ABSTRACT We study a rental firm's optimal inventory and rental allocation problem considering random inventory loss due to usage. Each product has two conditions: good and bad, both can satisfy demand. After each rental, good products have a depreciation rate to become bad, and bad products have a depreciation rate to become useless. The firm chooses its inventory before the rental season starts and decides how to allocate its good and bad products to satisfy demand in each period during the rental season. If the total inventory of the good and bad product is no greater than the demand, the firm rents out all inventory. Otherwise, the optimal rental quantities are governed by two thresholds that depend on the weighted sum of inventory of the good and bad products adjusted by the demand. Based on the two thresholds, the firm's optimal rental decision can be classified into three cases: rent the bad product first, good product first, or a mix of both products. We also analyze two priority allocation policies: Good‐First (GF) and Bad‐First (BF), and the cost difference between them and the optimal policy. When the total inventory is moderate, we propose a modified Bad‐First (MBF) policy that only optimizes the rental allocation in the last two periods and uses the BF policy for the remaining periods. Such policy performs well and significantly reduces computation complexity. Our numerical study shows that the usage‐based loss rates can have a non‐monotone impact on the initial inventories and significantly increase the firm's cost.
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.
In recent years, most maritime accidents have been caused by deficiencies in navigators’ situational awareness. Previous studies have evaluated the navigators' situation awareness (SA) through the application of the Situation Awareness Global Assessment Technique (SAGAT) in ship maneuvering simulations. Researchers have developed collision avoidance support systems and collision risk assessment models to mitigate maritime accidents. However, existing models often apply conventional weight parameters for collision risk factors, which may not be appropriate for navigators with different experience levels. To refine these weight parameter sets tailored to each navigator level, based on each navigator's significant SA, derived from experimental navigators' situation awareness measurement. In addition, grid search-based weight aggregation was employed to systematically refine the weight distributions, optimize the impact of collision risk factors, and ensure improved model accuracy. The results demonstrate that the proposed weight parameters improve the detection rate of significant targets according to navigator’s experience level in congested waters.
Precise underwater object detectors can provide Autonomous Underwater Vehicles (AUVs) with good situational awareness in underwater environments, supporting a wide range of unmanned exploration missions. However, the quality of optical imaging is often insufficient to support high detector accuracy due to poor lighting and the complexity of underwater environments. Therefore, this paper develops an efficient and precise object detector that maintains high recognition accuracy on degraded underwater images. We design a Cross Spatial Global Perceptual Attention (CSGPA) mechanism to achieve accurate recognition of target and background information. We then construct an Efficient Multi-Scale Weighting Feature Pyramid Network (EMWFPN) to eliminate computational redundancy and increase the model’s feature-representation ability. The proposed Occlusion-Robust Wavelet Network (ORWNet) enables the model to handle fine-grained frequency-domain information, enhancing robustness to occluded objects. Finally, EMASlideloss is introduced to alleviate sample-distribution imbalance in underwater datasets. Our architecture achieves 81.8% and 83.8% mAP on the DUO and UW6C datasets, respectively, with only 7.2 GFLOPs, outperforming baseline models and balancing detection precision with computational efficiency.
Melissa Costan, Kasim Costan, Anna Weißbach
et al.
The gap between theory and practice is well-documented in educational research. Physics teachers' willingness to apply research findings in practice may be influenced by a sceptical attitude towards science education research. This study explores physics teachers' perspectives on science education research, with a particular focus on potential scepticism towards the discipline. A two-step mixed-methods approach was employed: (1) Interviews with a purposeful sample of 13 experienced physics teachers for a first exploration of attitudes towards physics education research, and (2) a quantitative survey of 174 physics teachers to examine, among other aspects, the previously observed attitudes in a larger sample and to identify teacher profiles using latent profile analysis. The interview study revealed both sceptical and non-sceptical attitudes towards physics education research, including some that fundamentally questioned its practical value. Based on the survey data and latent profile analysis, four distinct teacher profiles differing in their level of scepticism towards science education research were identified. While one profile is highly sceptical, the other three exhibit a mix of sceptical and supportive attitudes. Thus, physics teachers are not generally sceptical. However, the cooperation between research and practice is perceived as unproductive by most teachers.
