Uxue Uribe-Martinez, Leire Mijangos, Juan F. Ayala-Cabrera
et al.
The occurrence and spatial distribution of polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), fragrances, UV filters and photoinitiators were investigated in surface sediments of Nerbioi-Ibaizabal estuary between 2005 and 2013, in 2020. Samples were extracted by focused ultrasound solid–liquid extraction technique and analyzed by gas chromatography coupled with mass spectrometry. Total PAHs, PCBs, OCPs, musks, UV filters and photoinitiators concentrations ranged between not detected (n.d.) and 43000 ng g<sup>−1</sup>, n.d. and 2500 ng g<sup>−1</sup>, n.d. and 820 ng g<sup>−1</sup>, n.d. and 880 ng g<sup>−1</sup>, n.d. and 91 ng g<sup>−1</sup> and from nd to 120 ng g<sup>−1</sup>, respectively. Hexachlorocyclohexanes (HCHs) were ubiquitous in the estuary, suggesting that these compounds, although banned, leach from landfills. The PCB concentrations showed a decreasing trend. Ecological risk assessments based on sediment quality guidelines (SQGs) and risk quotient (RQ) suggested semi-volatile organic compounds could represent a potential ecological risk in the Nerbioi-Ibaizabal estuary.
Bassam Adnan, Aviral Gupta, Sreemaee Akshathala
et al.
Benchmarks for large language models (LLMs) have progressed from snippet-level function generation to repository-level issue resolution, yet they overwhelmingly target implementation correctness. Software architecture tasks remain under-specified and difficult to compare across models, despite their central role in maintaining and evolving complex systems. We present ArchBench, the first unified platform for benchmarking LLM capabilities on software architecture tasks. ArchBench provides a command-line tool with a standardized pipeline for dataset download, inference with trajectory logging, and automated evaluation, alongside a public web interface with an interactive leaderboard. The platform is built around a plugin architecture where each task is a self-contained module, making it straightforward for the community to contribute new architectural tasks and evaluation results. We use the term LLMs broadly to encompass generative AI (GenAI) solutions for software engineering, including both standalone models and LLM-based coding agents equipped with tools. Both the CLI tool and the web platform are openly available to support reproducible research and community-driven growth of architectural benchmarking.
The prevailing scaling paradigm of Large Language Models (LLMs) rests on a substrate of "Fuzzy" floating-point arithmetic. To mitigate the inherent instability of this approximate foundation, modern architectures have erected a complex scaffolding of structural and numerical heuristics--Complex Residuals, Pre-RMSNorm, Attention Scaling, and Gradient Clipping--consuming significant compute solely to prevent numerical collapse. We propose a paradigm shift to the "Exact". We introduce the Halo Architecture, grounded in the Rational Field (Q) and powered by a custom Exact Inference Unit (EIU). To resolve the exponential bit-width growth of rational arithmetic, Halo employs a Dual-Ring Topology that unifies two complementary control mechanisms: (1) The Micro-Ring (Continuum Maintenance), which strictly bounds memory complexity via Diophantine Approximation; and (2) The Macro-Ring (Symbolic Alignment), which enforces logical consistency via periodic state collapse. This stable dual-ring substrate allows for the "Great Dismantling" of numerical scaffolding, reducing the Transformer block to its "Clean" algebraic form (Tabula Rasa). Furthermore, we verify the "Efficiency Paradox": the elimination of gradient noise (sigma -> 0) allows for Macro-Learning Rates, potentially reducing the Total Time-to-Convergence by orders of magnitude. Halo demonstrates that General Intelligence requires the hybridization of continuous fields and discrete chains under a rigorous mathematical framework.
Zoe Moorton, Kamlesh Mistry, Rebecca Strachan
et al.
Being able to accurately identify litter in a marine environment is crucial to cleaning up our seas and oceans. Research into object detection techniques to support this identification has been underway for over two decades. However, there have been substantial advancements in the past five years due to the implementation of deep learning techniques. Following the PRISMA-ScR guidelines, we provide an in-depth summary and analysis of recent and significant research contributions to the object detection of macro marine debris. From cross-referencing the results of the literature review, we deduce that there is currently no benchmarked framework for evaluating and comparing computer vision techniques for marine environments. Subsequently, we use the results from our analysis to provide a suggested checklist for future researchers in this field. Furthermore, many of the respected researchers in this field have advocated for a comprehensive database of underwater debris to support research developments in intelligent object detection and identification.
