For geotechnical structures with a strict control requirement of deformation, the high modulus and non-linear attenuation characteristics of the surrounding soil under small-strain conditions cannot be ignored during performance evaluation; the HSS constitutive model offers significant advantages over conventional approaches (e.g., Mohr–Coulomb) to describe the above soil behaviors. In this study, the theoretical framework of the HSS model, i.e., the yield function, hardening laws, and flow rule, is first elucidated. Subsequently, it is numerically implemented into the finite element software FssiCAS. The reliability of the FssiCAS software (Version 3.5) incorporating the HSS model is validated through a triaxial test and a physical test involving the horizontal loading of the monopile. Finally, taking the four-monopile jacket foundation of an offshore wind turbine (OWT) in Lianjiang County, China, as a representative, the HSS model is adopted to describe the mechanical behaviors of a seabed foundation. The horizontal bearing characteristics of the jacket foundation–seabed system under multi-angle horizontal loading are investigated, and the influence of the horizontal loading angle on the horizontal bearing capacity, jacket displacement, and seabed deformation is quantitatively elucidated. The results indicate that (1) the horizontal bearing capacity of the jacket is minimal when horizontal loading is along the diagonal of the four piles, representing the most severe loading case, and therefore, the horizontal bearing capacity of the jacket foundation–seabed system should be evaluated based on this case; and (2) the FE software FssiCAS has good reliability when dealing with pile–soil interaction problems involving complex geometries and complex mechanical behaviors of seabed soils. This study could provide technical support and an analysis platform for the design of jacket foundations for complex marine structures, such as OWTs.
AbstractProgrammable photonic integrated circuits (PICs) consisting of reconfigurable on-chip optical components have been creating new paradigms in various applications, such as integrated spectroscopy, multi-purpose microwave photonics, and optical information processing. Among many reconfiguration mechanisms, non-volatile chalcogenide phase-change materials (PCMs) exhibit a promising approach to the future very-large-scale programmable PICs, thanks to their zero static power and large optical index modulation, leading to extremely low energy consumption and ultra-compact footprints. However, the scalability of the current PCM-based programmable PICs is still limited since they are not directly off-the-shelf in commercial photonic foundries now. Here, we demonstrate a scalable platform harnessing the mature and reliable 300 mm silicon photonic fab, assisted by an in-house wide-bandgap PCM (Sb2S3) integration process. We show various non-volatile programmable devices, including micro-ring resonators, Mach-Zehnder interferometers and asymmetric directional couplers, with low loss (~0.0044 dB/µm), large phase shift (~0.012 π/µm) and high endurance (>5000 switching events with little performance degradation). Moreover, we showcase this platform’s capability of handling relatively complex structures such as multiple PIN diode heaters in devices, each independently controlling an Sb2S3 segment. By reliably setting the Sb2S3 segments to fully amorphous or crystalline state, we achieved deterministic multilevel operation. An asymmetric directional coupler with two unequal-length Sb2S3 segments showed the capability of four-level switching, beyond cross-and-bar binary states. We further showed unbalanced Mach-Zehnder interferometers with equal-length and unequal-length Sb2S3 segments, exhibiting reversible switching and a maximum of 5 ($$N+1,N=4$$ N + 1 , N = 4 ) and 8 ($${2}^{N},N=3$$ 2 N , N = 3 ) equally spaced operation levels, respectively. This work lays the foundation for future programmable very-large-scale PICs with deterministic programmability.
Our Oceans cover more than 70% of the Earth’s surface, and thus various ocean engineering projects have been undertaken to utilize these vast resources effectively [...]
