This 90-day trial evaluated the integrated benefits of biofloc technology (BFT) in lined ponds for intensive <i>Penaeus vannamei</i> culture, comparing it with a conventional water-exchange (WE) system. The BFT system maintained favorable water quality with a 68.4% reduction in cumulative water exchange. Concentrations of toxic total ammonia–nitrogen (TAN) and nitrite–nitrogen (NO<sub>2</sub><sup>−</sup>-N) were better controlled, and total suspended solids (TSS) stabilized within a beneficial range (150–200 mg L<sup>−1</sup>). Microbial analysis indicated that BFT significantly increased total bacterial abundance in both culture water and shrimp hepatopancreas while reducing the total <i>Vibrio</i>-to-bacteria ratio in culture water to below 6%, significantly lower than in the WE system (>18%). Moreover, BFT significantly lowered the loads of specific pathogens, acute hepatopancreatic necrosis disease (AHPND)-causing <i>Vibrio parahaemolyticus</i>, and <i>Enterocytozoon hepatopenaei</i> (EHP) in both culture water and shrimp hepatopancreas. Regarding production performance, BFT significantly enhanced shrimp survival rate (82.4% vs. 71.5%), yield (3460 vs. 2948 kg pond<sup>−1</sup>), and water productivity (0.85 vs. 0.28 kg m<sup>−3</sup>), while lowering the feed conversion ratio (1.16 vs. 1.33). In conclusion, BFT achieves stable water quality, effective pathogen suppression, and enhanced production efficiency through microbial regulation, offering a viable water-saving, environmentally sound, and disease-resilient strategy for intensive <i>P. vannamei</i> culture.
Rotated object detection plays a vital role in remote sensing interpretation, with broad applications in urban planning, port monitoring, and disaster response. However, the significant scale variations, complex orientations, and cluttered backgrounds in remote sensing images pose considerable challenges to accurate detection. To address these issues, this article proposes an efficient rotated object detection framework that integrates state space models with vision transformers to achieve an optimal balance between accuracy and computational efficiency. The proposed framework employs a MobileMamba backbone enhanced with a multireceptive field feature interaction module for effective local–global feature representation. An EfficientViT-FPN neck enables efficient multiscale feature fusion, while a refined Rotated RetinaNet head incorporates five-parameter rotated box regression with angle-aware constraints to improve the orientation estimation. Comprehensive experiments on the DOTA-v1.0 and SRSDD-v1.0 datasets demonstrate that our approach achieves superior detection accuracy with significantly reduced computational overhead, making it particularly suitable for practical remote sensing applications.
The integration of advanced wave scattering physics into operational forecast systems like WAVEWATCH III is often hindered by the computational complexity of high-fidelity models. While the diffusion approximation framework of Zhao and Shen (2016) offers a promising alternative to the full Boltzmann equation, its requirement to solve for multiple coupled auxiliary variables (e.g., transmitted and scattered components) presents a significant barrier to practical implementation. To overcome this challenge, this study proposes a novel algorithmic simplification that enhances the model's computational efficiency and tractability. Our key innovation is the introduction of an effective mean action density variable, Neff, formed by combining the transmitted energy and the isotropically redistributed scattered energy. This unification reduces the system's dimensionality, eliminating one prognostic equation and streamlining numerical integration. Validation against benchmark solutions demonstrates that the proposed model accurately captures the directional spreading of wave energy while offering a more computationally efficient pathway. By providing a streamlined and operationally viable framework, this work bridges a critical gap between theoretically rigorous scattering models and the demands of large-scale forecasting.
Planets in the liquid-water habitable zone of low-mass stars experience large tidal forces, $10^3$ to $10^4$ times those on Earth, due to the small distance between the habitable zone and the host stars. Therefore, interior solid tides, ocean tides and atmospheric tides on these planets could be much stronger than that on Earth, but rare work has been done to explicitly simulate the ocean tides. Here, for the first time, we perform global ocean tide simulations and show that ocean tides on asynchronously rotating planets with large eccentricities can reach $\mathcal{O}(1000)\,\mathrm{m}$ in height and $\mathcal{O}(10)\,\mathrm{m\,s^{-1}}$ in flow speed. Interactions between tide and bottom topography can induce large energy dissipation, $\sim\mathcal{O}(100)\,\mathrm{W\,m^{-2}}$ in global mean. This tidal energy dissipation can strongly accelerate orbital evolution by 1-2 orders of magnitude. However, for planets with small eccentricities, the ocean tides are much weaker but still comparable to that on modern Earth. Our results suggest that ocean tides on eccentric planets orbiting low-mass stars are orders of magnitude more powerful than those on Earth and can dramatically influence surface geography and orbital evolution.
