Search Results (23,024)

Rolling bearings in modern wind turbines operate under demanding tribological conditions that include high contact stresses, mixed lubrication, transient loads, electrical discharge, corrosion, and hydrogen-assisted damage. These factors contribute to premature failures such as micropitting, scuffing, white etching cracks (WECs), and electrical fluting, which remain major reliability challenges in both onshore and offshore turbines. Surface-engineering technologies have emerged as effective tools to mitigate these failure modes. Carbon-based coatings improve sliding performance and reduce wear under boundary-lubricated conditions; black oxide conversion layers enhance the corrosion resistance, lubricant retention, and early-life running-in behavior; and insulating ceramic coatings protect generator bearings from electrical discharge damage. Additional solutions, including polymer overlays, composite films, and hybrid ceramic architectures, offer further improvements in friction, surface fatigue resistance, and environmental robustness. This manuscript reviews the current state of coated bearing technologies relevant to wind turbine applications, synthesizing findings from tribological research, industrial practice, and emerging material developments. While only a limited number of coating suppliers provide documented evidence of coating use in wind turbine drivetrain bearings, the collective progress in surface engineering demonstrates clear potential for improving reliability and extending service life across the installed turbine base. The analysis highlights the mechanisms by which coatings enhance performance, the conditions under which they are most effective, and the gaps that remain in field validation and large-scale deployment. Coated bearings represent a promising pathway toward higher turbine availability, reduced maintenance costs, and improved drivetrain durability. Continued advances in carbon-based films, multilayer architectures, and insulating coatings, combined with better integration of lubrication strategies and condition-monitoring technologies, will play an increasingly important role in enabling the next generation of high-power wind energy systems. Full article

Carbon-based materials are widely employed in electrocatalytic energy conversion and storage technologies owing to their high electrical conductivity, chemical stability, tunable structure, and low cost. However, the limited intrinsic activity and surface inertness of pristine carbon materials often necessitate surface modification to generate catalytically active sites and improve interactions with reactants and electrolytes. Among the available approaches, plasma functionalization has emerged as a versatile, rapid, solvent-free, and potentially resource-efficient technique that enables systematic tuning of surface chemistry while often limiting modification primarily to the near-surface region. This review discusses the fundamentals of plasma-assisted surface modification of carbon materials, including plasma generation, reactive species, plasma–surface interaction mechanisms, and the influence of key processing parameters such as gas composition, power, pressure, and treatment time. Particular attention is devoted to plasma-induced heteroatom doping, defect engineering, surface functionalization, and the dynamic structural evolution of carbon frameworks during treatment. The impact of these modifications on the physicochemical properties and electrocatalytic performance of carbon materials is critically examined with respect to representative reactions, including the oxygen reduction, oxygen evolution, and hydrogen evolution reactions. The advantages, limitations, and scalability of plasma technologies are also discussed, along with current challenges in process control and reproducibility. Finally, future opportunities involving operando diagnostics, single-atom catalysts, advanced porous carbon architectures, and industrial-scale plasma processing are highlighted. Plasma processing offers a versatile route to carbon surface and catalyst-interface engineering, although standardized reporting and quantitative plasma–structure–performance relationships are still required for rational process design and scale-up. Full article

Biofilm formation on material surfaces represents a major challenge in many technological and biomedical applications, particularly in confined geometries such as tubes and channels. In this study, the antibacterial performance of a surface dielectric barrier discharge system with liquid electrodes was investigated to develop a plasma-assisted approach for inactivating bacterial biofilms on internal surfaces. The discharge operated along the inner surface of the dielectric tubes as it was gradually filled with water. This configuration created a dynamic plasma–liquid environment in which plasma filaments propagated along the treated surface, while reactive species were produced simultaneously in both the gas and liquid phases. The formation of reactive oxygen and nitrogen species in plasma-treated water was characterized, and its antimicrobial activity was evaluated against planktonic Escherichia coli CCM 3954. The effectiveness of both plasma-activated water and direct plasma exposure in inactivating E. coli biofilms grown on the inner surfaces of polymer tubes was also investigated. The results demonstrate that the investigated surface dielectric barrier discharge configuration enables simultaneous direct plasma treatment and in situ generation of plasma-activated water. This approach shows promise for plasma-assisted decontamination of tubular materials and confined systems, where conventional disinfection methods may be limited. Full article

