bluuebunny/crossref_metadata_2025_split huggingface dataset:
Superconductivity in Weyl semimetals with time reversal symmetry
Authors: Bai Xuesong , LiMing W , Zhou Tao 
Published: January 2025

Abstract
This theoretical study delves into the superconducting traits of Weyl semimetals that possess time reversal symmetry, utilizing the Bogoliubov–de Gennes equations. Our meticulous self-consistent calculations have unveiled a dual superconducting gap at the surface. We have also contrasted these findings with the superconducting characteristics of models that exhibit broken time-reversal symmetry. Our analysis indicates that Weyl semimetals with unimpaired time-reversal symmetry not only sustain a complete energy gap but also display modified Fermi arc surface states, which are notably distinct from those in models with compromised time-reversal symmetry. This work bridges the gap between theoretical expectations and experimental observations, advancing our understanding of the superconducting properties of Weyl semimetals.
System of fractal-fractional differential equations and Bernstein wavelets: a comprehensive study of environmental, epidemiological, and financial applications
Authors: Rayal Ashish 
Published: January 2025

Abstract
The fractal-fractional derivatives uniquely incorporate memory effects, heterogeneity, and fractal geometry, making them essential for studying dynamic systems compared to integer-order derivatives which cannot capture such intricate dynamics. So, this study aims to analyze the dynamical behaviour of the model of systems of differential equations under Caputo fractal-fractional derivative by designing a numerical framework based on the fractional order Bernstein wavelets. The Caputo fractal-fractional derivative under the power law kernel has been employed to obtain more accurate performances of the considered model as compared to fractional and integer order. A key novelty of this work lies in the implementation of fractional order Bernstein wavelets with collocation grids, which transform the complex differential equations into simpler algebraic equations, ensuring computational efficiency. The validity of the mentioned scheme is demonstrated by examining some famous problems, such as pond pollution problem, SIR epidemic modelling of infectious disease, a model of HIV interactions with CD4+T cells, and a financial model, showcasing its broad applicability across applied science, finance and engineering. For compactness, an error analysis using residual function is performed for fractal-fractional order. The graphs of the solution in integer, fractional and fractal-fractional order show that the achieved solutions are very close to the actual result of the examples and the error progressively decreases as the number of wavelets basis increases. In the case α = β = 1, the obtained approximated wavelet solutions for the suggested model are in good harmony with the exact solutions, the fourth-order Runge-Kutta (RK4) method and existing schemes provided in the literature. This investigation demonstrates that the mentioned scheme is very effective and straightforward for solving such kinds of fractal-fractional models.
Analysis of 1D NMR spectra with 2D image processing techniques
Authors: Meshkian M , Schmid N , Henrici A , Bruderer S 
Published: January 2025

Abstract
Rapid advances in NMR spectroscopy instrumentation demand powerful analysis techniques to be implemented to cope with the development. These include extracting patterns from the data acquired, such as images and 1D spectra. Furthermore, deep learning models have shown to be very powerful in extracting patterns from such data. However, current analysis techniques include several manual steps to label the data, which are usually time-consuming and crucially dependent on expert knowledge. Therefore, this paper aims to demonstrate the applicability of neural networks for extracting different spectral structures and specially, investigating an analysis approach, inherited from 2D image processing, to determine its usefulness in feature extraction from 1D spectroscopy data. The approach utilizes bounding-box algorithms, same as in image recognition, to recognize patterns in 1D spectra.
Simulating fish autonomous swimming behaviours using deep reinforcement learning based on Kolmogorov–Arnold Networks
Authors: Li Tao , Zhang Chunze , Zhang Guibin , Zhou Qin , Hou Ji , Diao Wei , Meng Wanwan , Zhang Xujin 
Published: January 2025