The increasingly severe issue of marine debris presents a critical threat to the sustainable development of marine ecosystems. Real-time detection is essential for timely intervention and cleanup. Furthermore, the density of marine debris exhibits significant depth-dependent variation, resulting in degraded detection accuracy. Based on 9625 publicly available underwater images spanning various depths, this study proposes UTNet, a lightweight neural model, to improve the effectiveness of real-time intelligent identification of marine debris through multidimensional optimization. Compared to Faster R-CNN, SSD, and YOLOv5/v8/v11/v12, the UTNet model demonstrates enhanced performance in random image detection, achieving maximum improvements of 3.5% in mAP50 and 9.3% in mAP50-95, while maintaining reduced parameter count and low computational complexity. The UTNet model is further evaluated on underwater videos for real-time debris recognition at varying depths to validate its capability. Results show that the UTNet model exhibits a consistently increasing trend in confidence levels across different depths as detection distance decreases, with peak values of 0.901 at the surface and 0.764 at deep-sea levels. In contrast, the other six models display greater performance fluctuations and fail to maintain detection stability, particularly at intermediate and deep depths, with evident false positives and missed detections. In summary, the lightweight UTNet model developed in this study achieves high detection accuracy and computational efficiency, enabling real-time, high-precision detection of marine debris at varying depths and ultimately benefiting mitigation and cleanup efforts.
The evaluation of steady turning performance for dual-tail propulsion underwater gliders typically relies on high-fidelity unsteady CFD simulations, which remain computationally prohibitive for control optimization and multi-scenario analysis. To overcome this limitation, this paper proposes a rapid prediction framework integrating Kriging surrogate modeling with dynamic equilibrium constraints. The proposed method employs a physics-informed decoupling strategy that isolates the hydrodynamic behavior of the hull from the thrust generation of the propellers. Since these are governed by distinct physical mechanisms and operate at different spatial scales, the decoupling strategy enables efficient and targeted steady-state CFD analysis for each component subsystem. Latin Hypercube Sampling (LHS) is used to generate training data for highly accurate Kriging models, which are subsequently coupled with the glider’s balance equations to form a bidirectional solution system. The forward mode predicts turning performance from control inputs, whereas the inverse mode identifies propeller speeds required for desired trajectories. Validation via fully-coupled 6-DOF unsteady CFD simulations confirms that the framework achieves prediction errors below 10% for key turning parameters while improving computational efficiency by over an order of magnitude. The method provides an effective tool for rapid maneuverability evaluation, control system design, and real-time path planning in dual-tail propulsion underwater gliders.
This EPTCS volume contains the post-proceedings of the Twelfth International Workshop on Fixed Points in Computer Science, presenting a selection of the works presented during the workshop that took place in Naples (Italy) on the 19th and 20th of February 2024 as a satellite of the International Conference on Computer Science Logic (CSL 2024).
This experimental study investigates the effectiveness of the Cognitive Conflict-Based Generative Learning Model (GLBCC) in enhancing science literacy among high school physics students. The novelty of this research lies in the innovative integration of cognitive conflict strategies with generative learning principles through a six stage structured framework, specifically designed to address persistent misconceptions in physics education while systematically developing scientific literacy competencies. The research employed pretest-posttest control group design involving 167 Grade XI students from three schools. Students were randomly assigned to experimental groups (n = 83) that received GLBCC instruction and control groups (n = 84) that used the expository learning model. Science literacy was measured using validated instruments assessing scientific knowledge, inquiry processes, and application skills across six key indicators. Statistical analysis using ANOVA with Tukey HSD post-hoc tests revealed significant improvements in science literacy scores for students receiving GLBCC instruction compared to traditional methods (p < 0.001). This study makes a unique contribution to physics education by demonstrating how the deliberate creation of cognitive conflict, combined with authentic real-world physics phenomena, can effectively restructure students conceptual understanding and enhance their scientific thinking capabilities. Factor analysis identified four critical implementation factors: science literacy development components, learning stages and orientation, and objectives, and knowledge construction processes. The findings provide empirical evidence supporting the integration of cognitive conflict strategies with generative learning approaches in physics education, offering practical implications
