Search Results (5,225)

The social acceptance of Renewable Energy Sources (RESs) is a decisive factor in the successful implementation of clean energy projects. This study explores the attitudes, demographic profiles, and common misconceptions of citizens in the Region of Epirus, Greece, toward photovoltaic and wind energy installations. Special attention is given to the role of education, age, and access to information—as well as spatial factors such as visual exposure—in shaping public perceptions and influencing acceptance of RES deployment. A structured questionnaire was administered to 320 participants across urban and rural areas, with subdivision between regions with and without visual exposure to RES infrastructure. Findings indicate that urban residents exhibit greater acceptance of RES, while rural inhabitants—especially those in proximity to installations—express skepticism, often grounded in esthetic concerns or perceived procedural injustice. Misinformation and lack of knowledge dominate in areas without visual contact. Statistical analysis confirms that younger and more educated participants are more supportive and environmentally aware. The study highlights the importance of targeted educational interventions, transparent consultation, and spatially sensitive communication strategies in fostering constructive engagement with renewable energy projects. The case of Epirus underscores the need for inclusive, place-based policies to bridge the social acceptance gap and support the national energy transition. Full article

Governments worldwide have set ambitious targets for decarbonising energy grids, driving the need for increased renewable energy generation and improved energy efficiency. One key strategy for achieving this involves enhanced energy management in buildings, often using machine learning-based forecasting methods. However, such methods typically rely on extensive historical data collected via costly sensor installations—resources that many buildings lack. This study introduces a novel forecasting approach that eliminates the need for large-scale historical datasets or expensive sensors. By integrating custom-built models with existing energy data, the method applies calculated weighting through a distance matrix and accuracy coefficients to generate reliable forecasts. It uses readily available building attributes—such as floor area and functional type to position a new building within the matrix of existing data. A Euclidian distance matrix, akin to a K-nearest neighbour algorithm, determines the appropriate neural network(s) to utilise. These findings are benchmarked against a consolidated, more sophisticated neural network and a long short-term memory neural network. The dataset has hourly granularity over a 24 h horizon. The model consists of five bespoke neural networks, demonstrating the superiority of other models with a 610 s training duration, uses 500 kB of storage, achieves an R² of 0.9, and attains an average forecasting accuracy of 85.12% in predicting the energy consumption of the five buildings studied. This approach not only contributes to the specific goal of a fully decarbonized energy grid by 2050 but also establishes a robust and efficient methodology for maintaining standards with existing benchmarks while providing more control over the method. Full article

There are many controversies over the material sources of the Late Paleozoic strata in the Lower Yangtze region, and there is a lack of consensus on the basin source–sink system, which hinders the reconstruction of Late Paleozoic paleogeography and exploration of energy and mineral resources in the area. This study aimed to clarify the sedimentary provenance and tectonic background of the Upper Permian Longtan Formation in the Chizhou area of southern Anhui Province. The key objectives were to: (i) analyze the geochemical characteristics of sandstones using major, trace, and rare earth elements; (ii) determine the tectonic setting of the sediment source region based on discrimination diagrams; and (iii) integrate geochemical, sedimentological, and paleocurrent data to reconstruct the source-to-sink system. The geochemical data suggest that the sandstone samples exhibit relatively high SiO₂, Fe₂O₃, MgO, and Na₂O content and relatively low TiO₂, Al₂O₃, and K₂O content, consistent with average values of post-Archean Australian shale (PAAS) and the upper continental crust (UCC). The chondrite-normalized rare earth element patterns resemble PAAS, with enrichment in light REEs and depletion in heavy REEs. Tectonic discrimination diagrams indicate a provenance from active continental margins and continental island arcs, with minor input from passive continental margins. Combined with regional tectonic context and paleocurrent measurements, the results suggest that the Longtan Formation sediments primarily originated from the Neoproterozoic Jiangnan orogenic belt and the Cathaysia Block, notably the Wuyi terrane. These research results not only provide new geological data for further clarifying the provenance of Late Paleozoic sedimentary basins in the Lower Yangtze region but also establish the foundation for constructing the Late Paleozoic tectonic paleogeographic pattern in South China. Full article

