bluuebunny/crossref_metadata_2025_split huggingface dataset:
Repulsive magnetic levitation-based electromagnetic energy harvesting of a low-frequency ocean wave
Authors: Park J. , Pillai N. , Wereley N. M. , Flatau A. B. 
Published: February 2024

In this study, an electromagnetic energy harvester for a low-frequency ocean wave was developed in a compact 3D-printed structure. Ocean wave energy conversion technologies exist, but maintaining them in the harsh marine environment is crucial for business. Friction increases maintenance costs. Therefore, magnetic levitation, being friction-free, is used for cost-effective, low-maintenance electromagnetic energy harvesting applications. Low-frequency oscillating energy is captured using repulsive magnetic levitation with a buoy and generating electricity using a permanent magnet and copper coil. A levitating magnet is repelled by a fixed one, inducing electricity as it passes through a coil. Experiments with a 0.1 Hz sine wave mimic the average frequency of ocean waves, showing successful voltage peaks at intervals. The output voltage and measured power from the harvester exhibit variations influenced by multiple parameters. The maximum output voltage observed was 3.4 V and an average of 99 mW of power was calculated. The experiment demonstrates the feasibility of using repulsive magnetic levitation for low-frequency wave energy harvesting and also encompasses various harvester configurations, including transfer magnet forces and top magnets.
Age, growth and maturity of an endemic valuable resource, the Rio skate (Rioraja agassizii (Chondrichthyes: Rajiformes)), off Uruguay and northern Argentina
Authors: Bianchi Santiago J. , Roman Jorge M. , Lucifora Luis O. , Barbini Santiago A. 
Published: February 2024

Context Rioraja agassizii is a vulnerable species endemic to the Southwest Atlantic. It is caught by trawl fisheries throughout its range. Aims To determine the age, estimate growth parameters, and age and size at maturity. Methods Ages were determined using vertebrae readings. To fit growth models, a Bayesian framework was employed with the von Bertalanffy, Gompertz and Logistic candidate models. To estimate age and size at maturity, a logistical ogive was fitted to binomial maturity data. Key results Maximum ages determined for males and females were 12 and 11 years respectively. The von Bertalanffy model was selected as the best one and there were no differences between sexes (mean parameters: L∞ = 684.8 mm, k = 0.33 years−1 and L0 = 105.5 mm). Age and size at maturity were estimated at 3.31 and 4.55 years, and 485.02 and 544.55 mm TL for males and females respectively. Conclusions Rioraja agassizii has a moderate growth rate and age at maturity was similar to those of skate species with a similar body size. Implications Because skate species have different maximum ages, growth rates and maturity parameters, we strongly recommend urgent species-specific management measures for the pool of skate species exploited in Argentina.
Impacts of necrotising disease on the Endangered cauliflower soft coral (Dendronephthya australis)
Authors: Steinberg Rosemary Kate , Turnbull John , Ainsworth Tracy D. , Dafforn Katherine A. , Poore Alistair G. B. , Johnston Emma L. 
Published: February 2024

Context Diseases have affected coral populations worldwide, leading to population declines and requiring active restoration efforts. Aims Describe population and individual impacts of necrotising disease in the Endangered octocoral Dendronephthya australis. Methods We quantified population loss and recruitment by using reference photos, survey and GPS mapping and described disease lesions by using histopathology. Key results From December 2019 to January 2020, we observed polyp loss, necrotic lesions and loss of large colonies of D. australis at Botany Bay, New South Wales, Australia. By September 2020, only a few scattered recruits remained, and all large colonies were lost. Histopathology of colonies sampled in January 2020 confirmed that the disease had resulted in necrosis, gastrovascular canal collapse and internal colony integrity loss, leading to mortality. New recruits were recorded within 10 months of disease onset, and large colonies within 18 months. Conclusions Although the necrotising disease had significant impacts on both the individual and population level, natural recruitment began quickly. As such, unlike in other populations, restoration is not currently required in the Bare Island D. australis population. Implications The extent of disease impact at the individual and population levels suggests that monitoring for lesions should be undertaken before developing conservation and restoration strategies for this species.
A zero-shot fault attribute transfer learning method for compound fault diagnosis of power circuit breakers
Authors: Yang Qiuyu , Lin Yuyi , Ruan Jiangjun 
Published: February 2024