Background and Objectives: Craniovertebral instability and its surgical management require a thorough knowledge of the anatomy and dynamics of the craniovertebral junction (CVJ). Due to the wide range of mobility and proximity of vital neurovascular structures, these surgeries demand high technical skill and precision. It is very difficult to suggest a single good technique for CVJ stabilization as each procedure has got its own indications and benefits. Novel techniques and gadgets like neuro navigation and robotic arms help surgeons to minimize complications, thereby improving the overall functional outcome. In this study, we are analyzing the retrospective data of CVJ instabilities surgically managed by freehand technique in our institute. Materials and Methods: We did a retrospective analysis of 33 patients operated on for craniocervical junction instability for 7 years from January 1, 2015, to December 31, 2021. We analyzed the clinical and radiological presentations and postoperative outcomes at 3 weeks, 6 months, and after 1 year. The distribution of clinical presentation in terms of neck pain, myelopathy, restricted neck movements, and lower cranial nerve palsy was evaluated and correlated with the demographic parameters. The paired “t”-test was used to correlate the clinical and radiological outcomes after surgery. Results: The paired “t” value of the clinical improvement assessed with the preoperative and postoperative Japanese Orthopedic Association (JOA) myelopathic scores was − 4.376 with P < 0.001, which indicates a significant clinical improvement 6 months after surgery. Among the 33 patients evaluated, only three patients developed a slight reduction in the JOA score after surgery, which was improved within 1 year. All the patients achieved satisfactory trabecular bone formation at the graft site and decorticated joint facets without any clinical or radiological evidence of implant failure. Among the C2 pedicle screws, 3 (7.5%) were having vertebral foraminal impingement, and 2 (5%) were having medial cortical violation and spinal canal impingement. All the patients with radiological evidence of implant malposition were clinically intact and did not show any deterioration of the studied myelopathic score (JOA). Conclusions: As the bony anatomy and the vascular course of the CVJ vary from patient to patient, thorough preoperative planning is mandatory for the surgical management of CVJ instability. In our study, the clinical and radiological improvement after surgical stabilization of craniovertebral instability by freehand technique is comparable with the available data. The overall risk of screw malposition and associated lethal complications may be minimized by adding modern technologies such as neuronavigation, robotic arms, and three-dimensional C-arm in the armamentarium.
This paper presents a localization method for an underwater multitonal source by using a vertically distributed system in deep water. The system is composed of two kinds of nodes. One is a node at large depth, and the other is a node covering most of the water column. The former and latter are utilized to estimate the source range and depth, respectively. Specifically, the proposed method estimates the source range by matching the spatial arrival angle measured by the first kind of node with the replicas calculated by the acoustic model. Based on the estimation value of the source range, the second kind of node is utilized to estimate the source depth by using an incoherent time reversal method. The effectiveness of the proposed method is demonstrated through numerical simulations. The effects of the measurement error and the sound speed profile mismatch on the performance of the proposed method are also analyzed.
Abeer Banerjee, Naval K. Mehta, Shyam S. Prasad
et al.
In this paper, we address the intricate challenge of gaze vector prediction, a pivotal task with applications ranging from human-computer interaction to driver monitoring systems. Our innovative approach is designed for the demanding setting of extremely low-light conditions, leveraging a novel temporal event encoding scheme, and a dedicated neural network architecture. The temporal encoding method seamlessly integrates Dynamic Vision Sensor (DVS) events with grayscale guide frames, generating consecutively encoded images for input into our neural network. This unique solution not only captures diverse gaze responses from participants within the active age group but also introduces a curated dataset tailored for low-light conditions. The encoded temporal frames paired with our network showcase impressive spatial localization and reliable gaze direction in their predictions. Achieving a remarkable 100-pixel accuracy of 100%, our research underscores the potency of our neural network to work with temporally consecutive encoded images for precise gaze vector predictions in challenging low-light videos, contributing to the advancement of gaze prediction technologies.
