bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phase fraction measurement of gas-liquid flow based on cyclonic capacitive sensor (CCS) and inverse drift flux method
Authors: Yuan Chao , Wang Jinghan , Xu Ying 
Published: August 2024

Abstract
As the demand for clean energy sources like natural gas increases, the need for methods to measure the phase fraction of gas-liquid two-phase flows, which have complex and variable flow patterns, becomes more pronounced. This study introduces a phase fraction measurement method based on a cyclonic capacitive sensor. An effective phase fraction prediction model for the gas-liquid flow measurement section is established based on the capacitive signals. Using the drift flux principle, the dimensionless drift velocity of the spiral annular flow is analyzed, and a volume gas fraction (GVF) prediction model based on the ‘inverse drift flux method’ is established. Experimental results show that this method is suitable for a wide range of phase fraction measurements and is highly accurate. When the liquid volume fraction (LVF) is less than 10%, the average relative error of the predicted GVF is 0.3%; for the LVF from 10% to 30%, the average relative error is 1.4%.
Noise reduction method for wind turbine gearbox vibration signals based on CVMD-DRDSAE
Authors: Yao Jinbao , Yue Bohao , Wang Yizhu , Li Xiang 
Published: August 2024

Abstract
Wind turbine gearbox fault feature extraction is difficult due to strong background noise. To address this issue, a noise reduction method combining comprehensive learning particle swarm optimization-variational mode decomposition (CLPSO-VMD) and deep residual denoising self-attention autoencoder (DRDSAE) is proposed. Firstly, the proposed CLPSO-VMD algorithm is used to decompose the noisy wind turbine gearbox vibration signals. Subsequently, the intrinsic mode functions highly correlated with the original signals are selected through the Spearman correlation coefficient and utilized for signal reconstruction, thereby filtering out high-frequency noise outside the fault frequency band in the frequency domain characterization. Secondly, the improved DRDSAE is utilized to learn the latent representations of data in the first-level denoised signal, further reducing the residual noise within the fault frequency band while retaining important signal features. Finally, the envelope spectrum highlights the weak feature of the wind turbine gearbox vibration signal. Experimental results demonstrate the effectiveness of the proposed method in denoising wind turbine gearbox vibration signals under strong noise.
Dynamically adaptive cascading updates for hierarchical digital twins
Authors: Guo Haoyu , Wang Shaoping , Shi Jian , Niu Yu , Lizzio Fausto , Guglieri Giorgio 
Published: August 2024

Abstract
Traditional sensors encounter challenges such as high collection costs, insufficient measurement points, and low data quality in the monitoring and maintenance of modern equipment. These challenges significantly affect the effectiveness and efficiency of monitoring and maintenance processes. Digital twin (DT) technology, as a digital replica of physical entities, is regarded as the ‘digital sensor’ of physical entities due to its high-precision modeling and dynamic updating capabilities. Compared to traditional sensors, DT models provide substantial improvements in both data volume and quality. However, creating a DT model with high precision and robust dynamic characteristics is notably challenging, particularly when the relationships and state features of the physical entity are complex and variable. To address this issue, a cascading update strategy was introduced. This strategy coordinates complex hierarchical DT update tasks, ensuring model accuracy. Furthermore, a signal characteristic-based dynamic adaptive update algorithm is proposed. This algorithm optimizes the DT updating process and enhances the model’s dynamic characteristics. The proposed method is validated using experimental data on plunger pump barrel-port plate oil leakage. The results demonstrate that the method significantly improves the accuracy and updating efficiency of the DT model. It achieves a balance between precision and update time costs, enhancing DTs accuracy and practicality as a ‘digital sensor’.
Projected moving patterns for reference-free background-oriented schlieren technique (BOS)
Authors: Raffel Markus , Smith Nathanial T , Wolf C Christian , Heineck James T , Gardner Anthony D 
Published: August 2024