We present a differentiable extension of the VEROS ocean model, enabling automatic differentiation through its dynamical core. We describe the key modifications required to make the model fully compatible with JAX autodifferentiation framework and evaluate the numerical consistency of the resulting implementation. Two illustrative applications are then demonstrated: (i) the correction of an initial ocean state through gradient-based optimization, and (ii) the calibration of unknown physical parameters directly from model observations. These examples highlight how differentiable programming can facilitate end-to-end learning and parameter tuning in ocean modeling. Our implementation is available online.
Pramudya Imawan Santosa, W.B. Wan Nik, Atria Pradityana
et al.
Currently, the increasing demand for environmentally friendly corrosion inhibitors. Sustainable organic inhibitor innovations can be an alternative in the industrial world that still uses hazardous chemical inhibitors. Carbon Steel is a material that is often used in the oil and gas industry. This type of steel is resistant to significant corrosion, so an effective solution is needed to minimise material degradation. This study investigates the potential of sunflower (Helianthus annus) seed shell extract, SSSE. as a sustainable, environmentally friendly corrosion inhibitor for steel in concentrated hydrochloric acid (1 M HCl), where these conditions are representative of an industrially hazardous environment. Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarisation (PDP) methods were used in this study. With these two approaches, SSSE showed a high inhibition efficiency of 99.56 % at a concentration of 400 ppm, effectively reducing both anodic and cathodic corrosion reactions. Scanning electron microscopy (SEM) showed the formed protective layer on the steel surface, significantly reducing corrosion. These findings highlight SSSE as a feasible and environmentally friendly alternative to conventional inhibitors, showing great potential applications in various acidic environments.
Azadeh Kazemi, Giuseppe T. Cirella, Amir Hedayatiaghmashhadi
et al.
This research investigates the complex interplay between urban heat island (UHI) and urban pollution island in the context of rapid urbanization. Using remote-sensed land surface temperature (LST), the UHI is categorized into five intensity levels. Air pollution monitoring in Arak city, including green spaces, roads, and industrial areas, combines in situ and remote sensing observations for a comprehensive 2019–2020 seasonal analysis. Findings reveal distinct surface UHI patterns, peaking in spring near highly industrialized areas with low greenery and high nitrogen compounds. A significant correlation between LST and pollutant levels is observed in summer in areas with both roads and industrial facilities. Industrial zones consistently exhibit higher LST intensity than green spaces throughout the year. Fall and winter analyses show unique pollution patterns, with sulfur dioxide concentrations peaking near roads in fall due to traffic congestion, and higher nitric oxide and nitrogen dioxide levels in areas with limited green spaces. These observations underscore the intricate relationship between surface UHI and pollutant concentrations, highlighting the multifaceted nature of urban environmental dynamics across diverse seasons and land-use categories.
Yingjun Zhang, Brian B. Barnes, Dennis J. McGillicuddy Jr.
et al.
Abstract Pelagic Sargassum has increased dramatically in the past decade, primarily in the annually recurrent Great Atlantic Sargassum Belt (GASB) that extends from the coast of West Africa to the Gulf of Mexico. Using satellite observations of Sargassum density and mesoscale eddies from 2011 to 2023, we investigate whether more Sargassum can be found in mesoscale eddies. Cyclonic eddies were found to contain 6%–47% more Sargassum (relative to eddy‐free waters) across all selected regions within the GASB, with the highest Sargassum density in their inner cores (<0.5 eddy radius). Impacts of anticyclonic eddies were weaker and varied between regions. In addition, Sargassum enrichment tended to be higher in eddies with greater size or amplitude, such as the North Brazil Current rings and those in the Caribbean Sea. These findings may inform Sargassum mitigation strategies, for example, through physical removal in targeted locations.
Tim Benedikt von See, Jens Greinert, Jens Greinert
et al.
