Pierre Daniel, Guy Claireaux, Nicolas Cormier
et al.
The disappearance of the trawler <i>Ravenel</i> in January 1962, resulting in the loss of fifteen men from the Saint-Pierre-and-Miquelon archipelago, has long remained unresolved. This study integrates archival documentation, eyewitness testimony, atmospheric and oceanic reanalyses, and probabilistic drift modelling to reconstruct the circumstances of the loss and to constrain the wreck location. Backward and forward drift simulations were conducted using the MOTHY sea-drift model, incorporating high-resolution tidal dynamics and wind forcing from ERA-20C and ERA5 reanalysis. Results show that uncertainty in debris stranding time exerts a much stronger influence on reconstructed drift paths than uncertainty in stranding location. The discovery of the wreck in May 2025 enabled forward simulations that indicated a most probable sinking time, with ERA5 producing debris stranding times consistent with historical observations. These results confirm the predictive skill of the modelling framework while highlighting remaining uncertainties regarding the sequence of events preceding the sinking.
ObjectivesIn order to ensure the safe and stable operation of a shipboard power system under fault conditions, a dynamic reconfiguration optimization method is proposed that considers time-varying load characteristics.MethodsFirst, considering the topological structure, generation capacity limit, line current, node voltage and other constraints of the shipboard power system, a dynamic reconfiguration optimization strategy is proposed to minimize weight load cutting and voltage deviation. Next, an improved inertial particle swarm optimization algorithm is used to solve the optimization model. Finally, a typical shipboard power system is used as an example to verify the effectiveness of the proposed method.ResultsThe simulation results show that compared with the static reconfiguration method, the dynamic reconfiguration method can reduce the system's voltage deviation by 9.94%, thus significantly improving the quality of the network power supply.ConclusionsThe results of this study can provide references for the reliability design of shipboard power systems.
Alfonso Arrieta-Pastrana, Edwin A. Martínez-Padilla, Modesto Pérez-Sánchez
et al.
Currently, hydrodynamic models for bay and estuarine systems involve many parameters that require proper calibration to design coastal structures effectively. However, in coastal regions with limited data availability, the implementation of such models becomes challenging. This research introduces a simplified hydrodynamic methodology designed to analyse the impact of hydraulic control structures in shallow waters. This approach offers a computationally efficient alternative that allows engineers to rapidly evaluate the impact of horizontal and vertical constrictions in shallow waters experiencing wave propagation. A practical application is demonstrated in a one-dimensional channel with a length of 200,000 m and an average depth of 5 m. The only parameter required for calibration in the proposed methodology is bed friction. The three analysed scenarios—longitudinal constriction, plan-view constriction, and the influence of bed friction—demonstrate the model’s sensitivity to these variations, highlighting its reliability as a decision-making tool for coastal engineering projects. Moreover, the comparison of the proposed hydrodynamic simulation methodology at the stabilised tidal inlet structure in Cartagena de Indias, Colombia, demonstrated its ability to reproduce observed water levels accurately, reinforcing its reliability and potential for broader application.
With the increasing demand for marine resource development and environmental protection, underwater robots have an urgent need for flexible, safe, and efficient soft grasping technology. This paper described three main actuation design methods for underwater soft grippers: fluid variable pressure drive, cable drive, and smart material drive. Based on this, the research progress of key technologies such as bio-inspired design, stiffness adjustment technology, integration of grasping and perception, and multi-modal grasping was analyzed. Combined with typical application scenarios such as marine waste cleanup, aquatic product fishing, underwater archaeology, and cultural relic protection, as well as biological sample collection, the unique advantages of soft grippers in non-destructive sampling, adaptability to multiple types of objects, and fine operations in the deep sea were analyzed. Finally, the future research directions of underwater soft grippers were prospected, and it is pointed out that efforts should be focused on the research and development of high-performance underwater intelligent materials, the integration of multiple driving methods, and the optimization of energy and control systems, so as to promote the evolution of the gripper towards deep sea and intelligentization and achieve reliable underwater operations in all scenarios.
Roham Koohestani, Philippe de Bekker, Begüm Koç
et al.