Abstract
The study of fish swimming behaviours and locomotion mechanisms holds significant scientific and engineering value. With the rapid advancements in artificial intelligence, a new method combining deep reinforcement learning (DRL) with computational fluid dynamics has emerged and been applied to simulate the fish’s adaptive swimming behaviour, where the complex fish behaviour is decoupled to focus on the fish’s response to the hydrodynamic field, and the simulation is driven by reward-based objectives to model the fish’s swimming behaviour. However, the scale of this cross-disciplinary method is directly affected by the efficiency of the DRL model. To promote it to more general application scenarios, there is a pressing need for further research on more efficient and economical network architectures to address the challenge of approximating state-value function in high-dimensional, dynamic, and uncertain environments. Building upon a previously proposed computational platform for the simulation of fish autonomous swimming behaviour, we integrated Kolmogorov–Arnold Networks(KANs) and tested their performance in point-to-point swimming and Kármán gait swimming environments. Experimental results demonstrated that, compared to long short-term memory Networks(LSTMs) and multilayer perceptron networks(MLPs), the introduction of KANs significantly enhanced the perception and decision-making abilities of the intelligent fish in complex fluid environments. With a smaller network scale, in the point-to-point swimming case, KANs effectively approximated the state-value function, achieving average reward improvements of up to 88.0% and 94.1% over MLPs and LSTMs networks, respectively, and increased by 766.7% and 105.6% in the Kármán gait swimming case. Under comparable network sizes, the intelligent fish with KANs exhibited faster learning capabilities and more stable swimming performance in complex fluid settings.
Decellularized cartilage tissue bioink formulation for osteochondral graft development
Authors: Golebiowska Aleksandra A , Tan Mingyang , Ma Anson WK , Nukavarapu Syam P 
Published: January 2025

Abstract
Articular cartilage and osteochondral defect repair and regeneration presents significant challenges to the field of tissue engineering (TE). TE and regenerative medicine strategies utilizing natural and synthetic-based engineered scaffolds have shown potential for repair, however, they face limitations in replicating the intricate native microenvironment and structure to achieve optimal regenerative capacity and functional recovery. Herein, we report the development of a cartilage extracellular matrix (ECM) as a printable biomaterial for tissue regeneration. The biomaterial was prepared through decellularization and solubilization of articular cartilage. The effects of two different viscosity modifiers, xanthan gum and Laponite®, and the introduction of a secondary photo-crosslinkable component on the rheological behavior and stability were studied. dcECM-Laponite® bioink formulations demonstrated storage modulus (G′) ranging from 750 to 4000 Pa, which is three orders of magnitude higher than that of the dcECM-XG bioink formulations. The rheological evaluation of the bioinks demonstrated the tunability of the bioinks in terms of their viscosity and degree of shear thinning, allowing the formulations to be readily extruded during 3D printing. Also, a spreadable ink composition was identified to form a uniform cartilage layer post-printing. The choice of viscosity modifier along with UV cross-linking warrants shape fidelity of the structure post-printing, as well as improvements in the storage and loss moduli. The modified ECM-based bioink also significantly improved the stability and allowed for prolonged and sustained release of loaded growth factors through the addition of Laponite®. The ECM-based bioink supported human bone-marrow derived stromal cell and chondrocyte viability and increased chondrogenic differentiation in vitro. By forming decellularized cartilage ECM biomaterials in a printable and stable bioink form, we develop a ‘Cartilage Ink’ that can support cartilaginous tissue formation by closely resembling the native cartilage ECM in structure and function.
Structural, electronic, mechanical, optical and magnetic properties of RhNbZ (Z = Li, Si, As) Half-Heusler compounds: a first-principles study
Authors: Bejo Adem Beriso , Shura Megersa Wodajo , Tadele Kumneger , Afrassa Mesfin Asfaw , Maremi Fekadu Tolessa 
Published: January 2025