Abstract
A background-oriented schlieren technique (BOS) using projected background patterns is presented. The projected backgrounds can be scaled to the measurement requirements, providing greater flexibility than printed backgrounds. The evaluation of the BOS image pairs using cross-correlation or optical flow analysis was demonstrated to produce equivalent results. The background pattern can dynamically be shifted by a rotating mirror, allowing evaluation using the reference-free shadowgraphy or reference-free BOS methods. The forward BOS technique is demonstrated, in which a projected speckle pattern is illuminated through a density object and recorded by a camera focused on the screen. In contrast to standard shadowgraphy, where the local image intensity is the parameter proportional the second derivative of density, this technique is robust with respect to varying lighting of the field as long as the displacement of small-scale image structures can be determined.
Nanosized-laser-induced sub-20 nm homogenous alloy nanoparticles
Authors: Zhang Chen , Wang Shu , Yang Yaqi , Jiang Chuanxiu , Liu Xinfeng , Liu Qian 
Published: August 2024

Abstract
Alloy nanoparticles (NPs) have great potential in nanosized 3D-printing, surface coating, plasmonic enhancement, information coding, and so forth. However, chemical-pollution-free and homogeneous sub-20 nm NPs maintain still a challenge in preparation. Here we present a smart nanosecond laser scan strategy of alloy-NPs preparation on a bilayer metal film by using a nanosized focused beam, successfully realizing controllable fabrication of the sub-20 nm homogeneous alloy NPs without pollution. As a demonstration, various sub-20 nm AgCu NPs with different volume ratios have been prepared, all NPs show narrow size distribution and uniform interparticle spacing. This simple and cost-effective method is stable and adaptable for other alloy-NPs such as AuAg NPs. In addition, such alloy NPs exhibit two-peak plasma resonance feature and information coding capacity. We believe that homogenous alloy sub-20 nm NPs will provide new application opportunities in many fields.
Imaging the adsorption sites of organic molecules on metallic surfaces by an adaptive tunnelling current feedback
Authors: Martin-Jimenez Daniel , Zhong Qigang , Schirmeisen André , Ebeling Daniel 
Published: August 2024

Abstract
Atomic force microscopy (AFM) allows submolecular resolution imaging of organic molecules deposited on a surface by using CO-functionalized qPlus sensors under ultrahigh vacuum and low temperature conditions. However, the experimental determination of the adsorption sites of these organic molecules requires the precise identification of the atomic structure of the surface on which they are adsorbed. Here, we develop an automation method for AFM imaging that provides in a single image both, submolecular resolution on organic molecules and atomic resolution on the surrounding metallic surface. The method is based on an adaptive tunnelling current feedback system that is regulated according to the response of the AFM observables, which guarantees that both the molecules and the surface atoms are imaged under optimum conditions. Therewith, the approach is suitable for imaging adsorption sites of several adjacent and highly mobile molecules such as 2-iodotriphenylene on Ag(111) in a single scan. The proposed method with the adaptive feedback system facilitates statistical analysis of molecular adsorption geometries and could in the future contribute to autonomous AFM imaging as it adapts the feedback parameters depending on the sample properties.
Micelles of poly[oligo(ethylene glycol) methacrylate] as delivery vehicles for zinc phthalocyanine photosensitizers
Authors: Kara Merve , Kocaaga Nagihan , Akgul Busra , Abamor Emrah S , Erdogmus Ali , Topuzogullari Murat , Acar Serap 
Published: August 2024