Benchmarks are essential for unified evaluation and reproducibility. The rapid rise of Artificial Intelligence for Software Engineering (AI4SE) has produced numerous benchmarks for tasks such as code generation and bug repair. However, this proliferation has led to major challenges: (1) fragmented knowledge across tasks, (2) difficulty in selecting contextually relevant benchmarks, (3) lack of standardization in benchmark creation, and (4) flaws that limit utility. Addressing these requires a dual approach: systematically mapping existing benchmarks for informed selection and defining unified guidelines for robust, adaptable benchmark development. We conduct a review of 247 studies, identifying 273 AI4SE benchmarks since 2014. We categorize them, analyze limitations, and expose gaps in current practices. Building on these insights, we introduce BenchScout, an extensible semantic search tool for locating suitable benchmarks. BenchScout employs automated clustering with contextual embeddings of benchmark-related studies, followed by dimensionality reduction. In a user study with 22 participants, BenchScout achieved usability, effectiveness, and intuitiveness scores of 4.5, 4.0, and 4.1 out of 5. To improve benchmarking standards, we propose BenchFrame, a unified framework for enhancing benchmark quality. Applying BenchFrame to HumanEval yielded HumanEvalNext, featuring corrected errors, improved language conversion, higher test coverage, and greater difficulty. Evaluating 10 state-of-the-art code models on HumanEval, HumanEvalPlus, and HumanEvalNext revealed average pass-at-1 drops of 31.22% and 19.94%, respectively, underscoring the need for continuous benchmark refinement. We further examine BenchFrame's scalability through an agentic pipeline and confirm its generalizability on the MBPP dataset. All review data, user study materials, and enhanced benchmarks are publicly released.
Paloma Guenes, Rafael Tomaz, Bianca Trinkenreich
et al.
Research shows that more than half of software professionals experience the Impostor Phenomenon (IP), with a notably higher prevalence among women compared to men. IP can lead to mental health consequences, such as depression and burnout, which can significantly impact personal well-being and software professionals' productivity. This study investigates how IP manifests among software professionals across intersections of gender with race/ethnicity, marital status, number of children, age, and professional experience. Additionally, it examines the well-being of software professionals experiencing IP, providing insights into the interplay between these factors. We analyzed data collected through a theory-driven survey (n = 624) that used validated psychometric instruments to measure IP and well-being in software engineering professionals. We explored the prevalence of IP in the intersections of interest. Additionally, we applied bootstrapping to characterize well-being within our field and statistically tested whether professionals of different genders suffering from IP have lower well-being. The results show that IP occurs more frequently in women and that the prevalence is particularly high among black women as well as among single and childless women. Furthermore, regardless of gender, software engineering professionals suffering from IP have significantly lower well-being. Our findings indicate that effective IP mitigation strategies are needed to improve the well-being of software professionals. Mitigating IP would have particularly positive effects on the well-being of women, who are more frequently affected by IP.
Keila Lima, Tosin Daniel Oyetoyan, Rogardt Heldal
et al.
The latest surveys estimate an increasing number of connected Internet-of-Things (IoT) devices (around 16 billion) despite the sector's shortage of manufacturers. All these devices deployed into the wild will collect data to guide decision-making that can be made automatically by other systems, humans, or hybrid approaches. In this work, we conduct an initial investigation of benchmark configuration options for IoT Platforms that process data ingested by such devices in real-time using the MQTT protocol. We identified metrics and related MQTT configurable parameters in the system's component deployment for an MQTT bridge architecture. For this purpose, we benchmark a real-world IoT platform's operational data flow design to monitor the surrounding environment remotely. We consider the MQTT broker solution and the system's real-time ingestion and bridge processing portion of the platform to be the system under test. In the benchmark, we investigate two architectural deployment options for the bridge component to gain insights into the latency and reliability of MQTT bridge deployments in which data is provided in a cross-organizational context. Our results indicate that the number of bridge components, MQTT packet sizes, and the topic name can impact the quality attributes in IoT architectures using MQTT protocol.
The control of marine robots has long relied on model-based methods grounded in classical and modern control theory. However, the nonlinearity and uncertainties inherent in robot dynamics, coupled with the complexity of marine environments, have revealed the limitations of conventional control methods. The rapid evolution of machine learning has opened new avenues for incorporating data-driven intelligence into control strategies, prompting a paradigm shift in the control of marine robots. This paper provides a review of recent progress in marine robot control through the lens of this emerging paradigm. The review covers both individual and cooperative marine robotic systems, highlighting notable achievements in data-driven control of marine robots and summarizing open-source resources that support the development and validation of advanced control methods. Finally, several future perspectives are outlined to guide research toward achieving high-level autonomy for marine robots in real-world applications. This paper aims to serve as a roadmap toward the next-generation control framework of marine robots in the era of data-driven intelligence.
ObjectiveAiming at the problem of the autonomous berthing control of tugboats, this study focuses on the application of a target tracking control strategy based on virtual leadership. MethodsFirst, the autonomous berthing process of the tugboat is transformed into the target tracking control process of the virtual tugboat and actual tugboat. A kinematics model of the berthing system is then designed. Considering special environmental interference in the berthing scenario, the backstepping method and sliding mode control method are used to design an autonomous berthing controller for an azimuth stern drive tugboat. Three different sliding mode surfaces are provided and the stability is verified by the Lyapunov function. Finally, a simulation test is used to verify the control effect through the berthing trajectory, speed error and distance error. ResultsThe simulation results show that the designed tugboat autonomous berthing control strategy and controller have a good effect in the tugboat autonomous berthing scenario and good performance in the face of uncertain disturbances of the system. ConclusionsThe control strategy and berthing controller designed in this paper have good applicability and robustness. The autonomous berthing control of tugboats is realized from a new angle, providing a new direction for subsequent research on the berthing control of tugboats.