Noise interference and multipath effects in complex marine environments seriously constrain the performance of hydroacoustic positioning systems. Traditional millisecond-level signal application and processing methods are widely used in existing research; however, it is difficult to meet the requirements of centimeter-level positioning accuracy in marine engineering. To address this problem, this study proposes a hydroacoustic positioning method based on a short baseline system for the cooperative reception of multi-channel signals. The method adopts ultra-short pulse signals with microsecond pulse width, and significantly improves the system signal-to-noise ratio and anti-interference capability through multi-channel signal alignment and coherent superposition techniques; meanwhile, a joint energy gradient-phase detection algorithm is designed, which solves the instability problem of the traditional cross-correlation algorithm in the detection of ultra-short pulse signals through the identification of signal stability intervals and accurate phase estimation. Simulation verification shows that the 8-hydrophone × 4-channel configuration can achieve 36.06% signal-to-noise gain under harsh environmental conditions (−10 dB), and the performance of the joint energy gradient-phase detection algorithm is improved by about 19.1% compared with the traditional method in an integrated manner. Marine tests further validate the engineering practicability of the method, with an average SNR gain of 2.27 dB achieved for multi-channel signal reception, and the TDOA estimation stability of the new algorithm is up to 32.0% higher than that of the conventional method, which highlights the significant advantages of the proposed method in complex marine environments. The results show that the proposed method can effectively mitigate the noise interference and multipath effects in complex marine environments, significantly improve the accuracy and stability of hydroacoustic positioning, and provide reliable technical support for centimeter-level accuracy applications in marine engineering.
Modular shipbuilding, as a cutting-edge ship construction paradigm, enables parallel manufacturing across workshops and stages—a core advantage that significantly shortens the total shipbuilding cycle, making it pivotal for modern shipyards to enhance productivity. However, this mode decomposes the integrated shipbuilding project into a large number of interdependent sub-activities spanning three key stages (fabrication, logistics, and assembly). Further, the duration of these sub-activities is inherently uncertain, primarily due to the extensive manual operations, variable on-site conditions, and supply chain fluctuations inherent in shipbuilding. These characteristics collectively pose a formidable challenge to project planning that pursues both high efficiency and low cost. To address this challenge, this paper proposes a Strategy-Group Evolution algorithm. First, the modular shipbuilding process scheduling problem is mathematically formulated as a resource-constrained three-stage multi-objective optimization model, where triangular fuzzy numbers are employed to characterize the uncertain sub-activity durations. Second, a two-layered Strategy-Group Evolution algorithm is designed for solving this model: the inner layer comprises 12 practical priority rules tailored to modular shipbuilding’s multi-stage features, while the outer layer adopts a genetic algorithm-based evolution policy to schedule and optimize the assignment of inner-layer rules to activity groups. The core of the Strategy-Group Evolution algorithm lies in dynamically assigning suitable strategies to different activity groups and evolving these assignments toward optimality—this avoids the limitation of a single priority rule for all stages, thereby facilitating the search for global optimal solutions. Finally, validation tests on real cruise ship construction projects and benchmark datasets demonstrate the efficacy and superiority of the proposed Strategy-Group Evolution algorithm.
While battery-powered propulsion represents a promising pathway for inland waterway freight, its widespread adoption is hindered by range anxiety and high investment costs. Strategic energy replenishment has emerged as a critical and cost-effective solution to extend voyage endurance and mitigate these barriers. This paper introduces a novel approach to optimize energy replenishment strategies for inland electric ships that considers the possibility of adopting multiple technologies (charging and battery swapping) and partial replenishment. The proposed approach not only identifies optimal replenishment ports but also determines the technology to employ and the corresponding amount of energy to replenish for each operation, aimed at minimizing total replenishment costs. This problem is formulated as a mixed-integer linear programming model. A case study of a 700-TEU electric container ship operating on two routes along the Yangtze River validates the effectiveness of the proposed approach. The methodology demonstrates superior performance over existing approaches by significantly reducing replenishment costs and improving solution feasibility, particularly in scenarios with tight schedules and limited technology availability. Furthermore, a sensitivity analysis examines the impacts of key parameters, offering valuable strategic insights for industry stakeholders.