Abstract
Structural, mechanical, electronic, optical and magnetic properties of the cubic RhNbZ (Z = Li, Si, As) half-Heusler compounds is reported using density functional theory (DFT) as implemented in quantum espresso simulation package. Structurally, the compounds are most stable when they are in type I atomic arrangement. Studies of mechanical properties indicate that all the three compounds are ductile in nature and mechanically stable. Calculations of electronic band structure and density of states (DOS) affirm that RhNbSi is a semi-conductor with an indirect band gap of 0.662 eV and 1.0095 eV from generalized gradient approximation (GGA) and GGA+U approaches respectively, where U is Hubbard parameter, RhNbLi has metallic property under both GGA and GGA+U approaches whereas RhNbAs has metallic nature under GGA prediction but it has half-metallic property under GGA+U approach, a property which is essential for spintronic applications. Optical parameters such as dielectric function, reflectivity, refractive index, extinction coefficient, absorption coefficient, optical conductivity and electron energy loss were estimated in the photon energy range of 0–40 eV. Results from these properties calculations reveal that both absorption coefficient and optical conductivity have maximum values whereas electron energy loss has minimum value in the lower energy ranges which show that the materials under our study can be considered as potential candidates for optoelectronic applications. From magnetic property calculations, RhNbSi is predicted to be nonmagnetic material but RhNbLi and RhNbAs have magnetic nature.
Laser treated super hydrophobic glass for solar PV self cleaning application: a SWOT-TWOS-based analysis
Authors: Rai Rahool , Ishak Mahadzir , Kumarasamy Sudhakar , Bin Mohd Halil Aiman , Quazi M M 
Published: January 2025

Abstract
With the increasing demand for sustainable energy solutions, laser surface modification has emerged as a promising technique to enhance the functional properties of materials, particularly in optimizing glass surfaces for solar applications that require hydrophobicity and environmental resilience to improve photovoltaic performance and durability. Consequently, a SWOT-TWOS analysis is conducted to identify the strengths, weaknesses, opportunities, and threats of integrating these technologies. This analysis assesses the advantages, such as improved light diffusion and reduced glare, along with the disadvantages, including decreased transparency and potential glass damage. Additionally, there are opportunities for technological and sustainable advancements, as well as threats such as quality control issues. The SWOT analysis for Laser Treated Super Hydrophobic Glass in solar PV self-cleaning applications revealed a distribution of 42% technical, 26% environmental, and 21% economic factors, with 11% of factors spanning all three domains. Notably, the two elements are complex and interdependent across multiple domains, underscoring the intricate influences affecting the viability of this technology. By identifying these characteristics, the study aims to provide a comprehensive understanding of laser texturing potential and limitations, as well as recommendations for future research and practical applications.
Tuning of electronic, optical and lipophilic behaviours of adamantane through various substitutions
Authors: R Aravindhan , Hu Jianping , Momeen M Ummal 
Published: January 2025

Abstract
Successive tuning of electronic, optical and lipophilic characteristics of adamantane molecules are obtained by various halogen substitutions at bridgehead and bridge positions of adamantane. In accordance with this, surface passivated halo adamantanes and dodecahalo adamantanes exhibit impressive tuning of transport properties. In all molecular complexes, electrophilicity and molecular polarizability show progressive growth from fluorine to iodine whereas vertical excitation energies of molecules also follow the same trend. Prominent sigma holes are observed on the outer lobe of bromine and iodine in most of the cases. High hydrophobicity and lipophilicity of the adamantane has a prominent application in medicinal chemistry as a lipophilic bullet for a drug. Through halogen substitution this is more significant in both electropositive and electronegative binding sites exhibited by the anisotropic charge distribution of the halogen.
Experimental investigation of CF8 stainless steel impeller quality using PLA-based fused deposition modeling-assisted investment casting
Authors: Shah Margi , Patel Dhiren , Pande Sarang , Abidi Mustufa Haider , Alasim Fahad 
Published: January 2025