The kallikrein–kinin system and its B1 and B2 receptors are key regulators in metabolic disorders such as obesity, diabetes, and insulin resistance. Obesity, a chronic and multifactorial condition often associated with comorbidities like type 2 diabetes and dyslipidemia, remains poorly understood at the metabolic level. The kinin B2 receptor (B2R) is involved in blood pressure regulation and glucose metabolism, promoting glucose uptake in skeletal muscle via bradykinin. Studies in B2R-KO mice demonstrate that the absence of this receptor predisposes animals to glucose intolerance under a high-fat diet and impairs adaptive thermogenesis, indicating a protective role for B2R in metabolic homeostasis and insulin sensitivity. In contrast, the kinin B1 receptor (B1R) is inducible under pathological conditions and is activated by kinin metabolites. Mouse models lacking B1R exhibit improved metabolic profiles, including protection against high-fat diet-induced obesity and insulin resistance, enhanced energy expenditure, and increased leptin sensitivity. B1R inactivation in adipocytes enhances insulin responsiveness and glucose tolerance, supporting its role in the development of insulin resistance. Moreover, B1R deficiency improves energy metabolism and thermogenic responses to adrenergic and cold stimuli, promoting the activation of brown adipose tissue and the browning of white adipose tissue. Collectively, these findings suggest that B1R and B2R represent promising therapeutic targets for the treatment of metabolic disorders. Full article

Outdoor air pollution poses a major global health risk, yet monitoring remains insufficient, especially in regions with limited infrastructure. Solar-powered monitors could allow for increased coverage in regions lacking robust connectivity. However, reliable sample collection can be challenging with these systems due to extreme temperatures and insufficient solar energy. Proper planning can help overcome these challenges. Air Sampler Solar and Thermal Optimization for Reliable Monitoring (Air-STORM) is an open-source tool that uses meteorological and solar radiation data to identify temperature and solar charging risks for air pollution monitors based on the target deployment area. The model was validated experimentally, and its utility was demonstrated through illustrative case studies. Air-STORM simulations can be customized for specific locations, seasons, and monitor configurations. This capability enables the early detection of potential sampling risks and provides opportunities to optimize monitor design, proactively mitigate temperature and power failures, and increase the likelihood of successful sample collection. Ultimately, improving sampling success will help increase the availability of high-quality outdoor air pollution data necessary to reduce global air pollution exposure. Full article

The present study examines the barriers that prevent cooling system flexibility from being optimized. In the context of an increasing reliance on renewable energy sources, the necessity for flexible energy utilization is becoming increasingly apparent. A survey and discussion groups were conducted with various stakeholders within the cooling value chain to obtain their experiences and insights regarding barriers to flexibilization. The findings point out that economic, technological, and regulatory barriers are the primary factors impeding the implementation of flexible solutions. In particular, high investment costs, complex technical implementation, a lack of information, and a complicated legal framework were identified as significant impediments. To enhance the flexibility of cooling systems, coordinated efforts are necessary to address these barriers. Practical examples, training, and the standardization and digitalization of processes could facilitate the widespread implementation of flexible cooling systems. Full article

Developing ultra-high-temperature geothermal resources is challenging, as traditional drilling fluids, including foam systems, lack thermal stability above 160 °C. To address this key technical bottleneck, this study delves into the screening principles for high-temperature-resistant foaming agents and foam stabilizers. Through high-temperature aging experiments (foaming performance evaluated up to 240 °C and rheological/filtration properties evaluated after aging at 200 °C), specific additives were selected that still exhibit good foaming and foam-stabilizing performance under high-temperature and high-salinity conditions. Building on this, the foam drilling fluid system formulation was optimized using an orthogonal experimental design. The optimized formulations were systematically evaluated for their density, volume, rheological properties (apparent viscosity and plastic viscosity), and filtration properties (API fluid loss and HTHP fluid loss) before and after high-temperature aging (at 200 °C). The research results indicate that specific formulation systems exhibit excellent high-temperature stability and particularly outstanding performance in filtration control, with the selected foaming agent FP-1 maintaining good performance up to 240 °C and optimized formulations demonstrating excellent HTHP fluid loss control at 200 °C. This provides an important theoretical basis and technical support for further research and field application of foam drilling fluid systems for deep high-temperature geothermal energy development. Full article