Sediment plumes created by dredging or mining activities have an impact on the ecosystem in a much larger area than the mining or dredging area itself. It is therefore important and sometimes mandatory to monitor the developing plume to quantify the impact on the ecosystem including its spatial-temporal evolution. To this end, a Bayesian Optimization (BO)-based approach is proposed for plume monitoring using autonomous underwater vehicles (AUVs), which are used as a sensor network. Their paths are updated based on the BO, and additionally, a split-path method and the traveling salesman problem are utilized to account for the distances the AUVs have to travel and to increase the efficiency. To address the time variance of the plume, a sliding-window approach is used in the BO and the dynamics of the plume are modeled by a drift and decay rate of the suspended particulate matter (SPM) concentration measurements. Simulation results with SPM data from a simulation of a dredge experiment in the Pacific Ocean show that the method is able to monitor the plume over space and time with good overall estimation error.
Science, General. Including nature conservation, geographical distribution
Ocean salinity is known to dramatically affect the climates of Earth-like planets orbiting Sun-like stars, with high salinity leading to less ice and higher surface temperature. However, how ocean composition impacts climate under different conditions, such as around different types of stars or at different positions within the habitable zone, has not been investigated. We used ROCKE-3D, an ocean-atmosphere general circulation model, to simulate how planetary climate responds to ocean salinities for planets with G-star vs. M-dwarf hosts at several stellar fluxes. We find that increasing ocean salinity from 20 to 100 g/kg in our model results in non-linear ice reduction and warming on G-star planets, sometimes causing abrupt transitions to different climate states. Conversely, sea ice on M-dwarf planets responds more gradually and linearly to increasing salinity. Moreover, reductions in sea ice on M-dwarf planets are not accompanied by significant surface warming as on G-star planets. High salinity can modestly bolster the resilience of M-dwarf planets against snowball glaciation and allow these planets to retain surface liquid water further from their host star, but the effects are muted compared to G-star planets that experience snowball bifurcation and climate hysteresis due to the ice-albedo feedback.
Earth's geodynamo has operated for over 3.5 billion years. The magnetic field is currently powered by thermocompositional convection in the outer core, which involves the release of light elements and latent heat as the inner core solidifies. However, since the inner core nucleated no more than 1.5 billion years ago, the early dynamo could not rely on these buoyancy sources. Given recent estimates of the thermal conductivity of the outer core, an alternative mechanism may be required to sustain the geodynamo prior to nucleation of the inner core. One possibility is a silicate dynamo operating in a long-lived basal magma ocean. Here, we investigate the structural, thermal, buoyancy, and magnetic evolution of an Earth-like terrestrial planet. Using modern equations of state and melting curves, we include a time-dependent parameterization of the compositional evolution of an iron-rich basal magma ocean. We combine an internal structure integration of the planet with energy budgets in a coupled core, basal magma ocean, and mantle system. We determine the thermocompositional convective stability of the core and the basal magma ocean, and assess their respective dynamo activity using entropy budgets and magnetic Reynolds numbers. Our conservative nominal model predicts a transient basal magma ocean dynamo followed by a core dynamo after 1 billion years. The model is sensitive to several parameters, including the initial temperature of the core-mantle boundary, the parameterization of mantle convection, the composition of the basal magma ocean, the radiogenic content of the planet, as well as convective velocity and magnetic scaling laws. We use the nominal model to constrain the range of basal magma ocean electrical conductivity and core thermal conductivity that sustain a dynamo.
Traditional requirements engineering tools do not readily access the SysML-defined system architecture model, often resulting in ad-hoc duplication of model elements that lacks the connectivity and expressive detail possible in a SysML-defined model. Further integration of requirements engineering activities with MBSE contributes to the Authoritative Source of Truth while facilitating deep access to system architecture model elements for V&V activities. We explore the application of MBSE to requirements engineering by extending the Model-Based Structured Requirement SysML Profile to comply with the INCOSE Guide to Writing Requirements while conforming to the ISO/IEC/IEEE 29148 standard requirement statement patterns. Rules, Characteristics, and Attributes were defined in SysML according to the Guide to facilitate requirements definition, verification & validation. The resulting SysML Profile was applied in two system architecture models at NASA Jet Propulsion Laboratory, allowing us to assess its applicability and value in real-world project environments. Initial results indicate that INCOSE-derived Model-Based Structured Requirements may rapidly improve requirement expression quality while complementing the NASA Systems Engineering Handbook checklist and guidance, but typical requirement management activities still have challenges related to automation and support in the system architecture modeling software.