In recycling of plastic packaging, the deinking of post-consumer waste (PCW) is a key technology to achieve high-quality recyclates that can be used in demanding applications. Removing printing inks minimises the contamination in the mechanical recycling process, enabling the production of (semi)-transparent recycled films with low odour and fewer defects. While the deinking of uniformly printed model films is thoroughly researched and the general mechanism well understood, these findings are not readily transferable to industrial implementation on household PCW. This study systematically investigates the deinking of household PCW flakes using industrially available surfactants. Deinking parameters (water temperature, washing time, lye concentration) are varied with no surfactant added as well as for four industrially available surfactant formulations. The deinking efficiency is determined via an image-based statistical analysis. Via a multiple linear regression, median grey values of the experiments allow insights into the deinking mechanism of PCW flakes. Depending on the surfactant and deinking parameters, either the hydrolysis of the binding agent by sodium hydroxide (NaOH) or the surfactant-based decrease of interfacial energy on the printed surface proved dominant for the overall deinking mechanism. Full article

The ChemiNova project—funded by the Horizon Europe programme and coordinated by the Universitat de València—demonstrates how digital innovation can transform cultural heritage conservation in the face of increasing climate-related emergencies. Through the integration of technologies such as augmented and mixed reality, AI-based analysis, and 3D modelling, ChemiNova will enable real-time monitoring and risk assessment of monuments, museum collections, and movable heritage. These tools became especially relevant during the emergency response to the catastrophic DANA flood that struck the Valencia region on 29 October 2024, which caused extensive damage to both institutional and domestic cultural heritage. In addition to safeguarding private collections, conservation teams intervened in contemporary art holdings at risk. Emergency protocols were activated to clean, stabilize, and digitally document paintings, sculptures, and archival materials using the methodologies developed by ChemiNova. The emergency also revealed the essential role of local museums as emotional and social reference points in times of crisis. These institutions provided spaces for care, community engagement, and memory reconstruction. This experience affirms that conservation must go beyond objects. By combining advanced digital tools with collaborative, community-based processes, projects like ChemiNova point the way toward a more resilient, inclusive, and human-centred approach to cultural heritage preservation. Full article

Effective welfare monitoring in laying hens is increasingly challenged by growing flock sizes, declining farm numbers, and the practical limitations of assessor-based protocols under commercial conditions. Precision Livestock Farming (PLF) technologies offer opportunities to support large-scale welfare assessment, yet their application in laying hens remains predominantly limited to small-scale or prototype systems. This study addresses three complementary objectives aimed at informing future computer-vision-based PLF research and development in commercially housed laying hens. First, a systematic literature review was conducted to identify welfare-related categories monitored in laying hens between 2005 and 2025, the methods used to assess them, and the extent to which automated monitoring approaches have been applied. Second, outcomes of a TransRegional Expert Panel (TREP) within the OMELETTE project were synthesised to rank priority welfare challenges, evaluate the feasibility of different monitoring approaches, and compare expert perspectives with trends identified in the literature. Third, two pan-tilt-zoom (PTZ) camera setups implemented in semi-commercial aviary systems were described as proof-of-concept examples illustrating how multiple welfare challenges can be monitored using a single, multipurpose camera system. The literature review revealed a pronounced imbalance in monitoring frequency, with feather pecking dominating the literature while several other welfare challenges, including piling, disturbed sleep, and toe-pecking, remain comparatively underrepresented. TREP outcomes confirmed feather pecking as the highest-priority welfare challenge but also highlighted the importance of integrated monitoring approaches that combine time-intensive assessments, shorter checklists, and automated systems rather than relying on single indicators. Experts further considered the use of digital devices during routine barn inspections to be practically feasible. The PTZ proof-of-concept demonstrates how priority welfare challenges identified through both literature and expert input can be operationalised through automated, scheduled, and location-specific monitoring under commercial conditions. Together, these findings highlight the need for future PLF research to move beyond isolated measurements and small-scale trials towards integrated, cost-effective, and farm-specific welfare-monitoring systems that support adaptive, data-informed management strategies—for example, within a Plan–Do–Check–Act framework—and enable the development of digital standard operating procedures that generate actionable insights under real-world commercial constraints. Full article