Elizabeth Bradley, Adilson E. Motter, Louis M. Pecora
Nonlinear science has evolved significantly over the 35 years since the launch of the journal Chaos. This Focus Issue, dedicated to the 80th Birthday of its founding editor-in-chief, David K. Campbell, brings together a selection of contributions on influential topics, many of which were advanced by Campbell's own research program and leadership role. The topics include new phenomena and method development in the realms of network dynamics, machine learning, quantum and material systems, chaos and fractals, localized states, and living systems, with a good balance of literature review, original contributions, and perspectives for future research.
The PRobe far-Infrared Mission for Astrophysics (PRIMA) mission concept is a proposed mission to NASA's Astrophysics Probe Explorer (APEX) call. The concept features a cryogenically cooled 1.8 m diameter telescope, and is designed to carry two science instruments covering the 24 to 264 $μ$m wavelength range: an imaging polarimeter (PRIMAger) and a spectrometer (FIRESS). The majority of PRIMA's time (75%) will be open to observations proposed by the community (General Observer science / GO), and all of data will be publicly available for archival research (Guest Investigator science / GI). Following up on the successful community engagement created by the first volume of the GO PRIMA Science Book (arXiv:2310.20572), Volume 2 gathers 120 new and updated contributed science cases which could be performed within the context of the PRIMA GO/GI program. This volume reflects the strong development of the community interest, awareness and involvement in PRIMA, and further develops how PRIMA's unprecedented capabilities can be leveraged for an impactful and innovative GO/GI program covering most areas of astrophysics and over 90% of the scientific questions and discovery areas in the Astro2020 decadal survey.
Dylan K Wainwright, George V Lauder, Bradford J Gemmell
Synopsis The scales and skin mucus of bony fishes are both proposed to have a role in beneficially modifying the hydrodynamics of water flow over the body surface. However, it has been challenging to provide direct experimental evidence that tests how mucus and fish scales change the boundary layer in part due to the difficulties in working with live animal tissue and difficulty directly imaging the boundary layer. In this manuscript, we use direct imaging and flow tracking within the boundary layer to compare boundary layer dynamics over surfaces of fish skin with mucus, without mucus, and a flat control surface. Our direct measurements of boundary layer flows for these three different conditions are repeated for two different species, bluegill sunfish (Lepomis macrochirus) and blue tilapia (Oreochromis aureus). Our goals are to understand if mucus and scales reduce drag, shed light on mechanisms underlying drag reduction, compare these results between species, and evaluate the relative contributions to hydrodynamic function for both mucus and scales. We use our measurements of boundary layer flow to calculate shear stress (proportional to friction drag), and we find that mucus reduces drag overall by reducing the velocity gradient near the skin surface. Both bluegill and tilapia showed similar patterns of surface velocity reduction. We also note that scales alone do not appear to reduce drag, but that mucus may reduce friction drag up to 50% compared to scaled surfaces without mucus or flat controls.
Influenced by the clearance flow between stator and rotor, the operational performance and hydraulic performance of full cross-flow pump units are often worse than that of semi-cross-flow pumps. In order to explore the influence mechanism of clearance structural parameters on clearance flow and provide a reliable scientific support for the improvement of both external and internal characteristics of full cross-flow pump units, firstly, the optimization of the stator–rotor clearance structure was studied as research entry point and the radial inlet and outlet clearance width were taken to set up design variables. Secondly, to establish a comprehensive optimization objective function considering both the operational performance and the hydraulic performance of the pump, the information weight method was adopted by weighting four evaluation indexes, namely, head coefficient, efficiency coefficient, vortex average radial deflection coefficient and axial velocity uniformity coefficient, which were calculated by numerical simulation. Finally, the relevant optimization design analysis was carried out by establishing the response surface model, with the optimal objective value obtained by conducting the steepest-descent method. The results show that the response of the radial inlet and outlet clearance width coefficient between stator and rotor to the comprehensive objective function is not directly coupled and the influence of the radial inlet clearance width coefficient on the objective function is higher than that of the radial outlet clearance width coefficient. The parameter optimization outcomes are as follows: the width coefficient of radial inlet clearance between stator and rotor is 2.2 and that of radial outlet clearance is 3.6, in which case the disturbance effect of clearance flow on the mainstream flow pattern in the pump can be significantly reduced, with the export cyclic quantity of the guide vane obviously decreased and the outlet flow pattern of the pump unit greatly improved. Verified by the model test, the average lift of the pump unit was increased by about 7.6% and the maximum promotion of the unit efficiency reached 5.2%.
