traditional cultivation without this treatment. The secondary factors were potato varieties. Sonication of tubers was conducted using a bath-type ultrasonic device equipped with piezoe-lectric transducers. Results revealed a significant influence of cultivation technology, cultivar, and weather conditions on seed tubers yield, quantity, and multiplication coefficient of potato tubers. However, genetic traits of the examined varieties and random factors significantly affected the individual seed tuber mass and the number of shoots emerging from a single tuber. Future Outlook: Future research could focus on further optimizing ultrasound application techniques in potato cultivation, considering diverse varieties and environmental conditions. Additionally, it would be worthwhile to analyze the long-term effects of ultrasound on tuber seed potato quality and their ability to adapt to changing climatic and soil conditions. Furthermore, studies investi-gating the impact of ultrasound on other plant species could broaden our understanding of po-tential benefits in agriculture.

In our investigation of the time evolution of energy states Einstein’s interpretation from more than a century ago is found to have greater internal consistency than that of non-relativistic quantum mechanics. We choose to align more closely with his methods by abandoning the non-relativistic Hamiltonian method, which has been the standard for nearly a century, in favor of a relativistically correct Lagrangian method. Integral equations of motion for the absorption and emission of radiation are derived that underlie and anticipate the differentially motivated Schrödinger equation. This new interpretation applies to a large volume of experimental evidence of both classical and quantum mechanical origin. Among the examples discussed in support are Planck’s law describing black body radiation, matrix mechanics, the function of the simplest quantum mechanical system an electron cyclotron, chaos theory, and evolutionary biology.

Surface–subsurface soil-rock modeling is crucial for infrastructure design and groundwater yield optimization, especially in the complex crystalline basement terrains of Penang Island, Malaysia. This study conducted large-scale characterization of soil-rock profiles using ERT, SRT, rock quality designation, and soil penetration test (SPT N-values) data, optimized through regression modeling. The approach effectively identified soil-rock structures and their suitability to prevent structural failures and enhance groundwater productivity. Correlations between borehole lithologic logs and velocity–resistivity models revealed distinct soil compositions across the study area. The results highlighted thick, saturated, and loose silty to sandy bodies in the eastern to northern sections, contrasting with sandy compositions and penetrative fractures in the southern part. The study also found good correlations between rock mass quality and N-values for different soil types. Depths of intra-bedrock weathered/fractured units varied between 12 and >35 m. This has significant implications for determining optimal foundation depths in the study area. Groundwater productivity was associated with intra-bedrock planes of weakness at depths exceeding 40 m. Overall, this study developed empirical relations between geophysical and geotechnical parameters for wet tropical granitic terrains, filling critical gaps in understanding subsurface characteristics.

In the decarbonization of the steel, cement, and chemical industry in Germany, green hydrogen is expected to play a crucial role. The utilization of green hydrogen in the production processes of said industries requires organizations to modify their business model, requiring sustainable business model innovation (SBMI). Numerous tools and frameworks that support organizations in the process of SBMI have been proposed in the literature in recent years. However, the applicability of these tools and frameworks for steel, cement, and chemical companies that intend to utilize green hydrogen to produce their goods remains unexplored. By conducting a systematic literature review on tools and frameworks for SBMI, a literature and practice review to identify and analyze existing green hydrogen projects of steel, cement, and chemical companies, and an evaluation of the identified tools and frameworks in an evaluation matrix, this paper aims to assess the suitability of SBMI tools and frameworks for steel, cement, and chemical companies that plan to use green hydrogen to produce their goods. Based on the evaluation, the Cambridge Business Model Innovation Process (CBMIP) was identified as the most suitable SBMI framework.

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

The article presents a model for optimizing biomass supply chains using the linear programming framework integrated with a Geographic Information System. Based on the distance from a given type of biomass resource, its calorific value, price, and transportation costs, the model identifies the optimal source of biomass, allowing it to cover the demand for the required total energy value with the lowest possible costs. The case study includes the Połaniec power plant in southeastern Poland and potential sources of forest biomass and agricultural straw within 100 km of the plant. Unit costs of biomass varied depending on biomass availability and energy demands. For energy demand on the level of 1 PJ yearly, the lowest unit costs of biomass (4.08 €/MJ) were when all kinds of biomass were available, and the highest (5.47 €/MJ) was when only stacked wood was available. As energy demand increased, unit costs increased, and the ability to meet this demand with just one type of biomass decreased. The energy biomass sector can utilize the model to benefit both biomass producers and their final buyers.