Semi-structured explanation depicts the implicit process of a reasoner with an explicit representation. This explanation highlights how available information in a specific query is utilised and supplemented with information a reasoner produces from its internal weights towards generating an answer. Despite the recent improvements in generative capabilities of language models, producing structured explanations to verify a model's true reasoning capabilities remains a challenge. This issue is particularly pronounced for not-so-large LMs (e.g., FLAN-T5-XXL). In this work, we first underscore the limitations of supervised fine-tuning (SFT) in tackling this challenge, and then introduce a carefully crafted reward engineering method in reinforcement learning (RL) to better address this problem. We investigate multiple reward aggregation methods and provide a detailed discussion which sheds light on the promising potential of RL for future research. Our proposed method on two semi-structured explanation generation benchmarks (ExplaGraph and COPA-SSE) achieves new state-of-the-art results.
Matthew Tyler, Hengyun Zhou, Leigh S. Martin
et al.
We introduce a framework for designing Hamiltonian engineering pulse sequences that systematically accounts for the effects of higher-order contributions to the Floquet-Magnus expansion. Our techniques result in simple, intuitive decoupling rules, despite the higher-order contributions naively involving complicated, non-local-in-time commutators. We illustrate how these rules can be used to efficiently design improved Hamiltonian engineering pulse sequences for a wide variety of tasks, such as dynamical decoupling, quantum sensing, and quantum simulation.
Visual analysis is well adopted within the field of oceanography for the analysis of model simulations, detection of different phenomena and events, and tracking of dynamic processes. With increasing data sizes and the availability of multivariate dynamic data, there is a growing need for scalable and extensible tools for visualization and interactive exploration. We describe pyParaOcean, a visualization system that supports several tasks routinely used in the visual analysis of ocean data. The system is available as a plugin to Paraview and is hence able to leverage its distributed computing capabilities and its rich set of generic analysis and visualization functionalities. pyParaOcean provides modules to support different visual analysis tasks specific to ocean data, such as eddy identification and salinity movement tracking. These modules are available as Paraview filters and this seamless integration results in a system that is easy to install and use. A case study on the Bay of Bengal illustrates the utility of the system for the study of ocean phenomena and processes.
Matthew Patterson, Christopher O'Reilly, Jon Robson
et al.
The coupled nature of the ocean-atmosphere system frequently makes understanding the direction of causality difficult in ocean-atmosphere interactions. This study presents a method to decompose turbulent heat fluxes into a component which is directly forced by atmospheric circulation, and a residual which is assumed to be primarily `ocean-forced'. This method is applied to the North Atlantic in a 500-year pre-industrial control run using the Met Office's HadGEM3-GC3.1-MM model. The method identifies residual heat flux modes largely associated with variations in ocean circulation and shows that these force equivalent barotropic circulation anomalies in the atmosphere. The first of these modes is characterised by the ocean warming the atmosphere along the Gulf Stream and North Atlantic Current and the second by a dipole of cooling in the western subtropical North Atantic and warming in the sub-polar North Atlantic. Analysis of atmosphere-only simulations confirms that these heat flux patterns are indeed forcing the atmospheric circulation changes seen in the pre-industrial control run. It is found that the Gulf Stream plays a critical role in the atmospheric circulation response to decadal ocean variability in this model. More generally, the heat flux dynamical decomposition method provides a useful way to establish causality in ocean-atmosphere interactions which could easily be applied to other ocean basins and to either models or reanalysis datasets.
