bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive uncertainty in state-estimation drives active sensing
Authors: Kaan Karagoz Osman , Kilic Aysegul , Yusuf Aydin Emin , Mert Ankarali Mustafa , Uyanik Ismail 
Published: November 2024

Abstract
Animals use active sensing movements to shape the spatiotemporal characteristics of sensory signals to better perceive their environment under varying conditions. However, the underlying mechanisms governing the generation of active sensing movements are not known. To address this, we investigated the role of active sensing movements in the refuge tracking behavior of Eigenmannia virescens, a species of weakly electric fish. These fish track the longitudinal movements of a refuge in which they hide by swimming back and forth in a single linear dimension. During refuge tracking, Eigenmannia exhibits stereotyped whole-body oscillations when the quality of the sensory signals degrades. We developed a closed-loop feedback control model to examine the role of these ancillary movements on the task performance. Our modeling suggests that fish may use active sensing to minimize predictive uncertainty in state estimation during refuge tracking. The proposed model generates simulated fish trajectories that are statistically indistinguishable from that of the actual fish, unlike the open-loop noise generator and stochastic resonance generator models in the literature. These findings reveal the significance of closed-loop control in active sensing behavior, offering new insights into the underlying mechanisms of dynamic sensory modulation.
Stability and agility trade-offs in spring-wing systems
Authors: Lynch James , Wold Ethan S , Gau Jeff , Sponberg Simon , Gravish Nick 
Published: November 2024

Abstract
Flying insects are thought to achieve energy-efficient flapping flight by storing and releasing elastic energy in their muscles, tendons, and thorax. However, ‘spring-wing’ flight systems consisting of elastic elements coupled to nonlinear, unsteady aerodynamic forces present possible challenges to generating stable and responsive wing motion. The energetic efficiency from resonance in insect flight is tied to the Weis-Fogh number (N), which is the ratio of peak inertial force to aerodynamic force. In this paper, we present experiments and modeling to study how resonance efficiency (which increases with N) influences the control responsiveness and perturbation resistance of flapping wingbeats. In our first experiments, we provide a step change in the input forcing amplitude to a series-elastic spring-wing system and observe the response time of the wing amplitude increase. In our second experiments we provide an external fluid flow directed at the flapping wing and study the perturbed steady-state wing motion. We evaluate both experiments across Weis-Fogh numbers from

1
<
N
<
10

. The results indicate that spring-wing systems designed for maximum energetic efficiency also experience trade-offs in agility and stability as the Weis-Fogh number increases. Our results demonstrate that energetic efficiency and wing maneuverability are in conflict in resonant spring-wing systems, suggesting that mechanical resonance presents tradeoffs in insect flight control and stability.
Identifying opportunities for nature-based solutions with geospatialized life cycle assessments and fine-scale socioecological data
Authors: Shirkey Gabriela , Anctil Annick , John Ranjeet , Kolluru Venkatesh , Mungai Leah , Kashongwe Herve , Cooper Lauren T , Celik Ilke , Fisher Joshua B , Chen Jiquan 
Published: November 2024