Abstract
Diagnosis of compound mechanical faults for power circuit breakers (CBs) is a challenging task. In traditional fault diagnosis methods, however, all fault types need to be collected in advance for the training of diagnosis model. Such processes have poor generalization capabilities for industrial scenarios with no or few data when faced with new faults. In this study, we propose a novel zero-shot learning method named DSR-AL to address this problem. An unsupervised neural network, namely, depthwise separable residual convolutional neural network, is designed to directly learn features from 3D time-frequency images of CB vibration signals. Then we build fault attribute learners (ALs), for transferring fault knowledge to the target faults. Finally, the ALs are used to predict the attribute vector of the target faults, thus realizing the recognition of previously unseen faults. The orthogonal experiments are designed and conducted on real industrial switchgear to validate the effectiveness of the proposed diagnosis framework. Results show that it is feasible to diagnose target faults without using their samples for training, which greatly saves the costs of collecting fault samples. This will help to accurately identify the various faults that may occur during CB’s life cycle, and facilitate the application of intelligent fault diagnosis system.
Adaptive convolutional sparsity with sub-band correlation in the NSCT domain for MRI image fusion
Authors: Hu Qiu , Cai Weiming , Xu Shuwen , Hu Shaohai , Wang Lang , He Xinyi 
Published: February 2024

Abstract

Objective. Multimodal medical image fusion (MMIF) technologies merges diverse medical images with rich information, boosting diagnostic efficiency and accuracy. Due to global optimization and single-valued nature, convolutional sparse representation (CSR) outshines the standard sparse representation (SR) in significance. By addressing the challenges of sensitivity to highly redundant dictionaries and robustness to misregistration, an adaptive convolutional sparsity scheme with measurement of the sub-band correlation in the non-subsampled contourlet transform (NSCT) domain is proposed for MMIF. Approach. The fusion scheme incorporates four main components: image decomposition into two scales, fusion of detail layers, fusion of base layers, and reconstruction of the two scales. We solved a Tikhonov regularization optimization problem with source images to obtain the base and detail layers. Then, after CSR processing, detail layers were sparsely decomposed using pre-trained dictionary filters for initial coefficient maps. NSCT domain’s sub-band correlation was used to refine fusion coefficient maps, and sparse reconstruction produced the fused detail layer. Meanwhile, base layers were fused using averaging. The final fused image was obtained via two-scale reconstruction. Main results. Experimental validation of clinical image sets revealed that the proposed fusion scheme can not only effectively eliminate the interference of partial misregistration, but also outperform the representative state-of-the-art fusion schemes in the preservation of structural and textural details according to subjective visual evaluations and objective quality evaluations. Significance. The proposed fusion scheme is competitive due to its low-redundancy dictionary, robustness to misregistration, and better fusion performance. This is achieved by training the dictionary with minimal samples through CSR to adaptively preserve overcompleteness for detail layers, and constructing fusion activity level with sub-band correlation in the NSCT domain to maintain CSR attributes. Additionally, ordering the NSCT for reverse sparse representation further enhances sub-band correlation to promote the preservation of structural and textural details.
MHD second-grade nanofluid slip flow over a stretching sheet subject to activation energy, thermophoresis, and Brownian effects
Authors: Rath Chinmoy , Nayak Anita 
Published: February 2024