Marius Manolache, Alexandra Ionelia Manolache, Gabriel Andrei
Excessive reliance on traditional energy sources such as coal, petroleum, and gas leads to a decrease in natural resources and contributes to global warming. Consequently, the adoption of renewable energy sources in power systems is experiencing swift expansion worldwide, especially in offshore areas. Floating solar photovoltaic (FPV) technology is gaining recognition as an innovative renewable energy option, presenting benefits like minimized land requirements, improved cooling effects, and possible collaborations with hydropower. This study aims to assess the levelized cost of electricity (LCOE) associated with floating solar initiatives in offshore and onshore environments. Furthermore, the LCOE is assessed for initiatives that utilize floating solar PV modules within aquaculture farms, as well as for the integration of various renewable energy sources, including wind, wave, and hydropower. The LCOE for FPV technology exhibits considerable variation, ranging from 28.47 EUR/MWh to 1737 EUR/MWh, depending on the technologies utilized within the farm as well as its geographical setting. The implementation of FPV technology in aquaculture farms revealed a notable increase in the LCOE, ranging from 138.74 EUR/MWh to 2306 EUR/MWh. Implementation involving additional renewable energy sources results in a reduction in the LCOE, ranging from 3.6 EUR/MWh to 315.33 EUR/MWh. The integration of floating photovoltaic (FPV) systems into green hydrogen production represents an emerging direction that is relatively little explored but has high potential in reducing costs. The conversion of this energy into hydrogen involves high final costs, with the LCOH ranging from 1.06 EUR/kg to over 26.79 EUR/kg depending on the complexity of the system.
Tim Wittenborg, Ildar Baimuratov, Ludvig Knöös Franzén
et al.
The aerospace industry operates at the frontier of technological innovation while maintaining high standards regarding safety and reliability. In this environment, with an enormous potential for re-use and adaptation of existing solutions and methods, Knowledge-Based Engineering (KBE) has been applied for decades. The objective of this study is to identify and examine state-of-the-art knowledge management practices in the field of aerospace engineering. Our contributions include: 1) A SWARM-SLR of over 1,000 articles with qualitative analysis of 164 selected articles, supported by two aerospace engineering domain expert surveys. 2) A knowledge graph of over 700 knowledge-based aerospace engineering processes, software, and data, formalized in the interoperable Web Ontology Language (OWL) and mapped to Wikidata entries where possible. The knowledge graph is represented on the Open Research Knowledge Graph (ORKG), and an aerospace Wikibase, for reuse and continuation of structuring aerospace engineering knowledge exchange. 3) Our resulting intermediate and final artifacts of the knowledge synthesis, available as a Zenodo dataset. This review sets a precedent for structured, semantic-based approaches to managing aerospace engineering knowledge. By advancing these principles, research, and industry can achieve more efficient design processes, enhanced collaboration, and a stronger commitment to sustainable aviation.
The rapid advancement of AI-assisted software engineering has brought transformative potential to the field of software engineering, but existing tools and paradigms remain limited by cognitive overload, inefficient tool integration, and the narrow capabilities of AI copilots. In response, we propose Compiler.next, a novel search-based compiler designed to enable the seamless evolution of AI-native software systems as part of the emerging Software Engineering 3.0 era. Unlike traditional static compilers, Compiler.next takes human-written intents and automatically generates working software by searching for an optimal solution. This process involves dynamic optimization of cognitive architectures and their constituents (e.g., prompts, foundation model configurations, and system parameters) while finding the optimal trade-off between several objectives, such as accuracy, cost, and latency. This paper outlines the architecture of Compiler.next and positions it as a cornerstone in democratizing software development by lowering the technical barrier for non-experts, enabling scalable, adaptable, and reliable AI-powered software. We present a roadmap to address the core challenges in intent compilation, including developing quality programming constructs, effective search heuristics, reproducibility, and interoperability between compilers. Our vision lays the groundwork for fully automated, search-driven software development, fostering faster innovation and more efficient AI-driven systems.