Microdrills are specific cutting tools widely used to drill microholes and microvias. For certain microdrill manufacturers, a conventional sampling inspection procedure is still manually operated for carrying out the destructive and visual measurements of two essential cross-sectional geometric parameters (CSGPs), called the cross-sectional web thickness (CSWT) and the cross-sectional outer diameter (CSOD), of their straight (ST) and undercut (UC) type microdrill products. In order to comprehensively automate the conventional sampling inspection procedure, a destructive and visual measuring system improved from an existing vision-aided automation system, for both the hardware and the automated measuring process (AMP), is presented in this paper. The major improvement of the hardware is characterized by a machine vision module consisting of several conventional machine vision components in combination with an innovative and lower cost optical subset formed by a set of plano-concave achromatic (PCA) lenses and a reflection mirror, so that the essential functions of visually positioning the drilltip and visually measuring the CSGPs can both be achieved via the use of merely one machine vision module. The major improvement of the AMP is characterized by the establishment of specific image processing operations for an auto-focusing (AF) sub-process based on two-dimensional discrete Fourier transform (2D-DFT), for a web thickness measuring (WTM) sub-process based on an iterative least-square (LS) circle-fitting approach, and for an outer diameter measuring (ODM) sub-process based on integrated applications of an iterative LS circle-fitting approach and an LS line-fitting-based group-dividing approach, respectively. Experiments for measuring the CSGPs of microdrill samples were conducted to evaluate the actual effectiveness of the developed system. It showed that the developed system could achieve good repeatability and accuracy for the measurements of the CSWTs and CSODs of both ST and UC type microdrills. Therefore, the developed system could effectively and comprehensively automate the conventional sampling inspection procedure.
ABSTRACT Gastrointestinal microorganisms play a crucial role in host survival and adaptation, but information on host-specific selection or environmental factors that shape the microbiome in natural populations is limited. In this study, we employed 16S rRNA gene amplicon sequencing to investigate the composition and predicted the functions of gut microbiota of two ophiuroid species (Ophiura sarsii and its subspecies O. sarsii vadicola) from cold-water habitats across three geographically distant sea areas in the Northern Pacific Ocean. We also explored the potential influence of the host and environment on the microbiota. The two ophiuroids possessed diverse microbial communities, with Proteobacteria being the most dominant phylum in all four groups. Aliivibrio was the predominant genus in O. sarsii from the Bering Sea, while Candidatus Hepatoplasma was the dominant genus in O. sarsii from the Japan Sea and O. sarsii vadicola from the Yellow Sea. Predicted bacterial functions indicated that most of the pathways with significant differences belonged to metabolism and genetic information processing. Notably, no significant difference was observed between the two coexisting ophiuroid species in the Japan Sea. The high similarity in microbial communities between O. sarsii from the Japan Sea and O. sarsii vadicola from the Yellow Sea may be attributed to their analogous ecological niche. The host and the environment jointly shape the composition of the gut microbial community. The presence of specific microorganisms supports the ecological success of ophiuroids across diverse environments, providing a foundation for host adaptation to cold-water habitats. IMPORTANCE Gastrointestinal microorganisms are critical to the survival and adaptation of hosts, and there are few studies on the differences and functions of gastrointestinal microbes in widely distributed species. This study investigated the gut microbes of two ophiuroid species (Ophiura sarsii and its subspecies O. sarsii vadicola) in cold-water habitats of the Northern Pacific Ocean. The results showed that a combination of host and environmental factors shapes the intestinal microbiota of ophiuroids. There was a high similarity in microbial communities between the two groups living in different regions, which may be related to their similar ecological niches. These microorganisms played a vital role in the ecological success of ophiuroids as the foundation for their adaptation to cold-water environments. This study revealed the complex relationship between hosts and their gut microbes, providing insights into the role they play in the adaptation and survival of marine species.
Analyzing the interactions of free surface waves caused by a submerged-body movement is important as a fundamental study of submerged-body motion. In this study, a two-dimensional mini-towing tank was used to tow an underwater body for analyzing the generation and propagation characteristics of free surface waves. The magnitude of the maximum wave height generated by the underwater body motion increased with the body velocity at shallow submerged depths but did not increase further when the generated wave steepness corresponded to a breaking wave condition. Long-period waves were generated in the forward direction as the body moved initially, and then short-period waves were measured when the body moved at a constant velocity. In numerical simulations based on potential flow, the fluid pressure changes caused by the submerged-body motion were implemented, and the maximum wave height was accurately predicted; however, the complex physical phenomena caused by fluid viscosity and wave breaking in the downstream direction were difficult to implement. This research provides a fundamental understanding of the changes in the free surface caused by a moving underwater body.