The state-of-the-art smart city has been calling for an economic but efficient energy management over large-scale network, especially for the electric power system. It is a critical issue to monitor, analyze and control electric loads of all users in system. In this paper, we employ the popular computer vision techniques of AI to design a non-intrusive load monitoring method for smart electric energy management. First of all, we utilize both signal transforms (including wavelet transform and discrete Fourier transform) and Gramian Angular Field (GAF) methods to map one-dimensional current signals onto two-dimensional color feature images. Second, we propose to recognize all electric loads from color feature images using a deep neural network with multi-scale feature extraction and attention mechanism. Third, we design our method as a cloud-based, non-intrusive monitoring of all users, thereby saving energy cost during electric power system control. Experimental results on both public and our private datasets have demonstrated our method achieves superior performances than its peers, and thus supports efficient energy management over large-scale Internet of Things.

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

Earth’s climate cannot be ignored any longer. Policies are vital in order to mitigate the negative effects of climate change. The energy crisis created by the Russo-Ukrainian war and pandemic affected the EU and its member states. The focus is more than ever on its energy policies and independence. The EU revised the energy strategy in response to Russia’s blackmail, and it sped up all the processes for energetic independence from Russia. This benefited the climate change policies the most, as all the measures involved reducing energy consumption and increasing renewables, thus contributing to reducing greenhouse gas emissions. As a member state of the EU, Romania is committed to complying with EU regulations. With a high degree of energy independence compared with the other EU members, Romania plans to become a regional energy provider and modernize the energy infrastructure internally as a response to Russia’s unprovoked aggression. The measures that the EU and Romania implemented after the war started in 2022 have come to fruition, and the effects are becoming visible a year later. This study aims to study the energy strategy of Romania in correlation with the EU strategy in the turbulent period of pandemics and war between 2019 and 2023, with the latest available data.

The emergence of Distributed Ledger Technology (DLT) in the past decade has challenged our imagination to discover new, innovative and disruptive solutions to problems in domains ranging from finance and healthcare to supply chain and smart cities. However, the enormous energy consumption that has been observed in some of the most successful DLT applications raises the question of their long term sustainability. This article reviews the standardization efforts of the International Telecommunications Union (ITU) to provide guidelines to regulators and policy makers for making informed decisions on the applicability and sustainability of DLT architectures from the point of view of energy consumption.

The Philippines has the highest HIV incidence rate in the Asia-Pacific region. Previous studies identified multilevel factors contributing to this phenomenon. This scoping review describes the extent of the literature on HIV contributory factors and identifies gaps to guide directions for HIV prevention research. The keywords HIV incidence, individual, sociocultural, environmental factors, and Philippines, were used to search for evidence on Google Scholar, PubMed, Scopus, and Web of Science databases. A total of 1,017 peer-reviewed articles published in the English language from 2014 to 2024 were reviewed using the Joanna Briggs Institute Scoping Review protocol. Thirty articles were included in this review. The majority of the available evidence was quantitative studies published between 2020 and 2024. Individual, sociocultural, economic, educational, political, and environmental factors shaped the Philippines’ HIV epidemic. Low levels of HIV knowledge, low testing rates, high-risk sex behaviors, stigma, lifestyle, location, lack of HIV education in schools, conservative society, and restrictive policies are HIV contributing factors. The Philippine HIV epidemic is multifactorial. Identifying the contributory factors is crucial in developing targeted interventions for high-risk populations. A dedicated HIV research program is needed to provide evidence-based information to guide the development of HIV preventive programs and research.

This article proposes a particular strategy to proceed with a progressive electrification of public transport systems in cities. Starting from a bus operation model, the possible electrification of two routes is analysed, one urban and another extra-urban in the city of Pisa. An estimate is made of the energy uses associated with certain operating modes. The maximum level of consumption is estimated at approximately 280 kWh per day per bus for the urban route and excluding some special days, less than 215 kWh per day for the extra-urban route, for which a hybrid bus is proposed. Starting from an estimate of the daily consumption for the management of the two routes, the sizing of a photovoltaic system distributed on some modular shelters which serves to power the same routes is carried out. The resulting system has a power of the order of 190-200 kW. The modular solution is also outlined, and an installation is proposed. The analyzed case lends itself to being easily replicated.

