Jackson D. Taylor, Emmanuel Fonseca, Lankeswar Dey
et al.
Trojan asteroids are found in the equilateral triangle Lagrange points of the Sun–Jupiter system in a great number, although they also exist less prolifically in other parts of the solar system. Despite up to planetary mass Trojans being predicted in extrasolar systems (i.e., exotrojans), they remain unconfirmed, although strong candidate evidence has emerged recently. For the first time, we extend the search for exotrojans to radio pulsars with low-mass (∼0.01 M _⊙ ) companions using accurately measured pulse times of arrival. With techniques developed for detecting the reflex motion of a star due to a librating Trojan, we place ∼1 M _⊕ upper mass constraints on potential exotrojans around eight pulsars observed in the NANOGrav 15 yr dataset. We find weak evidence consistent with ∼2–4 M _J exotrojans in the PSR J0023+0923 and PSR J1705−1903 binary systems, although the signals likely have a different, unknown source. We also place a libration-independent upper mass constraint of ∼8 M _J on exotrojans in the PSR J1641+8049 system by looking for an inconsistency between the times of superior conjunction as measured by optical light curves and those predicted by radio timing. These results offer initial observational constraints on the existence of exotrojans around pulsars, while their possible formation mechanisms remain unexplored.
This study examines portrayals of marine mammal celebrities (MMCs) in popular culture over the past 70 years, reflecting evolving public attitudes toward ocean conservation. It identifies four main types of MMCs, each linked to a specific era and shaped by changes in media landscapes, perceptions of marine mammal agency and welfare, and conservation priorities: (1) Hollywood MMCs (ca. 1960–1990s)—wild animals captured and exhibited in aquaria, cast as celebrities based on their roles in traditional mass media (blockbuster movies); (2) MMCs in human care (ca. 1990s–2010s)—animals housed in aquaria whose fame stemmed from public concern about their welfare and calls for their release; (3) rescued MMCs (ca. 1980s–present)—marine mammals cared for by humans after they were injured in the ocean; and (4) endangered and dangerous MMCs (2010s–present)—wild animals that approach humans, demonstrate human‐like behaviours, or interact with boats. Introducing the method of “following the animal,” the article provides examples of celebrity animals that illustrate each of the four categories, such as the dolphin Flipper and the walrus Freya. The study contributes to the thematic issue on Ocean Pop: Marine Imaginaries in the Age of Global Polycrisis by highlighting the mutual influence of media, animal celebrity, and conservation, and urges further research into how shifting representations shape global engagement with marine life and the environment.
Vishisht Srihari Rao, Aounon Kumar, Himabindu Lakkaraju
et al.
The integrity of peer review is fundamental to scientific progress, but the rise of large language models (LLMs) has introduced concerns that some reviewers may rely on these tools to generate reviews rather than writing them independently. Although some venues have banned LLM-assisted reviewing, enforcement remains difficult as existing detection tools cannot reliably distinguish between fully generated reviews and those merely polished with AI assistance. In this work, we address the challenge of detecting LLM-generated reviews. We consider the approach of performing indirect prompt injection via the paper’s PDF, prompting the LLM to embed a covert watermark in the generated review, and subsequently testing for presence of the watermark in the review. We identify and address several pitfalls in naïve implementations of this approach. Our primary contribution is a rigorous watermarking and detection framework that offers strong statistical guarantees. Specifically, we introduce watermarking schemes and hypothesis tests that control the family-wise error rate across multiple reviews, achieving higher statistical power than standard corrections such as Bonferroni, while making no assumptions about the nature of human-written reviews. We explore multiple indirect prompt injection strategies–including font-based embedding and obfuscated prompts–and evaluate their effectiveness under various reviewer defense scenarios. Our experiments find high success rates in watermark embedding across various LLMs. We also empirically find that our approach is resilient to common reviewer defenses, and that the bounds on error rates in our statistical tests hold in practice. In contrast, we find that Bonferroni-style corrections are too conservative to be useful in this setting.