Abstract
In this work, the magnetohydrodynamic flow of two engine oil-based second-grade nanofluids Copper (Cu) and Titanium oxide (TiO
2) over a penetrable stretching sheet is studied. The flow, heat and mass transfer characteristics in the existence of activation energy, inclined magnetic field, Brownian diffusion, elastic deformation, and thermophoresis are examined. The coupled nonlinear model equations are formulated by implementing the Modified Buongiorno model and then are non-dimensionalized by the similarity transformation technique. The non-dimensional equations are simulated numerically using the bvp4c solver. Graphs are plotted to study the flow behaviour of nanofluid with the rate of entropy generation and Bejan number. The outcomes of skin friction coefficient, Nusselt number and Sherwood number are exhibited via surface plots. From the analysis, a higher inclination of the magnetic field decays the velocity and amplifies the temperature profiles. The heat transport rate diminishes with the Brownian diffusion, thermophoresis and elastic deformation parameters. The mass transport rate is accelerated due to the activation energy parameter. The entropy generation rate is enhanced with the Brinkman, Biot and local Reynolds numbers. Furthermore, it is seen that engine oil-based TiO
2 nanofluid has larger velocity, temperature and rate of entropy generation than engine oil-based Cu nanofluid. The current examination has applications in automobile radiators, microchips, biomedical engineering, and extraction of geothermal power.
Optical voice encryption based on speckle-illuminated fourier ptychography and plaintext-related chaotic random phase mask
Authors: Li Jiaxin , Xu Wenjun , Wang Yonghui , Li Fei , Liu Shuaiqi , Su Yonggang 
Published: February 2024

Abstract
In this paper, we propose an optical voice encryption scheme based on speckle-illuminated Fourier ptychography (FP) and plaintext-related chaotic random phase mask (CRPM). In this proposed encryption scheme, the plaintext-related CRPMs are generated by chaotic Lozi map and secure hash algorithm (SHA-256). During the encryption process, the voice signal to be encrypted is first converted into a two-dimensional (2D) voice map. Then, with the help of CRPMs and speckle-illuminated FP, the voice map is encrypted into a series of noise-like low-resolution images. During the decryption process, the original voice signal can be recovered from the series of noise-like low-resolution images via Fourier ptychographic phase retrieval algorithm and the CRPMs. To the best of our knowledge, it is the first time to use the Fourier ptychography and chaotic random phase mask to implement the optical encryption of the voice signal. In addition, in this proposed encryption scheme, the chaotic parameters can replace the whole random phase masks as the secret keys, which makes the management and transmission of the secret keys become more convenient. Moreover, since the plaintext-related chaotic parameter keys can be updated dynamically, the security of the proposed encryption scheme can be further improved. The feasibility, security and robustness of the proposed encryption scheme are further analyzed by numerical simulations.
Annealing effects on the structural, positron annihilation parameters, and electrical properties of Fe2O3- PbO2-TeO2 glasses
Authors: El-Desoky M M , Abdel-Hady E E , Mohamed Hamdy F M , Hassanien Mohamed H M , Abdallah N , Harby Amany E 
Published: February 2024

Abstract
This study focuses on the transformation of selected glasses consisting of 20Fe2O3–xPbO2–(80–x)TeO2 (where x = 5, 10, 15, 20, and 25 mol%) with varying concentrations of PbO2, into nanomaterials through annealing at a temperature close to the crystallization temperature (Tc). The physical and chemical properties of the resulting samples were investigated. The chemical structure was analyzed using Fourier Transform Infrared spectroscopy (FTIR), which revealed no significant chemical changes except for an increase in the concentration of PbO2. X-ray diffraction (XRD) was used to study the crystal structure. Improvements were seen with increasing PbO2 concentrations, and these improvements were further increased after the sample was annealed. Furthermore, positron annihilation lifetime (PAL) spectroscopy was used to study the microstructure, more precisely the size of vacancy-type defects. A correlation was established between the PAL and the properties of the samples. The size of the vacancy-type defects was confirmed by calculating the distribution of the long lifetime deduced from the PAL. In this work, the overall influence of PbO2 concentration and thermal treatment on the chemical and crystalline structures, electrical conductivity, and microstructure of the studied nanomaterials is highlighted. The results provide valuable insights into the relationship between the PAL and the properties of the samples and provide potential opportunities to tailor their properties for different applications.
Using machine learning to optimise chameleon fifth force experiments
Authors: Briddon Chad , Burrage Clare , Moss Adam , Tamosiunas Andrius 
Published: February 2024