The harvesting of fruit and vegetable crops has long been plagued by prominent issues such as high labor costs, low harvesting efficiency, and high fruit damage rates. The application of object recognition technology has enabled harvesting robots to identify, detect, and locate crops in certain agricultural scenarios, achieving a degree of automated harvesting. However, these systems still suffer from shortcomings such as poor robustness in complex environments, insufficient generalization ability, and high model deployment costs, which significantly limit their large-scale application in agricultural harvesting equipment. This paper comprehensively reviews recent literature in the field of fruit and vegetable target recognition. It summarizes how current research focuses on the implementation principles and directions for the improvement of mainstream methods—including digital image processing, traditional machine learning, and deep learning—while also identifying the remaining issues and challenges facing current technology in terms of algorithmic model real-time performance, robustness, and generalization ability. In the future, target recognition technology is expected to achieve breakthroughs through approaches such as multimodal feature fusion, large-scale models, and semi-supervised learning, evolving toward higher accuracy, faster processing speeds, and easier deployment, thereby providing technical support for the large-scale implementation of smart agriculture. Full article

The Domain Name System (DNS) is a fundamental Internet technology that maps domain names to resource information such as IP addresses. DNS Security Extensions (DNSSEC) ensure the integrity of DNS responses, while DNS over TLS (DoT), DNS over HTTPS (DoH), and DNS over QUIC (DoQ) enhance the confidentiality of name resolution communications. However, these technologies do not verify whether domains resembling legitimate domains, or service domains operated by legitimate organizations, are organizationally or operationally related to them. This paper proposes a framework using X.509 certificates presented by DoT-enabled authoritative DNS servers and DNS-Based Authentication of Named Entities (DANE) TLSA resource records. Here, a related domain belongs to a different namespace but is authorized by the same organization, service provider, or similar entity. Standard TLS certificates are verified using the X.509 Public Key Infrastructure (PKIX), whereas additional certificates indicating related domains are verified using DANE Trust Anchor (DANE-TA), with a source-domain private certification authority (CA) as the trust anchor. We implemented additional certificate verification, Server Name Indication (SNI)-based certificate selection, resolver-side relationship verification, and full-certificate caching. Certificate information returned to stub resolvers or applications is converted into TLSA-compatible data and appended to DNS responses. Evaluation results confirmed that the prototype operated at a sufficiently practical speed and that full-certificate caching reduced the latency associated with inter-domain relationship verification. Full article

Construction supply chains are pivotal to circular economy transitions but remain structurally fragmented, limiting the scalability of resource-efficient solutions. At the same time, digital technologies and life cycle assessment are often deployed in isolation, constraining their ability to enable system-level circularity. Using a theory-building literature synthesis of 141 publications across circular economy, sustainable supply chain management, digitalization, and life cycle sustainability assessment, this study develops an integrated conceptual framework that explains how circular performance may be shaped by AI-enabled decision capabilities, lifecycle sustainability constraints operationalized through PESI-LCA, and system-level alignment conceptualized through DCAM. AI is conceptualized as a dynamic capability for prediction and optimization, while PESI-LCA is positioned as an operationalized LCSA-based constraint system that embeds environmental, social, and economic criteria into decision architectures. DCAM defines the alignment conditions required across digital infrastructure, circular strategies, business models, and institutional enablers. The framework advances a non-additive logic: circular outcomes depend on how sustainability constraints shape AI-driven decision-making and how alignment enables coordinated implementation across supply chains. A key theoretical contribution is the identification of structural distortion as a failure mode in which digital optimization reinforces linear resource flows. The study advances sustainable supply chain theory and offers testable propositions and governance implications for scaling circular construction systems. Full article

