Influence of Soil Damping and Aerodynamic Damping on the Dynamic Response of Monopile Wind Turbines under Earthquake and Wind Loads

Vibration damping is essential for predicting the responses of wind turbines, and contributions mainly come from structural, soil, and aerodynamic damping. In engineering design, it is difficult to precisely account for the individual contributions of each damping source. As a result, a simplified approach is commonly used, where a total damping factor is applied that combines the effects of structural, soil, aerodynamic, and other damping sources. However, the accuracy of this simplified approach in predicting the dynamic response of turbines has not been thoroughly evaluated. This study primarily focuses on the applicability of vibration-damping simplification methods, particularly in analyzing the dynamic response of turbines under earthquake and wind loads.

The Role of AI-Driven Synergy in Achieving Net Zero Buildings

Leveraging Drone Technology for Precision Agriculture: A Comprehensive Case Study in Sidi Bouzid, Tunisia

The integration of drone technology in precision agriculture offers promising solutions for enhancing crop monitoring, optimizing resource management, and improving sustainability. This study investigates the application of UAV-based remote sensing in Sidi Bouzid, Tunisia, focusing on olive tree cultivation in a semi-arid environment. REMO-M professional drones equipped with RGB and multispectral sensors were deployed to collect high-resolution imagery, enabling advanced geospatial analysis. A comprehensive methodology was implemented, including precise flight planning, image processing, GIS-based mapping, and NDVI assessments to evaluate vegetation health. The results demonstrate the significant contribution of UAV imagery in generating accurate land use classifications, detecting plant health variations, and optimizing water resource distribution. NDVI analysis revealed clear distinctions in vegetation vigor, highlighting areas affected by water stress and nutrient deficiencies. Compared to traditional monitoring methods, drone-based assessments provided high spatial resolution and real-time data, facilitating early detection of agronomic issues. These findings underscore the pivotal role of UAV technology in advancing precision agriculture, particularly in semi-arid regions where climate variability poses challenges to sustainable farming. The study provides a replicable framework for integrating drone-based monitoring into agricultural decision-making, offering strategies to improve productivity, water efficiency, and environmental resilience. The research contributes to the growing body of knowledge on agricultural technology adoption in Tunisia and similar contexts, supporting data-driven approaches to climate-smart agriculture.

Synthetic Biology Boosts the Biological Depolymerization and Upcycling of Waste Plastic Resources

The high molecular weight, hydrophobicity, and strong chemical bonds of petroleum-based synthetic plastics make them highly resistant to both abiotic and microbial degradation. This resistance plays a significant role in the growing problem of “white pollution” where the accumulation of plastic waste has become a major environmental issue worldwide. Currently, plastic waste management relies largely on landfill disposal and incineration, with only about 20% of plastic waste being recycled. However, both methods create secondary environmental risks, such as contamination of groundwater, soil, air, and oceans. Therefore, developing a sustainable and efficient approach for recycling and reusing plastic waste is essential for tackling plastic pollution and promoting a circular plastic economy. One promising solution involves utilizing microorganisms and enzymes to break down plastics into oligomers or monomers, which can then be transformed into valuable chemicals. This method provides a more environmentally friendly and milder alternative to conventional waste management techniques. This review explores recent progress in biodepolymerization and biotransformation processes for plastic waste, including the identification of plastic-degrading microorganisms and enzymes, the creation of microbial consortia and enzyme mixtures, an investigation into the mechanisms of plastic depolymerization, and the conversion of degradation products into useful materials such as chemicals, energy, and other resources. Despite these advancements, several challenges remain, such as the limited availability of effective degradation enzymes, low degradation efficiency, and difficulties in utilizing the breakdown products. However, emerging technologies in synthetic biology, such as high-throughput screening, evolutionary metabolic engineering, and bioinformatics to study catalytic mechanisms of degradation enzymes, offer promising solutions to address these issues. By improving enzyme design, optimizing microbial consortia interactions, and developing efficient metabolic pathways for plastic degradation products, these innovations could greatly enhance plastic biodegradation. These advancements hold the potential to provide environmentally sustainable, economically feasible, and technically viable solutions for promoting a circular plastic economy, particularly in countries like China.

Deciphering How Promoting Flower-Viewing Economy for Construction of Harmonious-Villages in Mountainous and Hilly Areas

Sustainable development in mountainous and hilly regions is a critical component of global sustainability efforts. These regions are facing numerous challenges, including ecological fragility, labor migration, and resource scarcity and imbalance. Addressing these issues is imperative for sustainable development; this study identifies two primary conditions necessary for sustainable development in mountainous regions: achieving human and nature’s sustainable development, which provides reliable material support and social support for achieving the same in the mountainous and hilly regions. The flower-viewing economy, derived from transforming China’s mountain agriculture, is an efficient new format for mountainous and hilly regions. To verify these primary conditions, this study constructed a flower-viewing economy from three dimensions: material support, subject relationship, and expectation, using the peach blossom festival in Tingzi Village, Taihe Town of Chongqing City, as an example. Here, we explained that a sustainable development model focused on benefiting farmers is an endogenous, farmer-centered pathway to sustainable development, highly relevant to promoting sustainable development in developing countries’ mountain villages.