Abstract
The chameleon is a theorised scalar field that couples to matter and possess a screening mechanism, which weakens observational constraints from experiments performed in regions of higher matter density. One consequence of this screening mechanism is that the force induced by the field is dependent on the shape of the source mass (a property that distinguishes it from gravity). Therefore an optimal shape must exist for which the chameleon force is maximised. Such a shape would allow experiments to improve their sensitivity by simply changing the shape of the source mass. In this work we use a combination of genetic algorithms and the chameleon solving software SELCIE to find shapes that optimise the force at a single point in an idealised experimental environment. We note that the method we used is easily customised, and so could be used to optimise a more realistic experiment involving particle trajectories or the force acting on an extended body. We find the shapes outputted by the genetic algorithm possess common characteristics, such as a preference for smaller source masses, and that the largest fifth forces are produced by small `umbrella'-like shapes with a thickness such that the source is unscreened but the field reaches its minimum inside the source. This remains the optimal shape even as we change the chameleon potential, and the distance from the source, and across a wide range of chameleon parameters. We find that by optimising the shape in this way the fifth force can be increased by 2.45 times when compared to a sphere, centred at the origin, of the same volume and mass.
Pulsar Timing Array signature from oscillating metric perturbations due to ultra-light axion
Authors: Hwang Jai-chan , Jeong Donghui , Noh Hyerim , Smarra Clemente 
Published: February 2024

Abstract
A coherently oscillating ultra-light axion can behave as dark matter. In particular, its
coherently oscillating pressure perturbations can source an oscillating scalar metric
perturbation, with a characteristic oscillation frequency which is twice the axion Compton
frequency. A candidate in the mass range 10(-24,-21) eV can provide a signal in the
frequency range tested by current and future Pulsar Timing Array (PTA) programs. Involving the
pressure perturbations in a highly nonlinear environment, such an analysis demands a relativistic
and nonlinear treatment. Here, we provide a rigorous derivation of the effect assuming
weak-gravity and slow-motion limit of Einstein's gravity in zero-shear gauge and show that dark
matter's velocity potential determines the oscillation phase and frequency change. A monochromatic
PTA signal correlated with the velocity field would confirm the prediction, for example, by
cross-correlating the PTA results with the future local velocity flow measurements.
Mixed convection in turbulent particle-laden channel flow at Re
τ
= 180
Authors: Zaza D , Iovieno M 
Published: February 2024

Abstract
A numerical investigation of mixed convection in a turbulent particle-laden channel flow is presented. Using Eulerian-Lagrangian Direct Numerical Simulations (DNSs) within the point-particle approach, the interaction between wall turbulence, particle inertia and thermal inertia, and buoyancy in the two-way coupling regime has been studied. The flow dynamics is controlled by the friction Reynolds number, Richardson number, particle Stokes and thermal Stokes numbers, and the Prandtl number. The effects of particle inertia and buoyancy on fluid and particle statistics are shown for a friction Reynolds number of 180, Stokes numbers ranging from 0.6 to 120, Richardson numbers ranging from 2.72 × 10−4 to 27.2 at a single Prandtl number, 0.71. The results indicate that the effect of particle inertia is significant on particle statistics, but not as pronounced on fluid statistics at the relatively low volume fraction considered. Particle inertia modulates the overall heat flux in a non-monotonic way.
Assessment of a Flow-dependent Subgrid Characteristic Length for Large-Eddy Simulation on Anisotropic Grids
Authors: D’Alessandro V , Delorme Y , Falone M , Wasserman M , Ricci R 
Published: February 2024

Abstract
This paper presents the latest results of a long track development activity in the context of low-dissipative finite volume method for compressible flows. Specifically, here we focus our attention on the Large-Eddy Simulation (LES) approach which can be considered a good candidate for turbulent flow simulations over the next decades. One of the key ingredients of LES models is the subgrid length scale which is typically evaluated based on the local mesh size. This standard approach suffers from loss of accuracy on anisotropic grids that are commonly employed to obtain sufficient wall-normal resolution, whilst keeping the total cell count to a minimum. In order to avoid this issue, we assess the effectiveness of a velocity-gradient-based length scale, referred to as least square length (LSQ) [1]. In this paper, we present for the first time results obtained with the LSQ length scale in the context of compressible LES. The superiority of the LSQ approach over the standard cubic-root length scale is demonstrated in terms of accuracy and overall time to solution.
Numerical and experimental study to examine methods to increase the convectional heat transfer of recuperator tubes
Authors: Trampe E , Hauch J , Büschgens D , Pfeifer H 
Published: February 2024

