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Enhanced YOLOv8 Model for Accurate and Real-Time Remote Sensing Target Detection
Get PDFCurrent remote sensing image object detection algorithms often struggle with false positives, missed targets, and suboptimal accuracy. To address these issues, we propose an improved YOLOv8 network (PIYN) solution achieved through targeted modifications to the YOLOv8 architecture. The backbone of YOLOv8 utilizes a Cross-Stage Partial (CSP) structure that includes two convolutions, called a faster C2f module. Firstly, we infuse the C2f module integrating an Efficient Multi-Scale Attention (EMA) mechanism, which enhances the module's ability to process information across various scales. Secondly, we introduce a Compact Path Aggregation Network (Compact-PAN) structure within the neck of the network, which reduces the computational complexity of the model. Finally, replacing the Complete Intersection over Union (CIoU) loss function with the Weighted Intersection over Union (WIoU) loss refines the model's detection accuracy. Additionally, we applied K-fold cross-validation on the dataset to mitigate overfitting. Experiments using the extensive Dataset for Object Detection in Aerial images (DOTA) and the Dataset for Object Recognition in Optical Remote Sensing Imagery (DIOR) reveal PIYN's effectiveness: there is a 2.43% and 2.56% increase in Mean Average Precision (mAP) over YOLOv8, respectively, alongside a 4.49% reduction in GFLOPs. These results demonstrate PIYN's capability to enhance accuracy while maintaining efficiency and solidify its progressive and practical impact, particularly for smart city applications
Mono- and bimetallic platinum-based catalysts in dehydrogenation of perhydro dibenzyltoluene
Get PDFLiquid organic hydrogen carriers (LOHCs) are emerging as solutions for storing renewable hydrogen. A particularly promising LOHC candidate system is dibenzyltoluene (DBT) and its fully hydrogenated form, perhydro dibenzyltoluene (H18-DBT). The dehydrogenation reaction of H18-DBT is critical for the feasibility of the LOHC system, requiring catalysts that are active, resistant towards deactivation, and do not promote the decomposition of the LOHC compound. This study examined the dehydrogenation of H18-DBT using both monometallic Pt-catalysts and bimetallic catalysts composed of Ptsingle bondPd, Ptsingle bondRu and Ptsingle bondRe supported on alumina and titania. The extent of dehydrogenation ranged from 32% to 69% over 45 min in a batch reactor, with a molar ratio of H18-DBT to Pt of 400:1. In the series of Pt-catalysts, the highest quantity of weak acid sites and a moderate amount of medium acid sites exhibited the highest dehydrogenation activity. The bimetallic Ptsingle bondRe catalyst on alumina demonstrated improved efficiency in H18-DBT dehydrogenation, though it did not outperform the most active catalyst, monometallic Pt supported on titania. Notably, the decomposition products of H18-DBT in the hydrogen gas reached concentration of 0.03 wt% within 45 min reaction time
Biobased barrier dispersion coating from solvent shifting of functionalized lignin inside cellulose nanofibers aqueous suspensions
No full textIn this study, we present a simple one-pot approach to formulate barrier dispersions by combining nanoscaled cellulose and lignin, while harnessing the hydrophobizing effect of tall oil fatty acid (TOFA) modification. Using an in situ solvent-shifting method, unmodified lignin and TOFA-esterified lignin solutions were directly incorporated into aqueous microfibrillated cellulose (MFC) suspensions, enabling the in situ formation of stable lignin nanoparticles (LNPs and TOFA-LNPs) within the MFC matrix. Nanopapers prepared from TOFA-LNP:MFC dispersion with a ratio of 1:2 exhibited excellent barrier properties, with a water vapor transmission rate of 6 g/m²·day (50 % RH, 23 °C), an oil Cobb1800 value of 0.3 g/m², and a water Cobb1800 value of 12 g/m². The results demonstrate that TOFA modification of lignin and its incorporation within the MFC matrix as nanoparticles, facilitates the formation of dense, uniform films with strong resistance to moisture and oil. To gain a deeper understanding of the system, surface-sensitive quartz crystal microbalance with dissipation monitoring (QCM-D) and atomic force microscopy (AFM) were used to analyze how the TOFA modification of lignin affected its physicochemical interactions within cellulose fibrils. Furthermore, humidity-controlled QCM-D measurements were used to analyze the effect of lignin-based nanoparticles on the water vapor adsorption behavior of MFC at different relative humidities providing new insights into their barrier performance, explored here for the first time. Finally, the successful application of dispersion coatings onto commercial fiber-based substrates demonstrates their industrial potential. This work introduces a versatile and scalable route to fully biobased coatings, advancing the transition toward circular and sustainable packaging solutions.</p
A Review of Public Funding for Agri-Food Exports, 2020–2025
No full textThis report examines the public funding supporting Finnish food exports and internationalization from 2020 to 2025. The study maps key funding sources – including Business Finland, European structural funds, the Rural Development Fund, the European Maritime, Fisheries and Aquaculture Fund (EMFAF), and EU promotion programs – and analyzes their support in fostering food sector growth. The analysis highlights the multi-stage export pathway for food companies, from local business development to international market entry and scaling, emphasizing the complementary roles of innovation funding, regional development, and sectoral collaboration. The report focuses on two themes: export promotion and internationalization, and food tourism. Results show that 48.2 million euros in public support were granted, with the majority directed at companies and also to research and education organisations. Municipalities, city actors and non-profit organizations had a smaller share of the funding. The study also addresses the challenges of data comparability and the need for unified terminology and impact metrics. Recommendations include improving data systems, harmonizing concepts, and developing better impact assessment tools to support the ambitious national goal of doubling food exports by 2031
Large Language Model hallucination mitigation in three industrial use cases