Abstract
As we increasingly understand the impact that land management intensification has on local and global climate, the call for nature-based solutions (NbS) in agroecosystems has expanded. Moreover, the pressing need to determine when and where NbS should be used raises challenges to socioecological data integration as we overcome spatiotemporal resolutions. Natural and working lands is an effort promoting NbS, particularly emissions reduction and carbon stock maintenance in forests. To overcome the spatiotemporal limitation, we integrated life cycle assessments (LCA), an ecological carbon stock model, and a land cover land use change model to synthesize rates of global warming potential (GWP) within a fine-scale geographic area (30 m). We scaled National Agricultural Statistic Survey land management data to National Land Cover Data cropland extents to assess GWP of cropland management over time and among management units (i.e. counties and production systems). We found that cropland extent alone was not indicative of GWP emissions; rather, rates of management intensity, such as energy and fertilizer use, are greater indicators of anthropogenic GWP. We found production processes for fuel and fertilizers contributed 51.93% of GWP, where 33.58% GWP was estimated from N2O emissions after fertilization, and only 13.31% GWP was due to energy consumption by field equipment. This demonstrates that upstream processes in LCA should be considered in NbS with the relative contribution of fertilization to GWP. Additionally, while land cover change had minimal GWP effect, urbanization will replace croplands and forests where NbS are implemented. Fine-scale landscape variations are essential for NbS to identify, as they accumulate within regional and global estimates. As such, this study demonstrates the capability to harness both LCA and fine-resolution imagery for applications in spatiotemporal and socioecological research towards identifying and monitoring NbS.
On a generating function for the isotropic basis functions and other connected results
Authors: Slepian Zachary , Chellino Jessica , Hou Jiamin , Greco Alessandro 
Published: November 2024

Abstract
Recently isotropic basis functions of N unit vector arguments were presented; these are of significant use in measuring the N-point correlation functions (NPCFs) of galaxy clustering. Here we develop the generating function for these basis functions—i.e. that function which, expanded in a power series, has as its angular part the isotropic functions. We show that this can be developed using basic properties of the plane wave. A main use of the generating function is as an efficient route to obtaining the Cartesian basis expressions for the isotropic functions. We show that the methods here enable computing difficult overlap integrals of multiple spherical Bessel functions, and we also give related expansions of the Dirac Delta function into the isotropic basis. Finally, we outline how the Cartesian expressions for the isotropic basis functions might be used to enable a faster NPCF algorithm on the CPU.
A metasurface integrated self-decoupled multiport tunable antenna for THz applications
Authors: Das Priyanka 
Published: November 2024

Abstract
A four port multiple-input multiple-output (MIMO) antenna is initially designed on silicon dioxide (quartz) substrate by arranging the antenna elements in an orthogonal configuration by using self-decoupling mechanism. Mean effective gain lower than 0.5 and radiation efficiency greater than 95% are obtained. Characteristic mode analysis of the proposed MIMO antenna has been performed using finite integration technique to validate the resonant modes. Further, a dual band self-multiplexing MIMO antenna has been constructed by loading each antenna element with a graphene constituted stub. Graphene loading in the antenna elements is done to introduce tunability in the MIMO operation in two frequency bands. The dual resonance frequencies range from 4.3–4.6 THz and 5.2–5.6 THz while the chemical potential is varied from 0.1 eV to 0.9 eV. The diversity performance of the MIMO antenna with and without graphene loading have been analyzed through numerical simulations. Envelope correlation coefficient lower than 0.0002 and diversity gain of 10 dB have been obtained. By biasing each of the antenna elements with different voltages, quadruplexing mechanism can be performed since each antenna resonates at a different frequency. Finally, a metasurface is designed on silicon dioxide (quartz) substrate to function as a reflective surface from 3.75–6.42 THz covering the resonance band of the tunable MIMO antenna for enhancing its gain to 14 dBi.
Enhanced proton acceleration using spiral-phase plasma mirrors
Authors: Shpilman Z , Amir Y , Hollinger R , Wang S , Zahedpour Anaraki S , Rocca J J , Pomerantz I 
Published: November 2024

Abstract
We present a method for generating intense vortex laser beams using spiral-phase plasma mirrors. These single-use micro-metric formations imprint a set amount of orbital angular momentum (OAM) to an arbitrary high power focusing beam. Using these beams, we irradiated ultrathin foils and measured the emission of ions from their back side. Utilizing a PW class laser, 5 J@45fs@2w resulting in an Intensity of 2×1020 W

cm

−
2

at spot focus, we observed an increase in the energy and numbers of these ions, compared to shots taken with reflection off flat plasma mirrors. A 45% increase in the proton numbers and a 35% increase in cutoff energy was observed. This is a major advance since the area of interaction and intensity are reduced due to the planar shape of the generated OAM laser. We review the available data-sets on laser ion acceleration using vortex beams, and conclude with a comparison to our findings.
Prediction of grain size in TB18 titanium alloy forgings by re-crystallization and grain growth modelling
Authors: Xiang Wei , Li Qineng , Zhang Feng , Yuan Wuhua 
Published: November 2024