Abstract
Drug-loaded polymeric micelles have proven to be highly effective carrier systems for the efficient delivery of hydrophobic photosensitizers (PSs) in photodynamic therapy (PDT). This study introduces the micellization potential of poly(oligoethylene glycol methyl ether methacrylate) (pOEGMA) as a novel approach, utilizing the hydrophobic methacrylate segments of pOEGMA to interact with highly hydrophobic zinc phthalocyanine (ZnPc), thereby forming a potential micellar drug carrier system. The ZnPc molecule was synthesized from phthalonitrile derivatives and its fluorescence, photodegradation, and singlet oxygen quantum yields were determined in various solvents. In solvents such as tetrahydrofuran, dimethyl sulfoxide, and N,N-dimethylformamide, the ZnPc compound exhibited the requisite photophysical and photochemical properties for PDT applications. The pOEGMA homopolymer was synthesized via reversible addition-fragmentation chain-transfer polymerization, while ZnPc-loaded pOEGMA micelles were prepared using the nanoprecipitation method. Characterization of the pOEGMA, ZnPc, and micelles was conducted using FTIR, 1H-NMR, dynamic light scattering, matrix-assisted laser desorption/ionization time-of-flight mass spectrometries, gel permeation chromatography, and transmission electron microscopy. The critical micelle concentration was determined to be 0.027 mg ml−1 using fluorescence spectrometry. The drug loading and encapsulation efficiencies of the ZnPc-loaded micelles were calculated to be 0.67% and 0.47%, respectively. Additionally, the release performance of ZnPc from pOEGMA micelles was monitored over a period of nearly 10 d, while the lyophilized micelles exhibited stability for 3 months. Lastly, the ZnPc-loaded micelles were more biocompatible than ZnPc on L929 cell line. The results suggest that the pOEGMA homopolymer possesses the capability to micellize through its methacrylate segments when interacting with highly hydrophobic molecules, presenting a promising avenue for enhancing the delivery efficiency of hydrophobic PSs in PDT. Moreover, it was also deciphered that obtained formulations were highly biocompatible according to cytotoxicity results and could be safely employed as drug delivery systems in further applications.
How a soup bowl and a coffee cup cool down
Authors: Ferreira João Paulo M 
Published: August 2024

Abstract
The cooling of liquid foods held in plates, bowls, or cups is an event encountered several times a day. Here, it is reported a simple practical activity that demonstrates the role played by different heat transfer mechanisms in that process. The experiments can be done even at home with basic kitchenware. The demonstrations show the important role of evaporative cooling in many cases, versus convection and radiation. In this work, the applicability of Newton’s law of cooling is verified, the contributions of the different heat transfer mechanisms are quantified, and values of heat transfer coefficients are estimated. However, the data analyses and the discussions of the results can be adjusted to different audiences.
A neural network for the analysis of Langmuir-probe characteristics
Authors: Joshi-Thompson Jasmin , Ramisch Mirko 
Published: August 2024

Abstract
Langmuir probes have been widely used in the field of plasma diagnostics for the characterisation of plasma properties. These probes play a crucial role in understanding the behaviour of a diverse range of plasmas, e.g.  edge plasmas in fusion experiments. The measurement of electron density (ne
) and electron temperature (Te
) provides valuable insights into the plasma’s state, stability, and confinement properties. Conventionally, this analysis involves post-experiment fitting methods to calculate plasma properties from the measured current–voltage curves obtained from Langmuir probes. This work introduces a neural-network approach for analysing probe data from the TJ-K stellarator, allowing for fast associative plasma characterisation. The results show a reliable performance on test data within the domain of the training set, predicting both ne
and Te
within the 10 % intrinsic error. Performance on unseen data outside the domain of the training set was on average within a 26 % and 21 % error on ne
and Te
, respectively. The network’s further abilities, including the identification of low-quality and falsely-labelled data, were also explored. The use of neural networks (NNs) offers fast predictions, enabling further research into real-time applications and live feedback control. This paper highlights the promising role of NNs in enhancing the analysis of Langmuir-probe characteristics.
Investigation of high-speed superconducting electric machines through time-space extrusion numerical modelling
Authors: Zhang Hongye 
Published: August 2024