Child Impact Statements (CIS) are instrumental in helping to foreground the concerns and needs of minor community members who are too young to vote and often unable to advocate for themselves politically. While many politicians and policymakers assert they make decisions in the best interests of children, they often lack the necessary information to meaningfully accomplish this. CISs are akin to Environmental Impact Statements in that both give voice to constituents who are often under-represented in policymaking. This paper highlights an interdisciplinary collaboration between Social Science and Computer Science to create a CIS tool for policymakers and community members in Shelby County, TN. Furthermore, this type of collaboration is fruitful beyond the scope of the CIS tool. Social scientists and computer scientists can leverage their complementary skill sets in data management and data interpretation for the benefit of their communities, advance scientific knowledge, and bridge disciplinary divides within the academy.
In this study, the stochastic nonlinear system-based trajectory tracking control problem of an autonomous underwater vehicle (AUV) is studied. We investigate the time-varying gain adaptive control method to find possible approaches to reduce the excessive computational burden. Enhanced adaptive algorithms are devised by considering the dynamic characteristics of AUV motion. By transforming the original controller design problems into parameter selection problems and subsequently solving them using the functional time-varying observer technical theorem, we can achieve optimal control performance. The control system is shown to constrain system state error due to stochastic disturbances within arbitrarily small domains. A coordinate transformation is proposed for all system states to meet boundedness conditions. We show that the closed-loop stability is confirmed, the system is asymptotically probabilistically stable, and contraction limits given in the stability analysis may be used to certify the convergence of the AUV trajectory errors. A large number of simulation studies using an underwater vehicle model have proved the effectiveness and robustness of the proposed approach. A real-time, time-varying gain constructive control strategy is further developed for the hardware-in-the-loop simulation; the effectiveness of the controller design is confirmed by introducing the controller into the AUV actuator model.
Amid a global effort in reducing the shipping ecologic impact, the study of the particular case of added resistance of high speed vessels cruising in a seaway has been approached by a very limited number of authors. In this study, we provide a comprehensive and systematic assessment of the added resistance of a planing hull in regular waves. The data are analyzed in both the time and frequency domains in order to fully characterize the added resistance and highlight its correlation with hull motions. It is found that peak added resistance modulation occurs for shorter waves with respect to the peak average added resistance, and slenderness is beneficial only in terms of modulation. Nonlinearity of both the average and first harmonic amplitude is also shown. In addition, results of the phase analysis show a correlation between the added resistance phase and average added resistance.
Daniele Arduini, Claudio Calabrese, Jacopo Borghese
et al.
This paper is part of a series of studies aimed at understanding the potential exploitation of the biomass of the polychaete worm <i>Sabella spallanzanii</i> (Gmelin, 1791), which is obtained as a by-product of an innovative Integrated Multi-Trophic Aquaculture (IMTA) system. IMTA systems are designed according to an ecosystem approach with the aim to reduce marine monoculture impact while further increasing production via exploitation of valuable by-products. <i>S. spallanzanii</i> can remove large amounts of suspended matter by filtering large volumes of water per hour and performs well as an extractive organism under IMTA; however, it currently lacks any economic value, thus hindering its sustainable large-scale implementation. However, <i>S. spallazanii</i> has the potential to become competitive as a newcomer in fish bait, as an ornamental organism, and in fish feed markets. Notably, sabella meal has already been successfully tested as an attractant in an innovative fish feed. Here, we refer to the use of sabella meal as the main component (60%) in the formulation of a novel aquarium fish feed. Following the biochemical analysis of farmed sabella meal, the experimental feed was formulated by adding spirulina (25%) and dry garlic (15%) in such proportion as to be isoproteic and isoenergetic to the commercial control feed. After preliminary observations of the palatability of sabella meal for several tropical fish species, the novel experimental feed was tested on ocellaris clownfish, <i>Amphiprion ocellaris</i> (Cuvier, 1830), by evaluating their growth response in a 70-day feeding trial. The fish seemed to enjoy the experimental feed at least as much as the control, and both the control and treatment groups showed no significant differences in weight gain (<i>p</i> = 0.46), specific growth rate (<i>p</i> = 0.76), and feed conversion ratio (<i>p</i> = 0.48), reinforcing the suitability of <i>S. spallanzanii</i> as a viable source of animal proteins to be employed in the fish feed industry in a circular economy perspective.