Abstract
After plastic deformation, metals and alloys will be in a thermodynamically unstable high free en-ergy state with a tendency to spontaneously return to a low free energy state. Understanding the laws of occurrence and development of these processes is of great significance in improving and controlling the microstructure and properties of TB18 titanium alloy. In this paper, the recrystalli-sation kinetics is investigated based on the Johnson–Mehl–Avrami equation, and a kinetic model for the grain growth of solid solution TB18 alloy undergoing predeformation at different solid solution temperatures and different solid solution times has been established by combining the Arrhenius formula and Beck’s equation to derive a prediction model for the grain size that includes three types of parameters, namely, T, t, and ε, during the solid solution process. Using simulation soft-ware(Deform) based on finite element analysis to simulate the grain size of forging heat treatment, validate the grown-up model, and analyse the deformation of each part of the forging and the grain size deviation of its corresponding position. The results show that the deviation of grain size pre-dicted by the TB18 grain size model for the forging after heat treatment is less than 10%. Overall, the size prediction model of the grain growth has been proven to be accurate and usable.
Development of sustainable geopolymer concrete by synergistic utilization of jarosite and GGBS
Authors: Pandiyan Tarunkumar , Solaiyan Elavenil 
Published: November 2024

Abstract
Jarosite (JS) is a zinc industry byproduct generated during the smelting process of zinc ore. Due to its high concentration of heavy metal ions, it has been declared a hazardous material by the United States Environmental Protection Agency. As a result, the utilization of JS is highly limited. Hence, geopolymer concrete provides an eco-friendly solution for producing sustainable concrete by incorporating various industrial byproducts. This study focuses on formulating a binary blended geopolymer concrete that incorporates ground granulated blast furnace slag (GGBS) and JS as precursor materials, which are activated using an alkali solution. The mix design for the GGBS-JS-based geopolymer concrete involves varying several parameters, including the proportion of JS, total aggregate percentages, alkali-to-binder ratios, and sodium hydroxide molarities. A total of 48 mix proportions of geopolymer concrete are prepared and investigated to determine the fresh and strength characteristics. Based on the experimental values, it is observed that the utilization of JS in geopolymer concrete elevates the dispersion of binders, which increases the workability of concrete by 44.5%, and a 47.37% reduction in compressive strength is observed as the JS incorporation is increased. With the collected experimental values, a new mix design procedure is proposed. Furthermore, selected concrete samples with varying JS percentages are studied to determine microstructural characteristics such as x-ray diffraction, scanning electron microscope, and fourier transform infrared spectroscopy to analyze the developed geopolymer concrete’s phase transformation, surface morphology, and bond formation. This study also assessed JS’s heavy metal leaching properties and observed that toxicity by leaching is reduced by up to 99%, which justifies the utilization of JS in geopolymer concrete as a sustainable solution for the zinc industry waste management system.
Environmental factors influencing inshore migration in Japanese eel Anguilla japonica
Authors: Arai Takaomi , Kimura Shogo 
Published: November 2024