This paper presents the application of strategic ship fleet planning for the maritime transportation of crude palm oil. This study aims to determine the optimal number of chemical tankers required, their capacity (in deadweight tonnage), and the appropriate timing for chartering, buying, or selling vessels within the fleet. To achieve this, mixed integer linear programing is utilized as the optimization framework for strategic ship fleet planning. To ensure a more authentic approach, the investigation utilized a case study focused on the export of Indonesian crude palm oil. The research findings indicate that several export routes cannot be serviced due to higher transportation costs, which could potentially be anticipated through an increase in freight rates. In addition, decisions regarding the quantity and categories of fleets required for each transportation route were also made. The importance of this study is highlighted by its capacity to offer valuable insights to exporters, shipping companies, and the government regarding tanker fleet deployment, management, and regulatory considerations. Furthermore, these findings provide a clearer understanding of the necessity of a tanker fleet for transporting crude palm oil. This supports the Indonesian government's 'beyond cabotage' policy, which mandates the use of vessels operated by national shipping companies for crude palm oil exports, making it a relevant case study for examining the effectiveness of such measures.
Multiwave interference plays a crucial role in shaping the spatial variations of internal tides. Based on a combination of in situ mooring and altimeter data, interference of semidiurnal internal tides was investigated in the northern South China Sea. Mooring observations indicate the observed kinetic-to-potential energy ratio and group speed are both relatively lower than the theoretical values of mode-1 semidiurnal internal tides, indicating the presence of partly-standing waves. This is consistent with the altimeter result that the mooring was located at the antinode within the interference pattern formed by the superposition of the westward and southward semidiurnal internal tides from the Luzon Strait and the continental slope of the southern Taiwan Strait. However, the kinetic-to-potential energy ratio and group velocity were notably changed when an anticyclonic eddy passed by the mooring. By employing the ray-tracing method, we identified that mesoscale processes may induce a phase difference in the semidiurnal internal tides between the Luzon Strait and the continental slope of the southern Taiwan Strait. This alteration further leads to changes in the positions of nodes and antinodes within the interference pattern of the semidiurnal internal tides.
Mislav Maljković, Ivica Pavić, Toni Meštrović
et al.
The maneuverability of ships is influenced by several factors, including ship design, size, propulsion system, hull shape, and external conditions such as wind, waves, and currents. The size, shape, and arrangement of the hull, rudder, and propeller are decisive for maneuverability. Hydrodynamic forces such as bank effect and squat significantly impact the maneuverability of large ships in narrow channels. With the increasing trend of building ever-larger ships, the demand to evaluate the maneuvering performance of the ship at the design stage has become more critical than ever. Both experimental and computational methods are used to obtain accurate maneuvering characteristics of vessels. In this study, the methods for predicting ship maneuvering characteristics are analyzed using a systematic review based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA). This article contributes to a deeper understanding of the hydrodynamic capabilities of ships and identifies possible future challenges in the field of ship hydrodynamics. The findings inform educators and the shipping industry about the importance of predicting the maneuvering performance of ships, with an emphasis on the education and training of seafarers needed to make timely decisions in critical situations.
Pedro Ortiz, Eleanor Casas, Marko Orescanin
et al.