Abstract Clear cell renal cell carcinoma (ccRCC), the most common subtype of RCC, requires accurate pathological grading for effective prognosis. However, current grading methods rely heavily on subjective pathologist assessment, leading to variability. While generative artificial intelligence (GenAI) has shown promise in medical imaging, its application in digital pathology remains underexplored. This study evaluates the performance of three multimodal GenAI models—GPT‐4o, Claude‐3.5‐Sonnet, and Gemini‐1.5‐Pro—in ccRCC grading and prognosis prediction. A total of 499 ccRCC slides from The Cancer Genome Atlas and 349 external samples from two independent cohorts were analyzed. A standardized prompt repetition mechanism and variance‐based stability validation method guided GenAI models in extracting 17 pathological features. Feature stability was assessed using intraclass correlation coefficient (ICC). These features, combined with 3 clinical variables, were used to build grading and prognostic models via logistic regression and 113 machine learning algorithms. Performance was benchmarked against CellProfiler, ResNet‐50, DenseNet‐121, attention‐based multiple instance learning (MIL) and Pathology Language and Image Pre‐training, using the concordance index (C‐index) and area under the receiver operating characteristic curve (AUC). Claude‐3.5‐Sonnet outperformed the other two GenAI models (ICC = 0.76; micro‐average AUC = 0.87), exceeding ResNet‐50 (AUC = 0.78) and attention‐based MIL (AUC = 0.70). Its top prognostic models achieved an average C‐index of 0.739, effectively stratifying high‐ and low‐risk patients. Key predictors included stage, calcification, sarcomatoid differentiation, and vascular networks. GenAI, particularly Claude‐3.5‐Sonnet, enhances accuracy and consistency in ccRCC pathology, showing strong potential for clinical use, especially in resource‐limited settings.
Qin Jianjun, Haytham F. Isleem, Walaa J. K. Almoghayer
et al.
Abstract The Purpose of this study is to propose a new integrative framework for athletic performance prediction based on state-of-the-art machine learning analysis and biometric data biometric scanning. By merging physiological signals i.e., Heart rate variability, oxygen consumption, muscle activation patterns, with psychological signals i.e., mental toughness, athlete engagement, group cohesion along with contextual training data, we create a hybrid model that performs superiorly as compared to traditional unidimensional models. Our exercisers were trained using a gradient boosting and neural network to learn the very complex non-linear relationships that exist between the physical and the psychological performance drivers. With a rich sample set of 480 athletes from different sports, the proposed model achieved 90% accuracy (R2 = 0.90) in predicting performance outcomes and outdid the conventional methods with statistical approaches R2 = 0.77) and machine learning based methods (R2 = 0.77) And machine whiz methods. The robust results achieved from the model (over 90%) as compared to conventional nor statistical methods. From the analysis of the features’ importance, the strongest predictor of performance are the Provided Dedicated Athletes’ scores of the Functional Movement Screening (13.7%), athlete dedication (11.5%), maximum acceleration capabilities (10.2%), which verify the relationship along biomechanical, preconceived explosive power and psychological commitment. This reflects the finding whereby deep categorized athletic talent prediction requires a multi-dimensional approach by sophisticated fusion techniques. The framework is useful to coaches and sports scientists because it allows for the individualized design of injury risk mitigation and physiologically and psychologically-focused interpersonal help. This approach integrates multiple factors and constitutes an important progress in sports analytics by providing a comprehensive perspective on the complex realities which influence elite athletic performance.
Offshore wind turbines positioned in deepwater areas are increasingly favored due to them providing superior and stable wind resources. However, the dynamic stability of floating offshore wind turbines (FOWTs) under complex environmental loading remains challenging. This study proposes a novel semi-submersible platform featuring a fractal structure inspired by the venation of Victoria Amazonica and investigates the effects of fractal branching level and biomimetic structural height on platform motions, with the aim of enhancing the overall system stability of FOWTs. Within a high-fidelity computational fluid dynamics (CFD) framework coupled with a dynamic fluid–body interaction (DFBI) model and a volume-of-fluid (VOF) wave model, the dynamic responses of the biomimetic platform are investigated under varying fractal dimensions (<i>D</i><sub>f</sub>) and structural heights. The results indicate that increasing fractal complexity enhances the local wall viscosity effect, significantly improving energy dissipation capabilities within the fractal cavities. Specifically, an eight-level fractal structure shows optimal performance, achieving reductions of approximately 16.94%, 23.26%, and 35.63% in heave, pitch, and rotational energy responses, respectively. Additionally, the increasing fractal height further strengthens energy dissipation, markedly enhancing stability, particularly in pitch motion. These findings underscore the substantial potential of biomimetic fractal designs in enhancing the dynamic stability of FOWTs.
