Istanbul Technical University
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Big data analytics in supply chain management: uncovering emerging trends through a bibliometric network analysis and a systematic literature review
No full textPurpose This study aims to investigate the intersection of supply chain management (SCM) and big data analytics (BDA) through a multidimensional approach that incorporates bibliometric and network analysis (BNA) and a systematic literature review (SLR). Design/methodology/approach BNA and SLR are academic research methods, each with distinct purposes and limitations. BNA manages large datasets, while SLR focuses on smaller ones for in-depth review. As of January 2023, we analysed 851 articles retrieved from the Web of Science (WoS) core collection via BNA. To mitigate against BNA's limitations, we performed an SLR of 194 articles in 2023–2024, unveiling new themes in the “BDA in SCM” domain that were not apparent through BNA alone. Findings The findings demonstrate global collaboration patterns, highlighting China's lead in publications but lower international engagement than the USA's. BDA and the emerging discipline of supply chain resilience are closely interlinked; Industry 4.0 intertwines with sustainability and circular economy (CE) themes, and both are contributions that have been underexplored in previous reviews. Future studies will explore how BDA and other digital technologies enhance Supply Chain Ambidexterity by improving information processing in uncertain environments. Healthcare 4.0 technologies – specifically BDA, AI and Blockchain – boost efficiency, innovation, and risk management. However, the full potential of an intelligent Food Supply Chain (IFSC) lies in the integration of AI-driven systems, BDA and advanced analytics – a step that is still in its early stages. Originality/value Big data analytics in supply chain management is a rapidly evolving research domain without a review paper since 2020 and with more than 500 papers published in 2021–2022. Our novel methodology of supplementing BNA with an SLR allows us to capture newer or niche contributions in the domain of big data analytics in supply chain management. This approach sets the study apart, ensuring insights into the field's current state and future directions. Integrating quantitative (BNA) and qualitative (SLR) approaches provides a well-rounded perspective on the field.https://doi.org/10.1108/jeim-07-2024-037
Revitalizando las interpretaciones materiales: aprendizaje aumentado en educación arquitectónica online mediante materialidad y comunicación
No full textMaterial augmentation and communication techniques in online education enhance architectural thinking and creation, opening new avenues for design exploration. By focusing on responsive constructions and unconventional modeling techniques, this study fosters a more immersive and expressive design approach. The methodology unfolds in three phases: local mapping based on environmental experiences, exploration of alternative material deviations, and the development of new tectonic principles through material representation. These phases critically examine the interaction between modeling techniques and material variations, aligning reality with representative preferences. The primary aim is to challenge conventional architectural modeling through dynamic processes and material perception strategies. Ultimately, the study offers alternative processes centered on materials and communication tools, enriching the educational experience by promoting deeper sensory and intellectual connections with the built environment for future architects.https://doi.org/10.18537/est.v014.n028.a1
A Microfluidic Refreshable Braille Display System
No full texthttps://doi.org/10.1109/smacd65553.2025.11092058https://doi.org/10.1109/SMACD65553.2025.1109205
Valorization of sugar beet pulp waste by extraction of pectin via novel technologies and application in food systems
No full texthttps://doi.org/10.1007/s11694-025-03449-
Crustal Structure across the Northern Scandinavian margin along the Senja OBS Profile 
No full textThe Senja onshore-offshore seismic profile is located in the northwestern part of Fennoscandia, extending from onshore Norway into the North Atlantic Ocean. The Fennoscandian lithosphere has been formed by the amalgamation of terranes and microcontinents to an Archean core, primarily during the Palaeoproterozoic. The later Sveconorwegian (Grenvillian) and Caledonian orogenies had strong effect on the western part of Fennoscandia. The Scandia Mountain range extends along the west coast with elevation up to 2500 m, mainly coinciding with the surface outcrops of Caledonian deformed crust. Its location far from any active plate boundary makes this mountain range enigmatic. The offshore continental part of Fennoscandia experienced a long post-Caledonian extensional period for more than 