Abstract Space-borne passive microwave (PMW) data provide rich information on atmospheric state, including cloud structure and underlying surface properties. However, PMW data are sparse and limited due to low Earth orbit collection, resulting in coarse Earth system sampling. This study demonstrates that Bayesian deep learning (BDL) is a promising technique for predicting synthetic microwave (MW) data and its uncertainties from more ubiquitously available geostationary infrared observations. Our BDL models decompose predicted uncertainty into aleatoric (irreducible) and epistemic (reducible) components, providing insights into uncertainty origin and guiding model improvement. Low and high aleatoric uncertainty values are characteristic of clear sky and cloudy regions, respectively, suggesting that expanding the input feature vector to allow richer information content could improve model performance. The initially high average epistemic uncertainty metrics quantified by most models indicate that the training process would benefit from a greater data volume, leading to improved performance at most studied MW frequencies. Using quantified epistemic uncertainty to select the most useful additional training data (a training dataset size increase of 3.6%), the study reduced the mean absolute error and root mean squared error by 1.74% and 1.38%, respectively. The broader impact of this study is the demonstration of how predicted epistemic uncertainty can be used to select targeted training data. This allows for the curation of smaller, more optimized training datasets and also allows for future active learning studies.
David G. Matthews, Meghan F. Maciejewski, Greta A. Wong
et al.
ABSTRACT The vertebrate immune system provides an impressively effective defense against parasites and pathogens. However, these benefits must be balanced against a range of costly side-effects including energy loss and risks of auto-immunity. These costs might include biomechanical impairment of movement, but little is known about the intersection between immunity and biomechanics. Here, we show that a fibrosis immune response to Schistocephalus solidus infection in freshwater threespine stickleback (Gasterosteus aculeatus) has collateral effects on their locomotion. Although fibrosis is effective at reducing infection, some populations of stickleback actively suppress this immune response, possibly because the costs of fibrosis outweigh the benefits. We quantified the locomotor effects of the fibrosis immune response in the absence of parasites to investigate whether there are incidental costs of fibrosis that could help explain why some fish forego this effective defense. To do this, we induced fibrosis in stickleback and then tested their C-start escape performance. Additionally, we measured the severity of fibrosis, body stiffness and body curvature during the escape response. We were able to estimate performance costs of fibrosis by including these variables as intermediates in a structural equation model. This model revealed that among control fish without fibrosis, there is a performance cost associated with increased body stiffness. However, fish with fibrosis did not experience this cost but rather displayed increased performance with higher fibrosis severity. This result demonstrates that the adaptive landscape of immune responses can be complex with the potential for wide-reaching and unexpected fitness consequences.
The leakage of the ship’s pipeline system will bring great risks to the engine equipment and seriously threaten the vitality of the ship. In this paper, the pipeline leakage detection and localization research are carried out based on the vibration signal generated by pipeline leakage. First, the finite element model of the pipeline is constructed to obtain the variation law of the vibration signal when the pipeline leaks are carried out. Second, the vibration signal is processed based on the variational mode decomposition (VMD) and radial basis function (RBF) neural networks. The wavelet packet threshold noise reduction is conducted before signal decomposition to improve the signal-to-noise ratio. Then, the denoised signal is decomposed by VMD. The effective component is identified by analyzing the correlation coefficient between the component and the denoised signal. The center frequency and energy of the effective component are used as feature vector to train the RBF neural network to identify and locate leakage. Finally, a pipeline leakage test platform is built under laboratory conditions. After processing the data samples collected from the test, the RBF neural network is trained to identify and locate leaks. The test sample identification results show that the leak identification and localization method based on VMD-RBF has a high accuracy.
Thomas Mion, Michael J. D’Agati, Sydney Sofronici
et al.