Abstract
Featured by high power density and efficiency, high temperature superconducting (HTS) electric machines provide a promising solution to heavy-duty electric transport, e.g. electric aircraft. However, designing HTS machines, particularly high-speed HTS motors, presents significant challenges: (1) modelling is highly time-consuming due to the non-linear resistivity of superconductors and complex machine topology; (2) accurately estimating the AC loss of HTS windings remains an open aspiration due to the complicated AC environment. To reduce computational complexity, the thin film approximation (only considering the approximated 1-D HTS film) for HTS coated conductors (CCs) has been widely adopted in simulations, such as the T-formulation models; however, the thin film approximation becomes inadequate for HTS CCs under high-frequency magnetic fields, as encountered in high-speed motors for aerospace. To efficiently and accurately model the AC loss of HTS windings in high-speed superconducting machines, taking a 1 MW superconducting synchronous motor with HTS armature windings as an example, this paper has adopted a time-space extrusion (TSE) method, which demonstrates a >25-fold decrease in modelling time while maintaining comparable accuracy to two benchmark H-A models. The power dissipation in both normal-conducting and superconducting layers of HTS windings has been studied, the AC losses in different turns of the armature winding have been explored, and the slot leakage field harmonics have been illustrated. Results have shown that the losses in Cu and Ag layers for high-speed HTS machines operating at cryo-temperatures (e.g. liquid hydrogen temperature) are not neglectable, especially with a high residual resistance ratio and in the presence of harmonics. The HTS armature winding should be positioned away from the iron tooth and slot opening to minimise exposure to slot leakage fields. The adopted TSE modelling strategy and drawn conclusions have provided valuable insights for the efficient design of high-speed superconducting machines.
Tighter upper bounds on the critical temperature of two-dimensional superfluids and superconductors from the BCS to the Bose regime
Authors: Shi Tingting , Zhang Wei , Sá de Melo C A R 
Published: August 2024

Abstract
We discuss standard and tighter upper bounds on the critical temperature

T
c

of two-dimensional superfluids and superconductors versus particle density n or filling factor ν for continuum and lattice systems from the Bardeen–Cooper–Schrieffer (BCS) to the Bose regime. We consider only one-band Hamiltonians, where the transition from the normal to the superfluid (superconducting) phase is governed by the Berezinskii–Kosterlitz–Thouless (BKT) mechanism of vortex-antivortex binding, such that a direct relation between the superfluid density tensor and

T
c

exists. The standard critical temperature upper bound

T
c

up
1

is obtained from the Ferrell-Glover-Tinkham sum rule for the optical conductivity, which constrains the superfluid density tensor components. We demonstrate that it is imperative to consider at least the full effect of phase fluctuations of the order parameter for superfluidity (superconductivity) and use the renormalization group to obtain the phase-fluctuation critical temperature

T
c

θ

, a much tighter bound to the critical temperature supremum than

T
c

up
1

over a wide range of densities or filling factors. We also discuss a fundamental difference between superfluids and superconductors in regards to the vortex core energy dependence on density. Going beyond phase fluctuations, we note that theories including modulus fluctuations of the order parameter or particle-hole fluctuations valid throughout the BCS-Bose evolution are still lacking, but the inclusion of these fluctuations can only produce a critical temperature that is lower than

T
c

θ

and thus produce an even tighter bound to the critical temperature supremum. We conclude by indicating that if the measured critical temperature exceeds

T
c

θ

in experiments involving two-dimensional single-band systems, then a non-BKT mechanism must be invoked to describe the superfluid (superconducting) transition.
Investigation of microstructure and mechanical properties of Al-Si alloy thin walled cylindrical part fabricated by CMT based WAAM process
Authors: Nanjundan Annamalai , Natarajan U , Simson D 
Published: August 2024

Abstract
Wire Arc Additive Manufacturing (WAAM) represents a major advancement in the production of large-scale metal components. WAAM is recognized for its capacity to produce components with enhanced material properties and structural integrity compared to conventional manufacturing processes. As WAAM involves layer-by-layer fabrication, the resulting components exhibit a higher degree of anisotropy in microstructural and mechanical properties. Additionally, the properties of WAAM components can vary significantly in terms of microstructure and mechanical performance along the build direction of the multi-layered parts. This study investigates the mechanical and microstructural properties of thin-walled cylinder made from Al-Si (Al 4043) alloy using CMT-WAAM. The analysis aims to elucidate the factors contributing to variations in these properties and provide insights into the underlying reasons for observed discrepancies. The micro hardness, tensile strength, and impact strength are analysed at both bottom and top region of the thin walled cylinder. The microhardness, tensile strength, and impact strength of the bottom region are 14.51%, 3.14%, and 12.19% less than those of the top region, respectively, due to the repeated thermal cycles during subsequent layer deposition. Fractographic analysis indicates a ductile fracture mode, characterized by the presence of dimples and microvoid coalescence. Further, the microstructural analysis reveal that top region consists fine grain compared to bottom region of thin-walled cylinder. X-ray Diffraction (XRD) analysis identified secondary phase particles, such as MgSi2 and Al9Si, at the grain boundaries, which was further confirmed by EDS analysis. These microstructural changes and the presence of secondary phases are reasons for the changes in the mechanical properties along build direction.
Q-switched pulse generation with an electro-deposited MoS2 film
Authors: Hong Lee Lian , Diblawe Abdulkadir Mukhtar , Rosol Ahmad Haziq Aiman , Tiu Zian Cheak , Arof Hamzah , Harun Sulaiman Wadi 
Published: August 2024