Cyanobacteria are a prolific source of bioactive metabolites with expanding applications in sustainable agriculture and biotechnology. This work explores, for the first time in thermotolerant Colombian isolates, the impact of light spectrum, photoperiod, and irradiance on the co-production of exopolysaccharides (EPS) and indole-3-acetic acid (IAA). Six strains from hot-spring environments were screened under varying blue:red (B:R) LED ratios and full-spectrum illumination. Hapalosiphon sp. UFPS_002 outperformed all others, reaching ~290 mg L⁻¹ EPS and 28 µg mL⁻¹ IAA in the initial screen. Response-surface methodology was then used to optimize light intensity and photoperiod. EPS peaked at 281.4 mg L⁻¹ under a B:R ratio of 1:5 LED, 85 µmol m⁻² s⁻¹, and a 14.5 h light cycle, whereas IAA was maximized at 34.4 µg mL⁻¹ under cool-white LEDs at a similar irradiance. The quadratic models exhibited excellent predictive power (R² > 0.98) and a non-significant lack of fit, confirming the light regime as the dominant driver of metabolite yield. These results demonstrate that precise photonic tuning can selectively steer carbon flux toward either EPS or IAA, providing an energy-efficient strategy to upscale thermotolerant cyanobacteria for climate-resilient biofertilizers, bioplastics precursors, and other high-value bioproducts. Full article

In this study, we aimed to address the lack of systematic research on key collision dynamics parameters (elastic restitution coefficient) in the full mechanization of rapeseed operations, which hinders the development of precision agriculture. In this present work, the restitution coefficient of rapeseed was systematically investigated, and a predictive model (R² = 0.959) was also established by using Box–Behnken design response surface methodology (BBD-RSM). The results show that the collision restitution coefficient varies in the range of 0.539–0.649, with the key influencing factors ranked as follows: moisture content (M_c) > material layer thickness (L) > drop height (H). The EDEM simulation methodology was adopted to validate the experimental results, and the results show that there is a minimal relative error (−1% < δ < 1%) between the measured and simulated rebound heights, indicating that the established model shows a reliable prediction performance. Moreover, by comprehensively analyzing stress, strain, and energy during the collision process between rapeseed and Q235 steel, it can be concluded that the process can be divided into five stages—free fall, collision compression, collision recovery, rebound oscillation, and rebound stabilization. The maximum stress (1.19 × 10⁻² MPa) and strain (6.43 × 10⁻⁶ mm) were observed at the beginning of the collision recovery stage, which can provide some theoretical and practical basis for optimizing and designing rapeseed machines, thus achieving the goals of precise control, harvest loss reduction, and increased yields. Full article

Effective building operation requires a careful balance between energy conservation and indoor environmental comfort. Although numerous methods have been developed to reduce energy consumption during the operational phase, their objectives and applications vary widely. However, the complexity of building energy management makes it challenging to identify the most suitable methods that simultaneously achieve both comfort and efficiency goals. Existing studies often lack a systematic framework that supports integrated decision-making under comfort constraints. This research aims to address this gap by proposing a decision-making tree for selecting energy conservation methods during building operation with an explicit consideration of indoor environmental comfort. A comprehensive literature review is conducted to identify four main energy-consuming components during building operation: the building envelope, HVAC systems, lighting systems, and plug loads and appliances. Three key comfort indicators—thermal comfort, lighting comfort, and air quality comfort—are defined, and energy conservation methods are categorized into three strategic groups: passive strategies, control optimization strategies, and behavioural intervention strategies. Each method is assessed using a defined set of evaluation criteria. Subsequently, a questionnaire survey is administered for the calibration of the decision tree, incorporating stakeholder preferences and expert judgement. The findings contribute to the advancement of understanding regarding the co-optimization of energy conservation and occupant comfort in building operations. Full article

An increasing global population, rising energy demands, and the shift toward a circular bioeconomy are driving the need for more resource-efficient waste management. The increase in the world population—now exceeding 8 billion as of 2024—results in an increased need for alternative proteins, both human and feed grade proteins, as well as for biopolymers and bioenergy. As such, agricultural, forest, and marine waste biomass represent a valuable feedstock for production of food and feed ingredients, biopolymers, and bioenergy. However, the lack of integrated and efficient valorization strategies for these diverse biomass sources remains a major challenge. This literature review aims to give a systematic approach on the recent research status of agricultural, forest, and marine waste biomass valorization, focusing on cascade processing (a sequential combination of processes such as pretreatment, extraction, and conversion methods). Potential products will be identified that create the most economic value over multiple lifetimes, to maximize resource efficiency. It highlights the challenges associated with cascade processing of waste biomass and proposes technological synergies for waste biomass valorization. Moreover, this review will provide a comprehensive understanding of the potential of waste biomass valorization in the context of sustainable and circular bioeconomy. Full article