Abstract
The conventional Investment Casting (IC) process is extensively used for manufacturing parts with intricate shapes and complex geometries. However, its drawbacks include long cycle times and costly tooling, making it ideal for mass production but inefficient for frequent design changes, small batch production, or customized products. To address these challenges, a novel hybrid method known as Fused Deposition Modeling Assisted Investment Casting (FDMAIC) has been developed. In FDMAIC, the wax pattern is replaced by an FDM-printed pattern, while all other steps follow the conventional IC process. In this study, a semi-open impeller for a centrifugal pump was produced using FDMAIC, with Polylactic Acid (PLA) as the pattern material and CF8 for casting. Dimensional accuracy and surface roughness, key indicators of quality, were evaluated at both the printing and casting stages. Critical dimensions such as outer and inner diameters, shroud and blade thicknesses, and total height were measured, along with surface roughness at the shroud and blade surfaces. In the final cast, maximum dimensional deviation was observed in Outer diameter(−2.408 mm), and minimum dimensional deviation was observed in total height(−0.169 mm). The surface roughness values obtained at the shroud and blade surface of the final cast were 4.64 μm 6.67 μm, respectively. Microstructure and hardness testing were also performed on the FDMAIC impeller to validate the process. The results provide detailed insights into the feasibility of FDMAIC and suggest areas for further improvement.
Preparation and flame retardancy of an Al2O3 infiltration layer on polycarbonate surface
Authors: Ren Shibo , Xu Jianlin , Niu Lei , Yang Penghui 
Published: January 2025

Abstract
In this study, the surface flame retardancy of polycarbonate (PC) was improved and the impact of flame retardants on the substrate were minimized by pre-mixing Al2O3 particles with dichloromethane, an infiltration promoter, to form a suspension, and then treating PC with the suspension to form an Al2O3 infiltration layer. For this layer, its structure and composition were characterized, its flame retardancy was evaluated, and its flame retardancy mechanism was investigated. The characterization results confirmed that an Al2O3 infiltration layer was successfully prepared on the PC surface under the aid of dichloromethane and that the involvement of dichloromethane induced certain microscopic pores and voids in the PC, with some dichloromethane remaining within the surface infiltration layer. The surface Al2O3 infiltration layer mainly served as a condensed-phase flame retardant. The infiltration layer prepared using a suspension with a dichloromethane-to-Al2O3 mass ratio of 24:1 not only exhibited a good overall performance but also achieved the best improvement in the PC flame retardancy, such as an increase in the vertical burning rating from HB to V-0, as well as the LOI increased from 24 to 31.3, and a 35% reduction in the peak heat release rate compared to those of pure PC.
Cultural and creative industries development on cities: a perspective from urban innovation ecosystems
Authors: Dong Yue , Zhang Qingfeng 
Published: January 2025

Abstract
As an emerging economic form, the cultural and creative industries (CCI) have gradually become a key force in driving urban economic transformation and enhancing urban competitiveness. In the knowledge economy, the CCI are producers of cultural content and vital sources of innovative resources. This study explores CCI’s role within urban innovation ecosystems and their impact on cities. The research employs a combination of theoretical model construction and empirical analysis. It begins with a literature review and theoretical analysis to construct a relationship model between the CCI and urban innovation ecosystems, as well as a hypothetical model of the impact of the CCI on cities. An online survey was conducted to collect data, and the results validate the models’ effectiveness. The findings indicate that the CCI significantly promotes urban development. They directly drive the economic transformation and upgrading of cities and indirectly foster sustainable urban development by optimizing the innovation environment and enhancing the vitality of innovation entities. The CCI plays a crucial role in urban innovation ecosystems, enhancing urban innovation capacity and competitiveness through interactions. The system reveals the pathways through which the CCI functions within urban innovation ecosystems and offers corresponding development recommendations. It provides theoretical support and practical references for promoting the synergy between the CCI and urban development.
GPM-based analysis of vertical structure of typical precipitation during 2020 extra-long Meiyu season in Northern Zhejiang
Authors: Du Shuang , Wu Bin , Yin Hao , Shen Yian 
Published: January 2025