Magnetoelectric (ME)-based magnetometers have garnered much attention as they boast ultra-low-power systems with a small form factor and limit of detection in the tens of picotesla. The highly sensitive and low-power electric readout from the ME sensor makes them attractive for near DC and low-frequency AC magnetic fields as platforms for continuous magnetic signature monitoring. Among multiple configurations of the current ME magnetic sensors, most rely on exploiting the mechanically resonant characteristics of a released ME microelectromechanical system (MEMS) in a heterostructure device. Through optimizing the resonant device configuration, we design and fabricate a fixed–fixed resonant beam structure with high isolation compared to previous designs operating at ~800 nW of power comprised of piezoelectric aluminum nitride (AlN) and magnetostrictive (Co<sub>1-x</sub>Fe<sub>x</sub>)-based thin films that are less susceptible to vibration while providing similar characteristics to ME-MEMS cantilever devices. In this new design of double-clamped magnetoelectric MEMS resonators, we have also utilized thin films of a new iron–cobalt–hafnium alloy (Fe<sub>0.5</sub>Co<sub>0.5</sub>)<sub>0.92</sub>Hf<sub>0.08</sub> that provides a low-stress, high magnetostrictive material with an amorphous crystalline structure and ultra-low magnetocrystalline anisotropy. Together, the improvements of this sensor design yield a magnetic field sensitivity of 125 Hz/mT when released in a compressive state. The overall detection limit of these sensors using an electric field drive and readout are presented, and noise sources are discussed. Based on these results, design parameters for future ME MEMS field sensors are discussed.
Rip currents are fast offshore currents generated during the breaking process of waves propagating nearshore, posing a potential life safety threat to coastal bathers. This study utilizes a Boussinesq phase-resolving model to investigate the formation mechanism of rip currents at Dadonghai Beach, based on its actual topography, and explores the characteristics of rip current formation under various wave conditions, with an emphasis on analyzing vortices, the mean water level and the spatial distribution of average velocity. The results indicate that rip current formation is significantly influenced by wave height and period. The increase in wave height and period results in more intense rip currents and higher water level fluctuations on arc-shaped beaches and on both sides of the bay, leading to complex vortex distributions. An increase in the angle of wave incidence hinders rip current formation in arc-shaped beach areas but is favorable to the generation of deflection rips on both sides of the bay. Furthermore, an increase in bottom friction inhibits rip current formation. When the water depth decreases in the channels, rip currents transition into longshore currents. The findings of this research offer valuable scientific insights into the formation mechanisms of rip currents and contribute to their prediction and prevention.
In order to ensure the high availability and high success of torpedoes in war, it is urgent to carry out research on the division and life assessment of life-limited parts in maintenance support. In view of torpedoes suitable for multiple platforms, based on the reliability-centered maintenance(RCM) theory, the environmental stress of torpedoes at different stages was analyzed. The determination principle and selection principle of life characterization parameters of life-limited parts of torpedoes were proposed. On this basis, the life characteristic functions under different distributions were studied in detail. At the same time, the assessment method of life-limited parts was proposed according to different life data of torpedoes, and a practical application case was given, which provided technical support for the subsequent formulation of scientific and reasonable maintenance support schemes for torpedoes.
The quest to find extraterrestrial life is a critical scientific endeavor with civilization-level implications. Icy moons in our solar system are promising targets for exploration because their liquid oceans make them potential habitats for microscopic life. However, the lack of a precise definition of life poses a fundamental challenge to formulating detection strategies. To increase the chances of unambiguous detection, a suite of complementary instruments must sample multiple independent biosignatures (e.g., composition, motility/behavior, and visible structure). Such an instrument suite could generate 10,000x more raw data than is possible to transmit from distant ocean worlds like Enceladus or Europa. To address this bandwidth limitation, Onboard Science Instrument Autonomy (OSIA) is an emerging discipline of flight systems capable of evaluating, summarizing, and prioritizing observational instrument data to maximize science return. We describe two OSIA implementations developed as part of the Ocean Worlds Life Surveyor (OWLS) prototype instrument suite at the Jet Propulsion Laboratory. The first identifies life-like motion in digital holographic microscopy videos, and the second identifies cellular structure and composition via innate and dye-induced fluorescence. Flight-like requirements and computational constraints were used to lower barriers to infusion, similar to those available on the Mars helicopter, "Ingenuity." We evaluated the OSIA's performance using simulated and laboratory data and conducted a live field test at the hypersaline Mono Lake planetary analog site. Our study demonstrates the potential of OSIA for enabling biosignature detection and provides insights and lessons learned for future mission concepts aimed at exploring the outer solar system.