No full textLarge-language models (LLMs) can produce factually false or ungrounded information. This occurs when the language model, being fundamentally a statistical model, generates inaccurate or non-existent information with high confidence in response to a given query. This phenomenon is particularly dangerous in safety-critical systems and involves risks when LLMs are used to access or control hardware such as robots, sensors, and other internet-of-things (IoT) applications. Additionally, in automation-rich industrial environments, effective human-machine cooperation depends on maintaining a shared and adaptive understanding of complex situations. Distributed Situation Awareness (DSA) provides a framework for how awareness emerges collectively across networks of operators, robots, sensors, digital interfaces, and LLM based artificially intelligent systems. LLMs can fuse fragmented data streams into coherent, actionable context, enabling Extended Reality (XR) technologies to strengthen DSA by embedding digital cues into physical workflows. While this process improves coordination and adaptability, it also makes reliable and verifiable model outputs essential, as hallucinations can erode operator trust and compromise distributed decision-making. Therefore, mitigation of hallucinations becomes essential for sustaining stable human–AI teaming. We present three industrial projects where LLMs are at the forefront, highlighting practical approaches for hallucination mitigation and demonstrating a transition from online to offline model. Scope is to demonstrate through architectural means how established mitigation mechanisms can be used in industrial systems.</p
Missions as relational scales of agency:urban leverage for transformative change
No full textThe mission-oriented innovation policy literature has recently attempted to address implementation challenges and identified research needs around the role of cities, scales and agency in implementation. We address these gaps and contribute to the literature, particularly on the spatial governance of mission-oriented innovation policies, through an integrated theoretical framework conceptualising missions as relational scales of agency. A case study of the mobility as a service (MaaS) concept in Finland enables us to identify and discuss scalar tensions related to MaaS failures. We conceptualise those as leverage points for transformative change that underscore the potential of urban policies in integrated transformative mission implementation.</p
Study of Isolation Improvement of Antenna Arrays for D-band Transceiver
No full textThis paper presents an experimental study evaluating the efficiency of various isolation techniques for antenna arrays in the D-band. The influence of antenna polarizations, the distance between the arrays, presence of absorbing materials and metal shield on isolation is studied. The study demonstrates that isolation of up to 80-85 dB between transmitting and receiving antenna arrays in the D-band can be achieved
Scientific assessment for urban air mobility (UAM)
No full textThis review article is the revised and expanded version of the Scientific Assessment for UAM document that the urban air mobility (UAM) working group of the International Forum for Aviation Research (IFAR) developed at the request of the International Civil Aviation Organization (ICAO). The assessment began with a study of the industry landscape, which includes an overview of existing market studies, proposed aircraft designs and concepts, and potential paths for industry evolution. The subsequent scientific assessment, developed through cooperative efforts among international domain experts, captures 17 focus areas relevant to UAM. Each focus area presents opportunities for further research. The assessment was delivered to the ICAO in 2023. This revised and expanded version reflects the UAM domain’s status quo, incorporating the most recent developments and trends identified in 2024. Key takeaways include: the need for further study of the impact of autonomous systems on the industry; infrastructure requirements (including vertiports and weather sensing) to support the industry sector; and data requirements (covering domains such as cybersecurity, emissions, and safety) to ensure safe and scalable UAM operations.</p
Crystal plasticity modelling of carbide network effects on microstructural strain localization and fracture behaviour in bainitic steels
Get PDFVarious steel microstructures contain carbides that are designed to enhance the strength of the material. In Reactor Pressure Vessel (RPV) steel, the carbides are an inherent part of the microstructure, finely distributed throughout the grains and grain boundaries. This work focuses on the investigation of the effect of carbides ranging from 80 nm to on strain and stress localization when the carbides are explicitly introduced in polycrystalline models. Two size dependent crystal plasticity finite element models are used in the investigation to evaluate their feasibility to address localization phenomena with carbide strengthened microstructures. We analysed the effects of carbides on quasi-2D Scanning Electron Microscopy (SEM) based microstructures with realistic carbide mapping, and utilized synthetic 3D computational grain-carbide microstructures to investigate spatial and shape effect of carbides. Microscale digital image correlation (uDIC) measurements show that strain localization is influenced significantly by carbide networks and carbides can promote slip in grains with low Schmid’s factor. Lastly, we demonstrated the effect of large carbides on fracture predictions using a newly developed microstructurally informed brittle fracture model, which represents a step forward compared with existing Beremin-type approaches. It was observed that carbide induced stress/strain heterogeneity alters fracture probability predictions notably
Collaborative Foresight: Major Research Trajectories and Future Research Agenda
No full textCollaborative foresight is increasingly recognized as an important tool for anticipating and shaping the future through engagement with diverse stakeholders. While academic interest in the topic has grown, highlighting its significance, the field remains fragmented. Literature on collaborative foresight is characterized by varying definitions, multiple theoretical foundations, and diverse methodological approaches. This study conducts a bibliometric review to structure the field of collaborative foresight studies, identifying four central research trajectories: (1) Collaboration in Technology Foresight, (2) Collaboration in Scenario Planning, (3) Open Foresight, and (4) Collaboration in Anticipatory Governance. Based on this structured analysis, we identify key research gaps, including the absence of a widely accepted definition of collaborative foresight, weak linkages to ecosystem and strategic management theories, and a lack of structured impact assessments to measure the long-term benefits of collaborative foresight. To address these gaps, we propose a research agenda emphasizing the development of robust theoretical foundations, stronger connections to strategic decision-making, and methodological improvements to enhance the practice and impact of collaborative foresight