In recent years, citizen science has become a larger and larger part of the scientific community. Its ability to crowd source data and expertise from thousands of citizen scientists makes it invaluable. Despite the field's growing popularity, the interactions and structure of citizen science projects are still poorly understood and under analyzed. We use the iNaturalist citizen science platform as a case study to analyze the structure of citizen science projects. We frame the data from iNaturalist as a bipartite network and use visualizations as well as established network science techniques to gain insights into the structure and interactions between users in citizen science projects. Finally, we propose a novel unique benchmark for network science research by using the iNaturalist data to create a network which has an unusual structure relative to other common benchmark networks. We demonstrate using a link prediction task that this network can be used to gain novel insights into a variety of network science methods.
O presente artigo aborda a importância da adoção de métodos de solução de controvérsias em matéria tributária, com o intuito de pacificar entendimentos dos Estados Contratantes da Convenção Modelo da OCDE acerca de assuntos tão sensíveis que afetam consideravelmente os investimentos. A partir da análise do art. 25 da Convenção Modelo da OCDE, o qual prevê expressamente a possibilidade da adoção do procedimento amigável e da arbitragem tributária pelos Estados Contratantes nos tratados internacionais sobre bitributação celebrados, conclui-se sobre a necessidade de o Brasil avançar nessa seara. Além da análise aprofundada quanto ao previsto na norma da OCDE, no que tange ao Direito Tributário Internacional é indispensável conhecer a posição estadunidense, através de seu órgão, o IRS, analisando como a arbitragem tributária foi adotada pelos Estados Unidos da América em Convenções sobre Dupla Tributação, em especial a firmada com a Alemanha. Por fim, destaca-se Portugal, cujo modelo de adoção da arbitragem tributária por sua legislação interna é objeto de estudo por diversos tributaristas brasileiros que afirmam ser um modelo a ser seguido pelo Brasil.
Simon Catterall, Roni Harnik, Veronika E. Hubeny
et al.
We summarize current and future applications of quantum information science to theoretical high energy physics. Three main themes are identified and discussed; quantum simulation, quantum sensors and formal aspects of the connection between quantum information and gravity. Within these themes, there are important research questions and opportunities to address them in the years and decades ahead. Efforts in developing a diverse quantum workforce are also discussed. This work summarizes the subtopical area Quantum Information for High Energy Physics TF10 which forms part of the Theory Frontier report for the Snowmass 2021 planning process.
Computer Science education has been evolving over the years to reflect applied realities. Until about a decade ago, theory of computation, algorithm design and system software dominated the curricula. Most courses were considered core and were hence mandatory; the programme structure did not allow much of a choice or variety. This column analyses why this changed Circa 2010 when elective subjects across scores of topics become part of mainstream education to reflect the on-going lateral acceleration of Computer Science. Fundamental discoveries in artificial intelligence, machine learning, virtualization and cloud computing are several decades old. Many core theories in data science are centuries old. Yet their leverage exploded only after Circa 2010, when the stage got set for people-centric problem solving in massive scale. This was due in part to the rush of innovative real-world applications that reached the common man through the ubiquitous smart phone. AI/ML modules arrived in popular programming languages; they could be used to build and train models on powerful - yet affordable - compute on public clouds reachable through high-speed Internet connectivity. Academia responded by adapting Computer Science curricula to align it with the changing technology landscape. The goal of this experiential piece is to trigger a lively discussion on the past and future of Computer Science education.