Exposure to nitrogen oxide (NOx) in underground mining workings poses a significant threat to the health and safety of workers, while NOx emissions also represent an important environmental challenge associated with the operation of diesel-powered mining equipment. This article provides an overview of primary and secondary methods for limiting emissions and reducing exposure to NOx under underground mining conditions. The primary methods include intensified ventilation, extended ventilation time after blasting, the use of low-emission fuels, and modifications to combustion engines, including exhaust gas recirculation (EGR). The secondary methods include the use of exhaust gas purification technologies such as photocatalysis, oxidation catalysts (DOCs), selective catalytic reduction (SCR), and nitrogen oxide traps (LNTs). The presented solutions were compared in terms of NOx reduction efficiency, implementation costs, technical requirements, and practical applicability in underground workings. The most effective strategies in the short and long term were identified, taking into account the growing role of machine park electrification as a potentially sustainable solution to reducing emissions at their sources. Additionally, an SWOT analysis of NOx emission reduction methods designed for deep underground ore mines was conducted, enabling assessment of their strengths and weaknesses as well as opportunities and threats related to their implementation. The results can support the selection of NOx emission reduction methods that take into account environmental protection, worker safety, technical possibilities, and implementation costs and thus contribute to more sustainable underground mining. Full article

Commercialisation of research outcomes depends not only on technological quality but also on the competences through which research organisations identify market opportunities, coordinate stakeholders and translate knowledge into sustainable value. This study identifies and classifies commercialisation competences in research network organisations and develops a time-structured framework for operationalising their contribution to sustainability-oriented innovation (SOI). A structured review of Scopus and Web of Science publications, using predefined relevance criteria, yielded 129 competence formulations. Competence extraction was conducted by one author, while two authors independently synthesised the formulations into 25 conceptually distinct competences: five cognitive, eight functional, four personal and eight meta-competences. The 25 competences were then mapped against the triple bottom line, dynamic capabilities and ESG perspectives through a consensus-based expert assessment. Ten competences were classified as core sustainability-oriented, twelve as enabling and three as neutral. Because this classification is interpretative rather than empirically validated, it is intended as a transparent analytical proposition for subsequent testing. Each competence was linked to an Activity–Process Performance–Outcome (A–S–W) structure based on leading, diagnostic and lagging indicators, producing 75 illustrative indicators. The proposed numerical thresholds are heuristic calibration examples rather than universal benchmarks. The framework connects competence activation with process quality and commercialisation outcomes while incorporating economic, environmental and social dimensions and provides a basis for competence development, performance monitoring and future empirical validation. Full article

The archaeological record is inherently fragile, and excavation is, by nature, destructive. While the recording of excavation processes has improved significantly, many archaeological sites excavated over the past decades remain under-reported or unpublished. These sites often have incomplete excavation records, hand-drawn sketches, non-annotated photographs, and fragmented fieldnotes associated with them, posing a significant challenge for contemporary researchers attempting to reconstruct past human activities. Recent technological advancements enable the collection of a significant amount of data; however without a proper data management plan (DMP), these records will meet a similar fate. Thus, implementing a DMP and associated narratives allows access to past excavation records, analyses, and interpretations. This paper explores the curatorial practices associated with legacy excavation data, focusing on the use of digital tools to rebuild information obtained during past excavations while emphasizing the need for a DMP as mandatory. The 19th-century cemetery of Carmo in Porto, Portugal, is used as a case study, demonstrating how CAD and GIS tools can be employed to spatialize fragmented data and identify patterns in mortuary practices while implementing appropriate curatorial practices. Despite the limitations imposed by the incompleteness of the original excavation records, in which only 120 of the 480 sets of excavated human remains could be accurately mapped, the analysis provided preliminary insights into the distribution of the human remains and thus the organization of the cemetery. The results highlight the critical need for a robust DMP prior to and during the excavation process, supporting field data collection and long-term curation. This ensures that the ‘destructive’ act of excavation results in a permanent and accessible digital record for future generations. Full article