Life Cycle Assessment of Tensile Specimens of Stainless Steel Obtained by Additive Manufacturing versus Conventional Manufacturing

Life Cycle Assessment (LCA) of additive manufacturing (AM) evaluates the environmental impacts associated with each stage of the process, from raw material extraction to end-of-life disposal. Unlike conventional manufacturing, AM offers significant advantages, such as reduced material waste, optimized designs for lightweight structures, and localized production, which can decrease transportation emissions. However, its environmental benefits are context-dependent, as energy-intensive processes like laser powder bed fusion or high reliance on specific materials can offset these gains. LCA provides a comprehensive framework to assess these trade-offs, guiding sustainable decision-making by identifying hotspots in energy use, material efficiency, and recyclability, ultimately driving innovation towards greener AM practices. This research conducted a cradle-to-gate study of a cylindrical dog-bone tensile specimen. The life-cycle inventory data were obtained from Ecoinvent for conventional manufacturing, while data from the literature review and our research were employed for laser-based powder bed fusion. The results obtained show that the additive manufacturing process is more environmentally friendly. Although the environmental impact is minor, this process consumes a large amount of energy, mainly due to the atomization process and the high laser power. Regarding the mechanical response, AM reduced the ductility but increased the yield strength and achieved the same fracture strength.

Thermal Characterization Study of Double End Face Grinding Powder Metallurgy Stainless Steel 316L

Double end face grinding machining is a highly efficient surface grinding technique. And grinding temperature is an important factor affecting the surface quality of workpieces. However, it is difficult to monitor the surface temperature of the workpiece in real time because of the covered contact between the grinding wheel and the upper and lower surfaces of the workpiece during the machining process. This paper aims to conduct a mechanistic analysis and experimental investigation of the machining process to address this challenge. Initially, the paper conducts an analysis of the kinematic mechanism, modal analysis, and the grinding force mechanism specific to the double end face grinding process. Afterwards, the mechanisms leading to the generation of grinding heat and the associated heat transfer mechanisms are explored in depth. The paper then proceeds to solve the instantaneous temperature field during double end face grinding by the finite element method (FEM). Furthermore, the micro and macro profile heights of the machined workpiece surfaces are measured and analyzed. The results show that the machined workpiece surface shows a high center and low edge. This is due to the fact that the temperature at the edge of the workpiece is higher than the center during machining, resulting in more material removal. Through these investigations, the study is able to determine the optimal process parameters for the machining process. This in turn improves machining efficiency and product conformity. And these findings not only guide practical production processes but also provide a foundation for future theoretical research in this area.

Cement-Free Binders in Alumina-Magnesia Refractory Castables—A Review

To solve the problem of the accelerated deterioration of calcium aluminate (CAC)-bonded alumina-magnesia refractory castables during the secondary refining process, the development of cement-free binders has emerged as one significant research field of castables. The hydration behavior, curing mechanism, and properties of the most recent research on cement-free binders are compared in this paper. The problems and the modification of each binder of recent research are summarized. High-temperature performance of the castables bonded by traditional hydraulic cement-free binders (ρ-Al₂O₃ and activated MgO) is outstanding, explosive spalling resistance of the castables bonded by sol binders (silica sol, alumina sol) is good, and the properties of the castables bonded by novel organic hydratable binder (hydratable magnesium citrate) combine the advantages of these two binders above, but the mid-temperature mechanical strength is low. Furthermore, alumina-magnesia castables bonded by organic-composited inorganic cement-free binders are expected to be a future domain.

Digital Twin and Artificial Intelligence in Machining: A Bibliometric Analysis

The past decade has witnessed an exodus toward smart and lean manufacturing methods. The trend includes integrating intelligent methods into sustainable manufacturing systems purposely to improve the machining efficiency, reduce waste and also optimize productivity. Manufacturing systems have seen transformations from conventional methods, leaning towards smart manufacturing in line with the industrial revolution 4.0. Since the manufacturing process encompasses a wide range of human development capacity, it is essential to analyze its developmental trends, thereby preparing us for future uncertainties. In this work, we have used a Bibliometric analysis technique to study the developmental trends relating to machining, digital twins and artificial intelligence techniques. The review comprises the current activities in relation to the development to this area. The article comprises a Bibliometric analysis of 464 articles that were acquired from the Web of Science database, with a search period until November 2024. The method of obtaining the data includes retrieval from the database, qualitative analysis and interpreting the data via visual representation. The raw data obtained were redrawn using the origin software, and their visual interpretations were represented using the VOSviewer software (VOSviewer_1.6.19). The results obtained indicate that the number of publications related to the searched keywords has remarkably increased since the year 2018, achieving a record maximum of over 80 articles in 2024. This is indicative of its increasing popularity. The analysis of the articles was conducted based on the author countries, journal types, journal names, institutions, article types, major and micro research areas. The findings from the analysis are meant to provide a bibliometric explanation of the developmental trends in machining systems towards achieving the IR 4.0 goals. Additionally, the results would be helpful to researchers and industrialists that intend to achieve optimum and sustainable machining using digital twin technologies.

The Emerging “AI Artists”: Breaking the Metacrisis and the Fear of Losing Human Creativity

The emergence of artificial intelligence (AI) in the creative arts has ignited a global discourse on the intersection of technology, human creativity, and artistic expression. This paper examines the rise of “AI artists” within the broader context of neuropsychology, the metacrisis, and theories of art and creativity. Drawing on Ian McGilchrist’s hemispheric theory, it explores how AI, often associated with left-hemisphere analytical dominance, can paradoxically contribute to right-hemisphere creative processes. The study evaluates the role of AI in expanding artistic boundaries, democratizing creative expression, and redefining authorship, while addressing concerns about originality, cultural significance, and the potential devaluation of human-made art. Through an anthropological and philosophical lens, the paper argues that AI does not replace human creativity but rather augments it, offering novel tools for artistic exploration. By integrating insights from cognitive science, aesthetics, and digital humanities, this article positions AI as a collaborator in artistic evolution rather than a competitor. Ultimately, there is an assertion that the human capacity for meaning-making and emotional resonance remains irreplaceable, ensuring that human creativity persists and thrives alongside AI-generated art.