This study provides a detailed investigation into the pathways through which microplastics from urban sources are transported to marine ecosystems, their distribution across different environments, and their impacts on marine life. Utilizing a combination of water and sediment sampling across urban, riverine, and marine environments, the research quantitatively assesses the concentration and types of microplastics present, and evaluates the ecological consequences of their accumulation in marine ecosystems. The findings reveal a significant concentration of microplastics in all examined environments, with the highest levels detected in urban areas, closely linked to industrial activities and inadequate waste management practices. The study documents a variety of microplastic polymers, with polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET) being the most prevalent. A substantial impact on marine organisms was observed, including evidence of microplastic ingestion across a wide range of species and indications of stress and physical damage to coral reefs. Seasonal variations indicate that microplastic concentrations peak during periods of high rainfall, suggesting urban runoff as a critical pathway for microplastic transport. The study concludes with recommendations for improving waste management practices, enhancing public awareness and engagement in plastic recycling efforts, and implementing policies aimed at reducing the production and use of single-use plastics. This research underscores the urgent need for coordinated actions to mitigate the pervasive issue of microplastic pollution, highlighting the role of urban management and policy interventions in safeguarding marine ecosystems.

This study considers an application of the first-order Grey Markov Model to foresee the values of Italian power generation in relation to the available energy sources. The model is used to fit data from the Italian energy system from 2000 to 2022. The integration of Markovian error introduces a random element to the model, which is able now to capture inherent uncertainties and misalignments between the Grey model predictions and the real data. This application provides valuable insights for strategic planning in the energy sector and future developments. The results show good accuracy of the predictions, which provides powerful information for the effective implementation of energy policies concerning the evolution of energy demand in the country. Despite advancements, Italy’s 2032 energy mix will still significantly rely on fossil fuels, emphasizing the need for sustained efforts beyond 2032 to enhance sustainability.

Due to the continued deepening of today’s mining projects, there is a need to develop new or improved rockbolts that are strong and yielding and have high energy absorption when exposed to dynamic loading. Impact tests can provide useful information about the dynamic response of rockbolts but most laboratory tests involve high costs in preparation and result validation. Numerical modeling is an alternative that, in addition to complementing laboratory results, can be used to represent the process of deformation and energy absorption of support elements. In this paper the implementation and results obtained from a finite difference (FDM) numerical model are presented. The model functions as a simulation tool to illuminate all the elements that conform the large-scale (1:1) impact test and their behavior and influence on the dynamic response of a threadbar bolt (22 mm nominal diameter). The model was calibrated using published results and based on these results as well as parametric analysis, the response of each component (steel tube, grout, and bolt) could be identified and its behavior in terms of absorbed energy and displacement could be observed. Results show the model can provide important preliminary information to make design decisions about support elements design.

As the global transition towards renewable energy accelerates, the integration of grid-scale energy storage systems has become increasingly critical for stabilizing energy supply and enhancing grid reliability. Among various storage technologies, lithium-ion batteries stand out for their high energy density, scalability, and relatively low environmental impact. This study investigates the performance and longevity of lithium-ion batteries in grid-scale applications, focusing on the impact of operational parameters such as cycling frequency, depth of discharge, temperature fluctuations, and charging/discharging rates. Employing a mixed-methods approach, we combined quantitative analysis of performance metrics (cycle life, capacity fade, efficiency) with qualitative assessments from case studies of existing grid-scale projects. Our findings reveal that while lithium-ion batteries exhibit robust performance in grid-scale storage, their longevity and efficiency are significantly influenced by operational conditions. Specifically, temperature management and optimized cycling strategies were identified as key factors in mitigating degradation and extending battery life. This research provides a comprehensive understanding of lithium-ion battery behavior in grid-scale environments, offering valuable insights for the design, optimization, and management of energy storage systems. By addressing the challenges of battery performance and longevity, our study contributes to the development of more sustainable and reliable grid storage solutions, facilitating the broader adoption of renewable energy sources.

In this paper the attention is focused on the analysis and the optimization of energy flows in networked systems via a fluid-dynamic model. In particular, a cost functional that represents a term proportional to the kinetic energy of an energy system is studied. First, the functional is optimized for a simple network having a unique node, with an incoming arc and two outgoing ones. The optimization deals with distribution coefficients and explicit solutions are found. Then, the global optimization is obtained using the local optimal parameters at the various nodes of the system. Considering the case study of an energy hub, interesting results are obtained for the whole network, proving the correctness of the proposed approach.