Floating photovoltaics (PVs) are progressively constructed in the ocean sea; therefore, the effect that freak waves have on their structural design needs to be considered. This paper developed a dedicated numerical model coupling the floating PV platform and mooring line structures to investigate their dynamic responses under freak waves. A feasible superposition approach is presented to generate freak wave sequences via the combination of transient waves and random waves. A large floating PV platform moored by twenty lines for a water depth of 45 m was designed in detail according to the actually measured ocean environmental and geological conditions. The global time domain analyses of the floating PV mooring structures were implemented to obtain dynamic responses, including PV platform motions and the mooring line configuration and tension under freak waves. A comparison of the response results with those caused by random waves was conducted to illustrate the intuitive evidence of the freak wave effects, which offer a significant reference for the preliminary design of the floating PV platform and mooring line structures.
This study examines the in-situ lateral static load behavior of a closed-diaphragm wall foundation, aiming to better understand its load–displacement response, structural behavior, and soil interaction under horizontal loading. An in-situ static load test was conducted with a maximum applied load of 70 MN, revealing that the diaphragm wall initially exhibits a linear load–displacement response, which becomes increasingly nonlinear as the load increases. The horizontal displacement of the lateral walls is nearly identical to the overall displacement of the diaphragm wall, making it a reliable indicator of the wall’s load state, particularly when it is challenging to measure total displacement. The wall behaves as a rigid body with minimal relative displacement between sections, and overturning failure is identified as the primary failure mode. Earth pressure distribution varies around the wall: passive earth pressure is observed at the front edge, while active and passive pressures alternate at the rear edge. These findings provide valuable insights into the design of diaphragm wall foundations, emphasizing the importance of lateral displacements.
Jialiang Wei, Anne-Lise Courbis, Thomas Lambolais
et al.
Graphical User Interfaces (GUIs) are central to app development projects. App developers may use the GUIs of other apps as a means of requirements refinement and rapid prototyping or as a source of inspiration for designing and improving their own apps. Recent research has thus suggested retrieving relevant GUI designs that match a certain text query from screenshot datasets acquired through crowdsourced or automated exploration of GUIs. However, such text-to-GUI retrieval approaches only leverage the textual information of the GUI elements, neglecting visual information such as icons or background images. In addition, retrieved screenshots are not steered by app developers and lack app features that require particular input data. To overcome these limitations, this paper proposes GUing, a GUI search engine based on a vision-language model called GUIClip, which we trained specifically for the problem of designing app GUIs. For this, we first collected from Google Play app introduction images which display the most representative screenshots and are often captioned (i.e.~labelled) by app vendors. Then, we developed an automated pipeline to classify, crop, and extract the captions from these images. This resulted in a large dataset which we share with this paper: including 303k app screenshots, out of which 135k have captions. We used this dataset to train a novel vision-language model, which is, to the best of our knowledge, the first of its kind for GUI retrieval. We evaluated our approach on various datasets from related work and in a manual experiment. The results demonstrate that our model outperforms previous approaches in text-to-GUI retrieval achieving a Recall@10 of up to 0.69 and a HIT@10 of 0.91. We also explored the performance of GUIClip for other GUI tasks including GUI classification and sketch-to-GUI retrieval with encouraging results.
For promoting the development of the marine economy more sustainably, based on the data envelopment analysis method and combined with the impact of the marine environment, the environmental performance of the marine economy was evaluated for Chinese coastal provinces. Firstly, the classical CCR model was used. Then, a model that considered undesirable outputs was developed to suit the Chinese marine economy. Using the two models, the economic efficiencies without environmental consideration and the environmental performance index were calculated and compared. According to the results, the empirical relationship between EPI and EE, per capita GDP, and the industrial structure was analyzed. It is useful for guiding the coastal local economy of China to a healthy way.
Software engineering (SE) is full of abstract concepts that are crucial for both researchers and practitioners, such as programming experience, team productivity, code comprehension, and system security. Secondary studies aimed at summarizing research on the influences and consequences of such concepts would therefore be of great value. However, the inability to measure abstract concepts directly poses a challenge for secondary studies: primary studies in SE can operationalize such concepts in many ways. Standardized measurement instruments are rarely available, and even if they are, many researchers do not use them or do not even provide a definition for the studied concept. SE researchers conducting secondary studies therefore have to decide a) which primary studies intended to measure the same construct, and b) how to compare and aggregate vastly different measurements for the same construct. In this experience report, we discuss the challenge of study selection in SE secondary research on latent variables. We report on two instances where we found it particularly challenging to decide which primary studies should be included for comparison and synthesis, so as not to end up comparing apples with oranges. Our report aims to spark a conversation about developing strategies to address this issue systematically and pave the way for more efficient and rigorous secondary studies in software engineering.