Abstract
We demonstrated a Q-switched erbium-doped fiber laser (EDFL) utilizing a new saturable absorber based on a MoS2 film grown on an ITO substrate via an electrodeposition process. The film was then added to an EDFL resonator to modulate the cavity loss, resulting in a Q-switched laser at 1559.4 nm with a minimum pulse duration of 4.75 μs and a maximum pulse rate of 89.9 kHz. The fundamental frequency signal-to-noise ratio was recorded at 62.28 dB, indicating the stability of the laser. This finding reveals the potential of the needle-like structure of MoS2 as a low-cost, practical, and effective saturable absorber.
QSPR analysis of drugs used for treatment of hepatitis via reduced reverse degree-based topological descriptors
Authors: Ravi Vignesh 
Published: August 2024

Abstract
Topological indices refer to numerical values that are structure-invariant and are used to quantify the bonding topology of a molecular graph. The primary objective of studying topological indices is to acquire and modify chemical structure data, thereby establishing a mathematical correlation between structures and physico-chemical properties, bio-activities, and other experimental attributes. Several studies show a high intrinsic correlation between the molecular architectures of pharmaceuticals and their boiling and melting temperatures, as well as other chemical properties. Researchers can discover more about the physical characteristics, chemical stability, and bioactivities of these chemical molecular structures by using topological indices. To compensate for the lack of chemical experiments and to give a theoretical foundation for the production of pharmaceuticals and chemical materials, topological indices on the molecular structure of chemicals/drugs are studied. This study evaluates the chemical structures of medications used to treat hepatitis (A, B, C, D, E and G) based on reduced reverse degree-based topological indices. The success of drug design is influenced by factors such as solubility, metabolic stability, toxicity, permeability, and transporter effects, which are contingent upon the physical and chemical characteristics of the medication. In recent times, computational techniques have gained prominence in the field of hepatitis medication discovery and development. Machine learning is employed by certain systems to assess the effectiveness and adverse effects of medications. The primary focus of this article is to examine the chemical applicability of ten reduced reverse degree-based descriptors in predicting the ten physico-chemical properties for the 16 drugs employed in the treatment of hepatitis.
Optimized data management with color multiplexing in QR codes
Authors: Ignacio-Cerrato Sara , Pacios David , Miguel Ezquerro Rodriguez José , Luis Vázquez-Poletti José , Estefanía Avilés Mariño María , Stavrakakis Konstantinos , Di Iorio Alessio , Schetakis Nikolaos 
Published: August 2024

Abstract
This study integrates colorimetry and computation by identifying their commonalities to develop a novel encryption system centered around color, specifically using QR codes. We propose an approach that multiplexes QR codes of varying colors, each containing distinct information. A key is generated to encapsulate user-specific data and identify the QR code with authentic information. We develop serverless architectures to facilitate rapid encryption and decryption processes. The system’s performance and efficiency are evaluated through two architectures: a sequential system implemented on Google Colab and a distributed system utilizing AWS Lambda serverless architecture. Metrics such as NPCR (Number of Pixels Change Rate), UACI (Unified Average Changing Intensity) and key space analysis, indicative of the system’s robustness, are analyzed according to existing literature. In addition, the cost of this serverless technology is evaluated in comparison to cloud and local. Our findings demonstrate that the serverless architecture offers a viable and efficient solution for coding. The implications of this research extend across various sectors, including defense, healthcare, and everyday digital interactions, presenting a scalable and secure alternative for data encryption and communication.