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

Here we will electrically-quantum model the neutron and proton as a three-phase alternating current electric generator, for this, we will use the theory of three-phase electric generators and vector or phasor diagrams. We will use this model to hypothesize how the quarks that form neutrons and protons with a combined mass of 10 MeV/c², can generate, through quarks-antiquarks-gluon interactions, a mass of 939.56 MeV/c² for the neutron and a mass of 938.27 MeV/c² for the proton. Using quantum mechanics and the theory of the generalization of the Boltzmann constant in curved space-time we will calculate the number of quarks-antiquarks-gluons and gravitons inside a neutron. We will also analyse βˉ decay using vector diagrams, we will calculate the tension of the string T₀ and the length of the string ℓs between quarks-antiquark and finally, we will model a black hole using a neutron equivalent model. In version 2 of this article, we will update the vector diagrams of the βˉ decay and theoretically calculate the energy of the W⁻ boson, the Z⁰ boson, and the Θ angle, Θ = arc cos (W⁻/Z⁰). We will demonstrate, through vector diagrams, that quarks-antiquarks-gluon interactions are the cause of the origin of the W⁻ boson and the Z⁰ boson. We will also demonstrate how the fine structure constant α originates. It is important to make clear, in future updates, we will describe the relationship that exists between the theory described in this paper and the Isospin theory, flavour and colour theory

Background: Online survey-based observational cross-sectional study aimed at elucidating experience and attitudes of unstructured population regarding diagnostic imaging. Methods: Invitations to participate were distributed using mixed-mode design to deidentified residents aged 18 years and older. Main outcome measures included morbidity structure and incidence of diagnostic imaging administrations. Results: Respondents (n = 1069) aged 44.3 ± 14.4 years; 32.8% suffered from cardiovascular diseases (CVD); 9.5% had chronic respiratory pathology; 28.9% considered themselves healthy. Respondents with COVID-19 history (49.7%) reported higher rates of computed tomography (CT) (p < .0001), magnetic resonance imaging (MRI) (p < .001), and ultrasound (p < .05). COVID-19 history in CVD respondents shifted imaging administrations towards CT and MRI (p < .05). Every tenth respondent received MRI, CT, and ultrasound on paid basis; 29.0% could not pay for diagnostic procedures; 13.1% reported unavailable MRI. Professional status significantly affected the pattern of diagnostic modalities (p < .05). MRI and CT availability differed between respondents in urban and rural areas (p < .0001). History of technogenic events predisposed responders to overestimate diagnostic value of fluorography (p < .05). Conclusions: Preparedness to future pandemics requires development of community-based outreach programs focusing on people's awareness regarding medical imaging safety and diagnostic value.

Scientific studies on the impact of wood species on solid fuel production, performance, and sustainability are grossly inadequate. The knowledge of this is imperative as users of solid fuels are increasing rapidly, especially in Africa. On this note, it becomes necessary to explore measures that will improve its efficiency and sustainability as an energy source. This study investigates some properties of selected wood species used as an energy source in Nigeria and their pelleting potential. Nine (9) samples were characterized and assessed for suitability of pelleting following four wood pellet quality standards. The findings revealed Anogeissus leiocarpus as the species with the best rating score in terms of fuel properties while Vitellaria paradoxa as the lowest. However, in terms of conformity with the four wood pellets standards, Khaya senegalensis, Parkia biglobosa and Anogeissus leiocarpus having presented density, calorific value, sulfur, arsenic, cadmium, and lead within the limits of the wood pellet quality standards were considered the best wood species in terms of fuel suitability and pelleting potential. The findings therefore suggest that not all wood species are suitable as fuel. Thus, for species that do not meet the standard wood pellet requirements, alternatives such as the use of biomass blends, additives, or process adjustments can be employed to adapt the quality to the standards or by using the fuels in improved cookstoves.