Abstract
The use of structured tubes in tube bundle recuperators is intended to improve the energy efficiency of gas-fired industrial furnace systems with central air preheating. Currently, smooth tubes as well as smooth tubes with internal twisted tape are commonly utilised. The increased surface area of structured tubes leads to an increased heat transfer between the off-gas and the combustion air. However, structuring leads to an increased pressure loss. The aim is to find an optimal operating range in which the pressure losses are still acceptable and the greatest increase of heat transfer compared to the reference will be achieved. Smooth tubes and also smooth tubes with twisted tapes are considered as reference systems in comparison to two concave structured tubes. CFD simulations were used to investigate the influence of the operating parameters of combustion air velocity and off-gas velocity on heat transfer according to industrial scale. The simulations have shown that the heat flow increases with the honeycomb depth and strongly depends on the operating conditions. Experimental measurements in a test bench were carried out to validate the model and confirm the positive influence of structuring on heat transfer.
Investigating the relationship between surface roughness and reflectance properties of building materials
Authors: Marchini F , Chiatti C , Fabiani C , Latterini L , Pisello AL 
Published: February 2024

Abstract
Materials used in the exterior envelope of buildings and open urban surfaces, in general, strongly affect the urban thermal balance, determining the general magnitude of urban overheating. The surface temperature of reflective materials varies as a function of physical and geometrical properties. Quantifying the influence of surface roughness on reflectance properties has crucial relevance since reflectance can significantly affect the reduction of the absorbed solar radiation and, in turn, the energy demand for cooling. Through an experimental and statistical investigation, this research aims to analytically assess the impact of surface roughness on the reflectance and thermal performances of building materials and, in turn, the role that roughness could play towards urban cooling and mitigation. Results show that the surface’s different roughness affects the sample’s reflectance coefficient, leaving it basically unchanged in the Ultraviolet and Visible ranges but with appreciable differences in the Near-Infrared wavelengths. This outcome confirms the correlation between the surface roughness and the optical and thermal characteristics of the building materials, making evident the importance of the study of superficial topography towards the mitigation of Urban Heat Island phenomena.
Numerical investigation of radiative transfer during oxyfuel combustion of hydrogen and hydrogen enriched natural gas in the container glass industry
Authors: Ott F , Losacker J , Schmitz N , Pfeifer H 
Published: February 2024

Abstract
The substitution of natural gas with hydrogen is one way to eliminate direct CO2 emissions. However, oxyfuel combustion of hydrogen or hydrogen enriched natural gas leads to different exhaust gas properties due to a changed composition compared to conventional combustion. In combustion simulation, the emissivity of a gas mixture is usually approximated using a Weighted Sum of Gray Gases (WSGG) model. Most of the existing WSGG models have been validated for natural gas combustion with air or oxyfuel and are therefore not applicable to hydrogen-oxyfuel combustion. CFD simulations showed, that none of the investigated WSGG models is able to predict the radiative heat transfer for all considered combustion scenarios with appropriate accuracy. In addition, in container glass manufacturing more than 95% of the heat flux to the glass surface is transferred by radiation because of the high process temperatures. Due to the changed gray gas emissivity, the high content of water vapor leads to a different emission spectrum of the exhaust gas. The influence of the changed emission spectrum on radiative heat transfer and the penetration depth of radiation in the glass melt is investigated using a simulation model of a pilot plant and non-gray modelling of the radiation transport. The CFD simulations show slightly enhanced radiative heat transfer to the glass and a slightly deeper penetration depth especially for wavelength below 2.2 μm for hydrogen-oxyfuel combustion.