Abstract
Catadromous eel species of the genus Anguilla have a long and complex life history, migrating between offshore spawning areas and continental growth habitats. The eel larvae are passively transported, metamorphosing into glass eels and colonizing continental growth habitats. However, inshore migration and recruitment mechanisms need to be better understood, notwithstanding the increasing concern for sustainable future stock. Inshore migration of glass eel, Japanese eel Anguilla japonica, concerning regional environmental factors, examined throughout the year in central Japan facing the Pacific Ocean. A total of 3534 glass eels were collected through 33 investigations, with peak recruitment occurring from February to April. The inshore migration occurred for both new and full moon phases during ebb tide, with mean daily temperature ranging from 5.8 to 23.3 °C. In various environmental factors, a clear recruitment peak was found at the timing of westerly wind, with a significant positive correlation between wind speed and CPUE (catch per unit effort). Westerly wind advects the surface seawater towards the coastal area, and the stronger wind facilitates the inshore migration of glass eels to continental habitats. Understanding the reliable environmental factors affecting the inshore migration of Japanese glass eels can help facilitate the management and conservation of regional eel stocks.
Planar filter for microwave loss analysis in nickel and cobalt ferrite samples
Authors: Barboza Amanda G , Araujo Jorge A I , Alencar Marina de O , Silva Crislane P do N , Silva Evanimeck Bernardo S da , Llamas-Garro Ignacio , dos Reis Albuquerque Anderson , de Melo M T 
Published: November 2024

Abstract
This paper analyzes the microwave loss behavior of nickel ferrite (NFO) and cobalt ferrite (CFO) samples using a planar fractal filter, along with the study of the crystal lattice of each sample. The resonator geometry used is the fourth iteration of the Hilbert fractal. The Hilbert curve is employed to compress the filter area and increase the interaction area with the tested sample. The resonance frequency is approximately 1.1 GHz, within the range of 0.7 to 1.6 GHz. Filter measurements were conducted with samples of each material to evaluate their specific characteristics.
Enhancing crop protection through smart autonomous pesticide spray bot in sustainable agriculture
Authors: Meshram Ashish , Vanalkar Anil , Meshram Kavita , Badar Avinash , Mehta Girish , Kaushik Vishal 
Published: November 2024

Abstract
Pesticide spraying is a common practice employed to safeguard crops against harmful pest infestations and mitigate crop losses. However, the conventional use of handheld pesticide sprayers by the farmers raises concern regarding adverse health effects, including fatalities, and the environmental damage caused by excessive pesticide dispersion. Present robotic spraying solutions over and over again lack the precision and adaptability essential to report these problems effectively. This work covers the design of a smart autonomous pesticide spray bot that combines an advanced robotic architecture with a deep learning-based pest detection module, driven by the desire to improve both environmental sustainability and human safety. The bot autonomously navigates entire fields, utilizing a Convolutional Neural Network (CNN) trained on a diverse dataset to detect pests on plant leaves with high accuracy. Upon detection, the bot promptly activates its spraying management system, it has an adaptive spraying mechanism that precisely applies the amount of pesticide required to target the pests that have been identified. Evaluation of the system’s performance in a cotton field yielded significant results, including a robot speed of 0.25 m s−1, a pest detection accuracy of 97%, an average droplet size of 60 microns, a spray nozzle pressure of 7 bar, and a pesticide flow rate of 25 ml/s. The system raises issues with data dependency and expenses even if it has several benefits in terms of environmental conservation and public health. However, this system stands out as a major development in automated agriculture technology since it combines deep learning with a strong architectural design.
A dual-phase strategy for oscillation damping in power systems: transitioning from traditional stabilizers to solar farms using PSSE and PSCAD
Authors: Mohammad Sheikh Fareed , Bakhsh Farhad Ilahi 
Published: November 2024