Novel cross-media vehicles can operate efficiently in different media where water entry is a critical process. In this paper, a water–air cross-media unmanned vehicle is designed and its hydrodynamic characteristics during water entry are studied. With the use of STARCCM, the movement of the vehicle during water entry was simulated with the adoption of a VOF multiphase flow model and a Schnerr–Sauer cavitation model and its accuracy was tested. The flow field characteristics of the vehicle under common operating conditions, as well as the influence of the initial water entry speed and angle on the motion state and the force endured by the vehicle under different operating conditions, were simulated. The results show that the overall operating attitude of the vehicle is stable, and the influence of the water entry speed is more significant than that of the water entry angle. The research results provide a theoretical basis and technical support for the design and application of cross-media vehicles, helping to promote cross-media navigation technology.
Albert Kjartan Dagbjartarson Imsland, Pablo Balseiro, Sigurd Handeland
et al.
Acoustic lice treatment (AcuLice) is a newly developed system which uses a composite acoustic sound image with low-frequency sound to remove salmon lice (<i>Lepeophtheirus salmonis</i>) from Atlantic salmon (<i>Salmo salar</i>). The effect of AcuLice treatment on salmon lice dynamics was measured by weekly salmon lice counting at a full-scale production facility from mid-summer 2019 to late-spring 2024. We monitored four production cycles, with AcuLice applied for two of the production cycles and with no AcuLice treatment applied during the other two production cycles as control. This is a follow-up study to our previous work. The numbers of salmon lice treatments and of weeks until the first salmon lice treatment were also compared in the two experimental groups. For the small (sessile and mobile stages) salmon lice, a significantly lower number (mean ± SEM) was shown for the AcuLice group (0.73 ± 0.03) compared with the control group (1.18 ± 0.05). For the mature female salmon lice, a significantly lower number (mean ± SEM) was found for the AcuLice group (0.12 ± 0.01) compared with the control group (0.22 ± 0.03). In addition, the mean (±SEM) number of <i>C. elongatus</i> varied between the two experimental groups and was higher in the control group (0.12 ± 0.01) compared with the AcuLice group (0.03 ± 0.01). In addition, a lower number (mean ± SEM) of salmon lice treatments (1.4 ± 0.17 vs. 4.22 ± 0.20) and a longer production period before the first salmon lice treatment occurred was observed for the AcuLice group (11.2 ± 0.1 weeks) compared with the control group (24.1 ± 2.3 weeks). These data suggest that the use of the AcuLice system significantly reduces the number of salmon lice (by 40–60%) and <i>C. elongatus</i> (by 70%) on farmed Atlantic salmon and reduces the need for traditional salmon lice treatments (by 65%).
ABSTRACT We study production and transportation integration in a make‐to‐order environment with time‐dependent waiting and inventory holding costs. In this problem, manufacturers receive orders from customers, produce and then transport the products to customers, resulting in associated production and transportation costs. Orders, upon receipt, are not immediately produced, and likewise, once produced, they are not instantly transported. This delay in processes incurs additional costs, specifically order waiting costs resulting from the gap between receipt and transportation, and inventory holding costs due to the storage of products preceding their transportation. The objective is to determine an integrated plan of production and transportation that minimizes the total cost of production, waiting, inventory holding, and transportation. We first show that the problem is strongly NP‐hard, and then develop a primal‐dual heuristic algorithm with a worst‐case bound of two. The computational results demonstrate that our algorithms perform well based on randomly generated instances. Finally, we incorporate both limited production capacity and unit production cost into the problem, and extend the proposed algorithm to solve the problem. Additionally, we conduct computational experiments to demonstrate the efficiency and efficacy of the algorithm.