Mobility-as-a-Service (MaaS) has emerged as a promising approach to urban transportation by integrating multiple mobility services into a single digital platform for trip planning, booking, and payment. More recently, Artificial Intelligence (AI) has expanded the capabilities of MaaS, enabling more efficient data processing, predictive analytics, personalized services, and intelligent decision support. This narrative review examines the current state of research on AI-enabled MaaS from both technological and socioeconomic perspectives. The analysis covers five major research areas: data integration and interoperability, predictive systems and demand forecasting, AI-enabled decision support for policy and planning, fairness and ethical AI, and cybersecurity and privacy protection. The findings show that successful implementation depends not only on advances in AI algorithms but also on high-quality interoperable data, effective governance, regulatory support, public trust, and collaboration among stakeholders. The review concludes that the main challenges facing AI-enabled MaaS are no longer primarily technical but organizational, institutional, and social. Future research should focus on trustworthy and explainable AI, privacy-preserving learning, standardized evaluation methods, fairness-aware optimization, resilient cybersecurity, and long-term assessments of MaaS impacts on sustainable urban mobility. Full article

This narrative and conceptual review examines how irrigation management in Australian sugarcane can progress from practice-based efficiency improvement towards an integrated evidence system supporting productivity, water-quality improvement and nature-positive reporting. It reviews regional irrigation conditions, standard and best management practices, crop and water modelling, grower-facing scheduling, Internet of Things (IoT) monitoring and automation, remote sensing, forecast-informed irrigation and artificial intelligence. It then considers natural-capital, nature-positive and environmental-reporting frameworks relevant to reef-connected sugarcane landscapes. The review identifies a persistent gap between information generated by irrigation technologies and the credible, transparent and auditable indicators required for broader environmental reporting. A five-part integration pathway connects established components from farm monitoring and modelling, environmental-pressure estimation, supporting evidence, documented methods and defined reporting applications. Existing studies support individual components and several adjacent linkages; this review maps how they could operate as a whole system. Farm-scale technology outputs are treated as evidence of management actions or modelled pressure pathways rather than direct measurements of ecosystem condition. Smart irrigation is thereby positioned as an enabling component linking farm profitability, reduced pressure on soil and water assets, and more credible nature-positive water management in Australian sugarcane. Full article

Dry anaerobic digestion (DAD) is increasingly recognized as a promising waste-to-energy pathway for treating high-solids organic wastes. However, the extent to which the contemporary peer-reviewed literature addresses conditions relevant to scalable implementation remains unclear. This systematic review synthesizes evidence from 148 studies on technological performance, process stability, scalability readiness, and deployment conditions. The evidence base was geographically and methodologically concentrated, with a predominance of laboratory-scale, batch-operated, and mesophilic systems. Co-digestion, pretreatment, operating-condition optimization, and recirculation were frequently investigated strategies. Methane performance varied substantially, reflecting differences in feedstock characteristics, solids content, reactor configurations, and operating conditions. Process stability remained a central concern, with pH, volatile fatty acids, and ammonia-related parameters the most frequently reported indicators, consistent with challenges associated with acidification, ammonia inhibition, and mass-transfer limitations. The scalability assessment showed that most studies provided limited evidence on advanced deployment maturity and enabling conditions, while commercial-scale implementation, financing, stakeholder engagement, and policy support were infrequently represented in the reviewed literature. The 2010–2025 peer-reviewed evidence base remains more strongly oriented toward technological and experimental optimization than integrated deployment-oriented assessment. Greater integration of long-term operational validation with techno-economic, institutional, and implementation-related evidence is needed to understand conditions for reliable and scalable DAD deployment. Full article