Abstract
The integration of renewable energy into existing power grids presents significant challenges due to the intermittent nature and rapid dynamics of renewables. These characteristics can lead to power system oscillations, notably inter-area oscillations, which may result in power generation loss, reduced transmission capacity, and potential blackouts. Additionally, local power plant-level oscillations further minimise equipment wear and efficiency. This paper presents a Kundur two-area power system model to address these issues, offering a straightforward framework for analysing system stability. The model focuses on local and inter-area oscillations and their mitigation, which are crucial for maintaining system stability. Two mitigation techniques are modelled and analysed. The first uses phase-compensated power system stabilisers within the Kundur two-area network modelled in PSSE, emphasising their impact on system stability. The second replaces conventional hydropower plants with renewable energy sources, eliminating traditional damping equipment. In this scenario, a solar farm in hybrid mode manages both active and reactive power without stabilisers, as modelled in PSCAD. This approach effectively dampens inter-area and local oscillations. A three-phase bus fault is used to induce disturbances for system testing. RMS and EMT dynamic simulations are conducted within PSSE and PSCAD software, respectively, demonstrating the effectiveness of both techniques in mitigating power system oscillations, thereby enhancing system stability. Notably, the solar farm in hybrid mode presents a promising solution for integrating renewables while maintaining stability without traditional damping equipment.
Equity-driven investments in community energy systems: an optimization model applied to Washington State
Authors: Sifuentes Froylan E , Major Sophie C , McNett Ben , Davis Robert , Nath Hari 
Published: November 2024

Abstract
This paper presents the development and application of the equity and climate impacts optimization in community energy (ECOCE) model, a mixed integer linear tool designed to optimize equity-driven investment in community solar projects (CSPs). By providing insight on a variety of impacts of CSP investments, including electricity bill savings, solar production, and greenhouse gas emissions reduction, the model assists policymakers in understanding the possible trade-offs in benefits and impacts of CSP investments. Using a detailed case study of a one-time $100 million investment in CSPs in Washington State, the model evaluates potential scenarios under various funding distributions to determine the optimal allocation of state funds. The study highlights considerations of geographical equity and participation, trade-offs between maximizing greenhouse gas reductions and minimizing energy burden, and the potential to use the model in different regional contexts. The findings suggest that targeted investments can provide significant electricity bill savings ($6.5–8.5 million annually) for low-income communities while contributing to state decarbonization goals (4–42 kTons of avoided emissions annually) in Washington State, though political and practical considerations may influence the feasibility of these optimized allocations. The ECOCE model provides a robust framework for decision-makers aiming to balance a variety of political, equity, and climate change mitigation considerations in the transition to renewable energy.
Overview of porous magnesium-based scaffolds: development, properties and biomedical applications
Authors: Motaharinia Amir , Drelich Jaroslaw W , Sharif Safian , Ismail Ahmad Fauzi , Naeimi Farid , Glover Alexandra , Ebrahiminejad Mahshid , Bakhsheshi-Rad Hamid Reza 
Published: November 2024

Abstract
Magnesium (Mg) and its alloys are revolutionizing the field of interventional surgeries in the medical industry. Their high biocompatibility, biodegradability, and a similar elastic modulus to natural bone make porous Mg-based structures potential candidates for orthopedic implants and tissue engineering scaffolding. However, fabricating and machining porous Mg-based structures is challenging due to their complexity and difficulties in achieving uniform or gradient porosity. This review aims to thoroughly explore various fabrication procedures used to create metallic scaffolds, with a specific focus on those made from Mg-based alloys. Both traditional manufacturing techniques, including the directional solidification of metal-gas eutectic technique, pattern casting, methods using space holders, and modern fabrication methods, which are based on additive manufacturing, are covered in this review article. Furthermore, the paper highlights the most important findings of recent studies on Mg-based scaffolds in terms of their microstructure specifications, mechanical properties, degradation and corrosion behavior, antibacterial activity, and biocompatibility (both in vivo and in vitro). While extensive research has been conducted to optimize manufacturing parameters and qualities of Mg-based scaffolds for use in biomedical applications, specifically for bone tissue engineering applications, further investigation is needed to fabricate these scaffolds with specific properties, such as high resistance to corrosion, good antibacterial properties, osteoconductivity, osteoinductivity, and the ability to elicit a favorable response from osteoblast-like cell lines. The review concludes with recommendations for future research in the field of medical applications.