Schooling in fish is linked to a number of factors such as increased foraging success, predator avoidance, and social interactions. In addition, a prevailing hypothesis is that swimming in groups provides energetic benefits through hydrodynamic interactions. Thrust wakes are frequently occurring flow structures in fish schools as they are shed behind swimming fish. Despite increased flow speeds in these wakes, recent modeling work has suggested that swimming directly in-line behind an individual may lead to increased efficiency. However, only limited data are available on live fish interacting with thrust wakes. Here we designed a controlled experiment in which brook trout, Salvelinus fontinalis , interact with thrust wakes generated by a robotic mechanism that produces a fish-like wake. We show that trout swim in thrust wakes, reduce their tail-beat frequencies, and synchronize with the robotic flapping mechanism. Our flow and pressure field analysis revealed that the trout are interacting with oncoming vortices and that they exhibit reduced pressure drag at the head compared to swimming in isolation. Together, these experiments suggest that trout swim energetically more efficiently in thrust wakes and support the hypothesis that swimming in the wake of one another is an advantageous strategy to save energy in a school.
This paper evaluates the contributing factors to maritime dangerous goods (DG) transport accidents by integrating the Entropy Weight (EW) and Grey Relational Analysis (GRA) methods. For this purpose, investigation reports of maritime DG transport accidents that occurred worldwide between 2000 and 2023 are derived from the International Maritime Organization’s Integrated Shipping Information System (IMO GISIS) database’s Marine Casualties and Incidents (MCI) module. Eleven main ship operations and thirteen primary causes were selected by analysing accident investigation reports. The weights of main ship operations are calculated utilizing the EW method. The correlational degrees of the primary causes are then calculated using the GRA method. Most maritime DG transport accidents occur during unberthing, bunkering, and pilotage operations. The most common contributing factors of maritime DG transport accidents are collisions and occupational accidents. Specifically, maritime DG transport accidents are most likely to be caused by collisions during sailing, passage, maneuvering, and bunkering operations, as well as occupational accidents during cargo loading, anchoring, berthing, and mooring operations. The results of this paper can support stakeholders in developing the needed policies to guarantee the safety of maritime DG transport.
Luca Micoli, Tommaso Coppola, Roberta Russo
et al.
This work focuses on the modeling of a zero-emissions, high-speed catamaran ferry employing a full-electric propulsion system. It addresses the global emphasis on full-electric vessels to align with IMO regulations regarding ship emissions and energy efficiency improvement. Using the AVL Cruise-M software, this research verified the implementation of an onboard fuel cell power-generating system integrated with a propulsion plant, aiming to assess its dynamic performance under load variations. The catamaran was 30 m long and 10 m wide with a cruise speed of 20 knots. The power system consisted of a proton-exchange membrane fuel cell (PEM) system, with a nominal power of 1600 kWe, a battery pack with a capacity of 2 kWh, two 777 kW electric motors, and their relative balance of the plant (BoP) subsystems. The simulation results show that the battery effectively supported the PEM during the maneuvering phase, enhancing its overall performance and energy economy.
Marikka Heikkilä, Heidi Himmanen, Olli Soininen
et al.
The maritime industry is rapidly evolving with digital technologies, aiming to enhance efficiency, safety, and sustainability. Recent interest has focused on autonomous vessels and the digitalization of ports, yet fairway development has lagged behind. To effectively support the growing digital and autonomous marine traffic, it is essential that fairways are also upgraded and modernized. Addressing this need, this study examines key elements of Smart Fairways, with a particular focus on Finland’s maritime infrastructure. This research contributes to the development of the Smart Fairways concept by identifying five foundational and ten advanced Smart Fairway service elements. The main finding highlights the foundational role of communication systems in the development of more advanced Smart Fairway services such as Enhanced Vessel Traffic Service, Port just-in-time Service, Remote Pilotage, and Digital Twin of the Physical Fairway.
Jingqian Guo, Lingshuai Meng, Mengmeng Feng
et al.