Abstract
The Meiyu season during 2020 in China was an extra-long flood season, in particular, the northern region of Zhejiang experienced long duration of precipitation and frequent heavy rainfall processes. In this study, we selected three typical precipitation cases during 2020 ultra-long Meiyu season, using dual frequency spaceborne radar data (GPM DPR) revealed the characteristics of precipitation macro-micro vertical structure characteristics at different life cycle. In the development stage, the large-value area of particle diameter (≥ 2 mm) between the height of 5 km and ground level corresponds to heavy rain zone, while a lower particle number density for the same particle size results in temporarily reduced precipitation efficiency. In the maturity stage, large-scale water condensate particles remain between the height of 5 and 6 km, and cloud anvil structures are identifiable in radar reflectivity factor profiles. In the dissipation stage, with the weakness of the dynamic weather conditions, the height of the radar echo and particle distribution shifts closer to the surface layer. Further analysis of the effect of water condensate particles on surface rainfall intensity shows that the changes from development to maturity and dissipation stages in convective precipitation are primarily determined by the hydrometeor particle concentration during the Meiyu season. For stratiform precipitation, it is more closely related to particle concentration parameters. Even when particle concentration and size are high, the absence of strong dynamic mechanisms to trigger latent heat release means raindrops do not continue to grow, resulting in minimal precipitation.
Development of Eco-friendly CQDs/TiO2 nanocomposite for enhanced photocatalytic degradation of methyl orange dye
Authors: Prabhakaran Prasanna Kumar , Balu Surendar , Sridharan Gokul , Ganapathy Dhanraj , Sundramoorthy Ashok K 
Published: January 2025

Abstract
This research explores the photocatalytic degradation of methyl orange (MO) dye using a novel TiO2/biowaste-derived carbon quantum dots (CQDs) composite under visible light. The TiO2, biowaste-derived CQDs, and TiO2/CQDs composite were synthesized via a hydrothermal method and characterized using UV-visible spectroscopy (UV–vis), Fourier-transform infrared spectroscopy (FTIR), x-ray diffraction (XRD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). TEM analysis revealed a uniform distribution of CQDs within the TiO2 matrix, confirming the successful integration of CQDs into the nanocomposite structure. The incorporation of CQDs significantly reduced the band gap of the composite, enhancing its photocatalytic activity under visible light. Photocatalytic experiments, conducted with a 300 W Xe lamp as the light source, utilized a 20 mg catalyst dosage for a 15 ppm MO solution. The TiO2/CQDs composite demonstrated an outstanding degradation efficiency of 85% within 130 min, following a pseudo-first-order kinetic model with a rate constant of k = 0.01353 min−1. In comparison, pure TiO2 and CQDs achieved degradation efficiencies of 61% and 19%, respectively, under the same conditions. These findings underline the potential of TiO2/biowaste-derived CQDs composites as a sustainable, eco-friendly approach for wastewater treatment and environmental remediation through visible-light-driven photocatalysis.
Methodology for designing low-cost robots with parallel kinematics
Authors: Dimitrova Reneta , Nikolov Stiliyan , Tsolov Stanislav , Dimitrov Slav 
Published: January 2025

Abstract
In this paper, a methodology for the design of low-cost robots with parallel kinematics is proposed, involving ten stages. The methodology offers an alternative to the classic methods used in the design of robots with parallel kinematics, taking into account the capabilities of modern CAD/CAE systems, which is of particular importance due to the limited financial resources for designing and manufacturing low-cost robots with parallel kinematics. The main classical methods used in the design of robots with parallel kinematics are described, at the individual stages of the proposed methodology and the possibilities for accelerated solving of the relevant tasks with the use of CAD/CAE systems. Recommendations are given for the methods and means used at each of the proposed stages. The proposed methodology can serve as a basis for defining the main steps performed when designing robots with parallel kinematics. The developed methodology has been tested for the design of a low-cost robot with parallel kinematics, with a positioning accuracy of ± 0.1 mm. The results of the application of the proposed methodology have been analyzed.