In this work, we explore new constraints on phantom scalar field cosmologies with a scalar field employing early times catalogues related to CMB measurements, along with the local standard observables, like Supernovae Type Ia (SNIa), H(z) measurements (Cosmic Clocks), and Baryon Acoustic Oscillations (BAO) baselines. In particular, we studied a tracker phantom field with hyperbolic polar coordinates that have been proposed in the literature. The main goal is to obtain precise cosmological constraints for H0 and σ8, in comparison to other constructions that present tension in early cosmological parameters. Our results show that phantom scalar field cosmologies have a reduced statistical tension on H0 that it is less than 3σ using model-independent CMB catalogues as SPT-3G+WMAP9 and ACTPol DR-4+WMAP9 baselines. This suggests these models using a different phantom potential might address the Hubble constant problem and reduce the systematics involved.

This paper undertakes a comprehensive review to underscore the central role of sustainability in the evaluation and innovation of jet grouting technologies. It meticulously traces the evolution of evaluation methodologies, emphasizing the imperative of sustainable practices throughout history. Traditional evaluation paradigms are examined alongside contemporary trends, with a particular focus on sustainability metrics and visualization techniques. Through an examination of innovative jet grouting technologies, this paper illustrates how sustainability principles have driven advancements aimed at improving the efficiency and environmental impact of jet grouting methods. Central to this review is an assessment of sustainability across multiple dimensions, including method applicability, installation and operational compatibility, and the performance of the resulting jet grouted piles. By emphasizing sustainability considerations, the paper highlights the intrinsic link between environmental integrity and technological innovation in the field of jet grouting. In addition, it discusses analytical evaluation methods designed to proactively address sustainability concerns prior to construction, thereby promoting a more environmentally responsible approach. Finally, this paper presents a pioneering evaluation framework that integrates real-time monitoring and visualization tools, allowing stakeholders to track sustainability milestones throughout the construction process. By emphasizing sustainability as a guiding principle, this review advocates for a paradigm shift toward more ecologically sound and resilient jet grouting practices.

A selective permeable membrane between two different solutions can generate osmotic pressure, Donnan potential, and ion/pH gradients based on various factors such as membrane type, solute concentration and temperature. In this study, we introduce a novel method for extracting energy from ion gradients through an innovative cycle, presenting intriguing experimental findings. Additionally, by leveraging Raoult’s Law, which describes the relationship between vapor pressure and solute presence, in conjunction with osmosis within a closed system, we successfully engineer the simplest iteration of Maxwell’s demon device. This pioneering approach to sustainable energy generation harnesses ambient temperature marking a significant advancement in energy research. Finally this renewable energy source is available all the time and everywhere.

This study grounded in the Affective Events Theory, explores how post-pandemic urban residents' nostalgic tourism influences environmental behaviors in rural areas. The article constructs a model of pro-environmental behavior in rural settings with nostalgic tourism as the antecedent variable, environmental responsibility and awe as mediators, ecological concern as a moderating variable, and pro-environmental behavior as the outcome variable. Analyzing 535 valid survey responses from urban residents and utilizing Partial Least Squares Structural Equation Modeling (PLS-SEM) to test research hypotheses reveals that nostalgic tourism significantly impacts environmental responsibility and awe. Environmental responsibility mediates between nostalgic tourism and pro-environmental behavior, forming a serial mediation chain with awe psychology, and its mediating effect is significant. However, awe psychology forms a serial mediation chain between nostalgic tourism and pro-environmental behavior, and its mediating effect is insignificant. Notably, environmental concern does not moderate the relationship between environmental responsibility and pro-environmental behavior, indicating no support for this hypothesis. The positive role of nostalgic tourism in pro-environmental behavior at rural tourism destinations enriches theoretical research on the nexus between nostalgia and environmental behavior, providing insights into the sustainable development of rural environments and the operation of rural tourism.

In the current complex and uncertain macroeconomic situation, improving the inherent resilience of the new energy vehicle industry chain is the key to effectively addressing various risks and challenges, and achieving dynamic balance between high-quality industrial development and industrial chain security. Based on the basic concept of resilience and the actual situation of new energy vehicle industry chain development, this study constructs a comprehensive evaluation index system for the resilience of the new energy vehicle industry chain, which includes four dimensional first-level indicators of coping resistance, adaptive resilience, autonomous control and leading competitiveness. In addition, it is measured by combining the data related to the new energy vehicle industry chain in Changzhou City. Our study shows that the situation on the new energy vehicle industry chain is complicated, and the comprehensive evaluation index system is more favorable for evaluating its resilience level.