The widespread use of Unmanned Underwater Vehicles (UUVs) in seafloor observatory networks highlights the need for docking stations to facilitate rapid recharging and effective data transfer. Floating docks are promising due to their flexibility, ease of deployment, and recoverability. To enhance understanding and optimize UUV docking with floating docks, we employ dynamic fluid body interaction (DFBI) to construct a seabed moored suspended dock (SMSD) model that features a guiding funnel, a suspended body, and a catenary of a mooring chain. This model simulates SMSD equilibrium stabilization in various ocean currents. Then, a UUV docking model with contact coupling is developed from the SMSD model to simulate the dynamic contact response during docking. The accuracy of the docking model was validated using previous experimental data. Through investigation of the UUV docking response results, sensitivity studies relating to volume, moment of inertia, mass, and catenary stiffness were conducted, thereby guiding SMSD optimization. Finally, sea tests demonstrated that the SMSD maintained stability before docking. During docking, the SMSD’s rotation facilitated smooth UUV entry. After the UUV docked, the SMSD was restored to its original azimuth, confirming its adaptability, stability, and reliability.
Camera-based visual navigation has great potential for various applications, especially in satellite-signal-degenerated environments. However, the lack of integrity protection has constrained its utilization in safety-critical applications. Integrity characterizes the quality of the information that a navigation system delivers. Integrity frameworks have been developed over decades for satellite navigation, and continue to play an essential role in safety-critical applications like civil aviation. Nevertheless, there are several challenges to quantify the risks associated with visual navigation. Over the last few years, several approaches to tackle these challenges have been investigated. These developments are the first steps toward a reliable visual positioning framework with integrity monitoring capabilities. In this paper, we review the current status, particular challenges, and development trends in visual positioning integrity monitoring. In addition, we propose a preliminary framework so that the future developments on visual navigation integrity can benefit from a systematic approach.
Canals and inland navigation. Waterways, Naval Science
ABSTRACTThis research was aimed to evaluate the safety of the LNG cargo compressor room against unwanted gas leakage from two different re-liquefaction systems applicable for an LNG carrier: 1) the Partial (Full) Re-liquefaction System (P(F)RS) and 2) the combination of Partial Re-liquefaction System and Mixed Refrigerant Re-liquefaction system (PRS+MRS). To achieve this goal, quantitative risk assessment was carried out with the integration of system hierarchical modelling, statistical analysis, and CFD simulation. The frequency of initial leakages, occurring to each component of the re-liquefaction systems, was analysed, whereas for the consequence analysis, a CFD program of PyroSim was employed to simulate the gas dispersion in the confined room fitted with mechanical ventilation systems. In addition, various ventilation capacities were investigated with changes in their allocations in the room in order to determine these parametric influences on the results. The risk level of re-liquefaction systems was determined in a quantitative way. Research results clearly presented the importance of the proper arrangement of the ventilation systems. The risk levels were estimated at 5.6 E-3/year for P(F)RS whereas about 9.6 E-3/year for the PRS+MRS in consideration of current regulations. However, the increase in the ventilation capacity was found to reduce the risk levels. The research findings are highly believed to offer meaningful guidance into future safety regulatory frameworks.
The deep-sea batfish genus <i>Halieutopsis</i> is reviewed based on worldwide collections. Sixteen species are recognized, including five newly described species: <i>Halieutopsis echinoderma</i> sp. nov. from eastern Taiwan and northeastern Australia, <i>Halieutopsis kawaii</i> sp. nov. from Taiwan and Indonesia, <i>Halieutopsis okamurai</i> sp. nov. from southeastern Japan, <i>Halieutopsis murrayi</i> sp. nov. from the Gulf of Aden, and <i>Halieutopsis taiwanea</i> sp. nov. from northeastern Taiwan. These species differ from their congeners in escal morphology, squamation, and morphometric proportions. <i>Dibranchus nasutus</i> Alcock, 1891, a senior synonym of <i>Halieutopsis vermicularis</i> Smith & Radcliffe, 1912, as well as <i>Dibranchus nudiventer</i> Lloyd, 1909 and <i>Coelophrys oblonga</i> Smith & Radcliffe, 1912, are recognized as valid species in <i>Halieutopsis</i>. Comments on the systematics and biogeographic distributions of the species of <i>Halieutopsis</i> are provided, along with a key to the species.