200 My, and it now forms a continental shelf below sea level extending to the continent to ocean transition.We present a crustal-scale seismic profile along the NW-SE striking Senja OBS Profile in northern Scandinavia between 12°E and 20°E. This profile covers both offshore and onshore domains over a total distance of ~300 km across the Norwegian shelf in the North Atlantic Ocean, Senja Island, and mainland Norway. Airgun shots from the vessel Hakon Mosby were used as sourced for the refraction/wide-angle reflection survey. The dataset includes recordings on 5 ocean bottom seismometers (OBS) on the shelf, slope, and oceanic environment, complemented by 68 onshore stations at 1.3-kilometre intervals. We present a seismic p-wave velocity model derived by ray-tracing modelling of P-wave arrivals along the profile.The model includes a deep sedimentary basin extending to ~10 kilometres depth with velocities between ca. 2 km/s and 5.10 km/s, which gradually thickens from the coast to its maximum thickness of 10 km about 25 km from the coast. This deep sedimentary basin is very wide (approximately 8 km). Further offshore the sedimentary cover of the shelf and oceanic environment is relatively thin. The upper crustal velocity below the sedimentary sequence has velocities of ~ 6.0 km/s. https://doi.org/10.5194/egusphere-egu24-109
Analysis of MLP, CNN, and GNN Architectures for MNIST Digit Classification: Accuracy, Inference Time, and Memory Trade-Offs
No full texthttps://doi.org/10.1109/asyu67174.2025.1120833
Progress and challenges of multi-habitat marine restoration in the eastern Aegean Sea, Türkiye
No full textAbstract Ecological restoration is an increasing global priority and is critical to reverse ecosystem decline caused by anthropogenic impacts. We outline the approach to marine restoration in Gökova Bay, Türkiye and present observations from lesser to more highly assisted restoration interventions and trials, including enforcing multi-habitat No Fishing Zones (including Posidonia oceanica, macroalgae and rocky reef) within a wider Marine Protected Area network. We consolidate evidence from ecological monitoring, small-scale fisheries catch data, marine patrol threat monitoring and a macroalgae trial intervention. It remains difficult to decipher interactions in this system where anthropogenic threats persist and change is not linear but we observe that areas of restoration (No Fishing Zones) demonstrated a lower proportion of Non Indigenous Species compared to fished areas. This work provides a new case study of the progression of multi-habitat interventions and the potential for marine ecosystem recovery in the eastern Mediterranean Sea, informing restoration at scale.https://doi.org/10.1038/s44183-025-00114-9https://doaj.org/article/80077561404047c5a8aff1673837012fhttps://avesis.deu.edu.tr/publication/details/b79483c1-1c78-4e35-9d21-c2dc0e3b3779/oa
Post-Earthquake Fire Resistance in Structures: A Review of Current Research and Future Directions
No full textPost-earthquake fires (PEFs) pose a significant secondary hazard in earthquake-prone regions, compounding the destruction caused by seismic events and threatening structural safety. This review explores the interplay between seismic damage and fire resistance, focusing on ignition sources such as damaged utility systems and overturned appliances, and their cascading effects on structural integrity. Advanced performance-based design approaches are evaluated, emphasizing the integration of probabilistic risk assessments, sequential analysis, and hybrid fire simulations to address multi-hazard scenarios. Key findings of current studies reveal that seismic damage, including spalling, cracking, and loss of fireproofing, substantially reduces the fire resistance of materials like steel and reinforced concrete, exacerbating structural vulnerabilities. Despite advancements, critical gaps persist in experimental data, probabilistic modeling, and comprehensive performance-based design guidelines for PEF scenarios. Addressing these deficiencies requires enhanced data collection, improved modeling techniques, and the integration of PEF considerations into building codes. This study provides a comprehensive review of PEF damage assessment and underscores the need for a holistic, multi-hazard design paradigm to enhance structural resilience and ensure safety in regions subject to seismic and fire risks. These insights provide a foundation for future research and practical applications aimed at mitigating the compounded effects of earthquakes and fires.https://doi.org/10.3390/app15063311https://doaj.org/article/ae755b2d656549658c75fbd9cec64e2
Current methodologies for assessing protein–phenolic interactions
No full texthttps://doi.org/10.1007/s44187-025-00573-
Recycling Methods of Plastic Materials for Circular and Sustainable Production Design: A Review
No full texthttps://doi.org/10.1080/25740881.2025.248085