Nasir U. Eisty, Jeffrey C. Carver, Johanna Cohoon
et al.
In the evolving landscape of scientific and scholarly research, effective collaboration between Research Software Engineers (RSEs) and Software Engineering Researchers (SERs) is pivotal for advancing innovation and ensuring the integrity of computational methodologies. This paper presents ten strategic guidelines aimed at fostering productive partnerships between these two distinct yet complementary communities. The guidelines emphasize the importance of recognizing and respecting the cultural and operational differences between RSEs and SERs, proactively initiating and nurturing collaborations, and engaging within each other's professional environments. They advocate for identifying shared challenges, maintaining openness to emerging problems, ensuring mutual benefits, and serving as advocates for one another. Additionally, the guidelines highlight the necessity of vigilance in monitoring collaboration dynamics, securing institutional support, and defining clear, shared objectives. By adhering to these principles, RSEs and SERs can build synergistic relationships that enhance the quality and impact of research outcomes.
This study examines global research trends in shipbuilding materials using bibliometric matching and addresses the gap in the literature stemming from the lack of a comprehensive bibliometric study directly focusing on shipbuilding materials. The Scopus database was searched for studies published between 1970 and 2024; the starting year was chosen because it corresponds to the period when research on modern shipbuilding materials accelerated with advances in welding/joining processes, corrosion protection, and material testing standards. The search used the keywords “ship hull materials,” “naval architecture materials,” and “marine vehicle construction materials.” The latter two terms were defined to encompass structural and construction elements directly related to shipbuilding. Bibliometric matching identified leading countries, institutions, journals, frequently cited studies, and thematic clusters. The thematic framework is organized according to four main material groups: wood, steel, aluminum, and composites. The findings indicate a growing emphasis on composite materials, and ongoing research on improving corrosion resistance, strength, and sustainability in steel and aluminum. The results obtained provide a comprehensive overview of the subject and produce insights that can contribute to the shaping of future research agendas in marine engineering and naval architecture. ------------------------------------------------------------------------------Cite this article: Sekban, D. M., Berigel, M., & Kirma, F. (2026). Shipbuilding materials: A bibliometric analysis of research trends. Maritime Technology and Research, 8(2), 281595. https://doi.org/10.33175/mtr.2026.281595 ------------------------------------------------------------------------------ Highlights Summarizes recent studies on materials in maritime structural applications. Presents a 50-year bibliometric analysis of shipbuilding materials research. Identifies top countries, institutions, and key authors in the maritime field. Reveals thematic shifts and keyword trends in naval material studies. Maps international collaboration networks in shipbuilding materials research. Highlights emerging topics such as composites, corrosion, and eco-friendly design.
This paper studies the trajectory tracking issue for an underactuated autonomous underwater vehicle (AUV) in the horizontal plane. The desired velocity–tracking error relationship (DVTER) is constructed according to the kinematics and kinetic equation, which means that the expected velocities are built so that the position tracking errors converge to 0. Moreover, the limitation of obtaining the expected velocity by directly differentiating the desired position values is avoided. Then, the nonsingular fast terminal sliding mode (TSM) controller is developed to ensure that the velocities converge to the designed expected values in finite time, and tracking speed is improved by comparing with the traditional nonsingular terminal sliding mode method. It turns out that the expected trajectory can be tracked by an underactuated AUV. Finally, the efficiency of the constructed control mechanism is confirmed by simulation results.
Joseph Zuckerman, John-David Wellman, Ajay Vanamali
et al.
We present several enhancements to the open-source ESP platform to support flexible and efficient on-chip communication for programmable accelerators in heterogeneous SoCs. These enhancements include 1) a flexible point-to-point communication mechanism between accelerators, 2) a multicast NoC that supports data forwarding to multiple accelerators simultaneously, 3) accelerator synchronization leveraging the SoC's coherence protocol, 4) an accelerator interface that offers fine-grained control over the communication mode used, and 5) an example ISA extension to support our enhancements. Our solution adds negligible area to the SoC architecture and requires minimal changes to the accelerators themselves. We have validated most of these features in complex FPGA prototypes and plan to include them in the open-source release of ESP in the coming months.