Promoting energy efficiency in the Italian production sector is significantly hampered by the lack of knowledge, the scarcity and the limited distribution of tools for supporting energy audits in small and medium-sized enterprises (SMEs) in a wide range of Italian economic sectors (industry, tertiary sector, transport). The Advanced Tool for ENErgy Audit for SMEs, ATENEA4SME, is intended to help SMEs promote energy-efficiency projects, supports energy audits and self-evaluation of energy consumption. The tool uses an original mathematical model that takes into account the results of questionnaires and a multi-criteria analysis to generate recommendations for energy efficiency investments. This article will give a thorough explanation of the tool, emphasizing and outlining the sections as well as the procedures to get the ultimate summary of the energy usage of the enterprises under investigation and the potential for energy saving. From a technological and financial perspective, the tool helps to remove obstacles to the development of energy-efficiency measures. In this article, the IT and methodological structure of the tool will therefore be extensively described, and its operation for the context of SMEs will be illustrated, with application cases. Ample space will be allocated to the dissemination campaign and the replicability of the tool for all economic sectors of the industrial and tertiary sectors. Full article

Currently, Poland is witnessing a dynamic development of the offshore wind energy sector, which will be a key component of the national energy mix. While many international studies have addressed wind energy deployment, there is a lack of research that compares the energy and economic performance of both onshore and offshore wind farms under Polish climatic and spatial conditions, especially in relation to turbine spacing optimization. This study addresses that gap by performing a computer-based simulation analysis of three onshore spacing variants (3D, 4D, 5D) and four offshore variants (5D, 6D, 7D, 9D), located in central Poland (Stęszew, Okonek, Gostyń) and the Baltic Sea, respectively. The efficiency of wind farms was assessed in both energy and economic terms, using WAsP Bundle software and standard profitability evaluation metrics (NPV, MNPV, IRR). The results show that the highest NPV and MNPV values among onshore configurations were obtained for the 3D spacing variant, where the energy yield leads to nearly double the annual revenue compared to the 5D variant. IRR values indicate project profitability, averaging 14.5% for onshore and 11.9% for offshore wind farms. Offshore turbines demonstrated higher capacity factors (36–53%) compared to onshore (28–39%), with 4–7 times higher annual energy output. The study provides new insight into wind farm layout optimization under Polish conditions and supports spatial planning and investment decision making in line with national energy policy goals. Full article

Neglected diseases significantly impact the world, and there is a lack of effective treatments, requiring therapeutic alternatives. Thus, the study of the phytochemical and schistosomicidal activity evaluation of Copaifera oblongifolia leaves’ crude extract was conducted. The quercitrin (1) and afzelin (2) were isolated from the crude extract. In the in vitro schistosomicidal activity test, the isolated compounds demonstrated promising results, with 75% mortality at a concentration of 12.5 µM after 72 h. Molecular docking calculations indicated that compounds 1 and 2 could potentially interact with the amino acids of the FAD binding site in the TGR enzyme, a crucial enzyme for the survival of Schistosoma mansoni. These interactions could have binding energies comparable to praziquantel, a preferred drug for treating schistosomiasis. Therefore, in silico and in vitro investigations are crucial for developing new studies that can reveal the antiparasitic potential of compounds of plant origin. Full article

Rural regions face significant barriers to adopting IoT technologies, due to limited connectivity, energy constraints, and poor technical infrastructure. While urban environments benefit from advanced digital systems and cloud services, rural areas often lack the necessary conditions to deploy and evaluate secure and autonomous IoT solutions. To help overcome this gap, this paper presents the Smart Rural IoT Lab, a modular and reproducible testbed designed to replicate the deployment conditions in rural areas using open-source tools and affordable hardware. The laboratory integrates long-range and short-range communication technologies in six experimental scenarios, implementing protocols such as MQTT, HTTP, UDP, and CoAP. These scenarios simulate realistic rural use cases, including environmental monitoring, livestock tracking, infrastructure access control, and heritage site protection. Local data processing is achieved through containerized services like Node-RED, InfluxDB, MongoDB, and Grafana, ensuring complete autonomy, without dependence on cloud services. A key contribution of the laboratory is the generation of structured datasets from real network traffic captured with Tcpdump and preprocessed using Zeek. Unlike simulated datasets, the collected data reflect communication patterns generated from real devices. Although the current dataset only includes benign traffic, the platform is prepared for future incorporation of adversarial scenarios (spoofing, DoS) to support AI-based cybersecurity research. While experiments were conducted in an indoor controlled environment, the testbed architecture is portable and suitable for future outdoor deployment. The Smart Rural IoT Lab addresses a critical gap in current research infrastructure, providing a realistic and flexible foundation for developing secure, cloud-independent IoT solutions, contributing to the digital transformation of rural regions. Full article