bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-past and past verb stems in Tangut
Authors: Beaudouin Mathieu 
Published: September 2024

Abstract
Over the past decade, the documentation of Gyalrongic languages has shed light on grammatical phenomena which were
poorly understood in Tangut, a language of critical importance in the field of Sino-Tibetan comparative linguistics. This paper
provides an explanation for the last remaining unelucidated verbal alternation in Tangut
(-ɨ1
/-i2
), which, as I will demonstrate, encodes a non-past/past
distinction. By doing so, it also gives fresh arguments for placing Tangut and the Horpa languages together within one clade.
Finally, methodologically speaking, it offers an example of grammatical reconstruction from above, i.e. employing sister languages
to better understand the grammar of an extinct language through their common ancestor, revealing a rare example of complex
distributional retention uncorrelated with regular phonetic correspondences.1
Language learning from watching cartoons in the primary EFL
classroom
Authors: Casulleras Montserrat , Miralpeix Imma 
Published: September 2024

Abstract
This chapter presents the results of a study in which two
groups of primary
school English as a Foreign Language (EFL) learners watched one
episode a week of the animated TV series Curious George –
with L1
subtitles or L2 subtitles – over a period of five months. These beginner
students were tested on comprehension and vocabulary recognition
immediately after watching each episode and in two special episodes without
subtitles (middle and end of treatment). Although significant differences
were not always present, the L1-subtitles group tended to score higher in
comprehension, and the L2-subtitles group in L2 word recognition. The
findings also emphasize the central role of language aptitude and vocabulary size for L2
learning through audiovisual materials in instructional settings.
Temperature of a steady system around a black hole
Authors: Kim Hyeong-Chan 
Published: September 2024

AbstractWe study the issue of temperature in a steady system around a black hole event horizon, contrasting it with the appearance of divergence in a thermal equilibrium system. We focus on a spherically symmetric system governed by general relativity, particularly examining the steady state with radial heat conduction. Employing an appropriate approximation, we derive exact solutions that illuminate the behaviors of number density, local temperature, and heat in the proximity of a black hole. We demonstrate that a carefully regulated heat inflow can maintain finite local temperatures at the black hole event horizon, even without considering the back-reaction of matter. This discovery challenges conventional expectations that the local temperature near the event horizon diverges in scenarios of thermal equilibrium. This implications shows that there’s an intricate connection between heat and gravity in the realm of black hole thermodynamics.
Dark matter and dark energy in combinatorial quantum gravity
Authors: Trugenberger C A 
Published: September 2024

Abstract
We point out that dark matter and dark energy arise naturally in a recently proposed model of combinatorial quantum gravity. Dark energy is due to the ground-state curvature at finite coupling, dark matter arises from allotropy in the discrete structure of space-time. The stable structure of the space-time ‘crystal’ represents the curved background, the coexisting metastable allotropes of higher curvature and energy are natural candidates for dark matter. We thus suggest that dark energy and dark matter are two manifestation of quantum gravity.
Boosting gravitational waves: a review of kinematic effects on amplitude, polarization, frequency and energy density
Authors: Cusin Giulia , Pitrou Cyril , Bonvin Camille , Barrau Aurélien , Martineau Killian 
Published: September 2024

AbstractWe review the kinematic effects on a gravitational wave due to either a peculiar motion of the astrophysical source emitting it or a local motion of the observer. Working in the context of general relativity, we show at fully non-linear order in velocity, that the amplitude of the wave is amplified by the Doppler factor in the case in which the source moves with respect to a reference frame, while it is invariant if the observer moves (with respect to a reference observer). However, the observed specific intensity transforms in the same way under a boost of the source or of the observer. We also show at fully non-linear order that under a boost (of either source or observer), the polarization tensor is rotated in the same way the wave direction is rotated by aberration, such that the only net effect of a boost on polarization is to change the phase of the helicity components. We apply these results to a wave emitted by a binary system of compact objects in the cosmological context.
Plasma synthesis of Pt/C catalysts and their electrocatalytic performance
Authors: Zhu Xiangmiao , Zhang Xu , Tao Yunming , Wang Wei , Wang Cong , Zhang Shiru , Shen Jie , Starostin Sergey A , Lin Liangliang 
Published: September 2024

Abstract
A simple, green, and scalable approach, utilizing dielectric barrier discharge (DBD) plasma in lieu of chemical reductants, is presented for producing Pt/C catalysts. The results revealed crystalline well-dispersed Pt nanoparticles of small sizes were generated on the surface of carbon support, where the Pt loading can be regulated by adjusting the H2PtCl6 concentration. The resulting Pt/C catalysts demonstrated excellent catalytic activity in both acidic and alkaline electrolytes for hydrogen evolution reactions (HER) and methanol oxidation reactions (MOR). With the rise of the Pt loading, the catalytic activity gradually improves. Specifically, for HER, an overpotential value of 120 mV was measured for the 8 wt% Pt/C-modified electrode at a geometric current density of −10 mA cm−2, with a Tafel slope of 45.4 mV dec−1 in acidic electrolyte. The values became 208 mV and 83.7 mV dec−1 in alkaline electrolyte. Same phenomenon was also observed in MOR, where the increase of the Pt loading results in faster electron transport rate and stronger methanol oxidation peak. Besides, the catalytic activity of the plasma-prepared Pt/C catalysts is better than the commercial samples with the same Pt loading. This work demonstrates a DBD plasma-assisted strategy for the preparation of Pt/C catalysts in an efficient and environmentally friendly manner.
Brain-inspired computing with self-assembled networks of nano-objects
Authors: Vahl Alexander , Milano Gianluca , Kuncic Zdenka , Brown Simon A , Milani Paolo 
Published: September 2024

Abstract
Major efforts to reproduce functionalities and energy efficiency of the brain have been focused on the development of artificial neuromorphic systems based on crossbar arrays of memristive devices fabricated by top-down lithographic technologies. Although very powerful, this approach does not emulate the topology and the emergent behavior of biological neuronal circuits, where the principle of self-organization regulates both structure and function. In materia computing has been proposed as an alternative exploiting the complexity and collective phenomena originating from various classes of physical substrates composed of a large number of non-linear nanoscale junctions. Systems obtained by the self-assembling of nano-objects like nanoparticles and nanowires show spatio-temporal correlations in their electrical activity and functional synaptic connectivity with nonlinear dynamics. The development of design-less networks offers powerful brain-inspired computing capabilities and the possibility of investigating critical dynamics in complex adaptive systems. Here we review and discuss the relevant aspects concerning the fabrication, characterization, modeling, and implementation of networks of nanostructures for data processing and computing applications. Different nanoscale electrical conduction mechanisms and their influence on the meso- and macroscopic functional properties of the systems are considered. Criticality, avalanche effects, edge-of-chaos, emergent behavior, synaptic functionalities are discussed in detail together with applications for unconventional computing. Finally, we discuss the challenges related to the integration of nanostructured networks and with standard microelectronics architectures.
Experimental progress in Eu(Al,Ga)4 topological antiferromagnets
Authors: Shang Tian , Xu Yang , Gao Shang , Yang Run , Shiroka Toni , Shi Ming 
Published: September 2024

Abstract
The non-trivial magnetic and electronic phases occurring in topological magnets are often entangled, thus leading to a variety of exotic physical properties. Recently, the BaAl4-type compounds have been extensively investigated to elucidate the topological features appearing in their real- and momentum spaces. In particular, the topological Hall effect and the spin textures, typical of the centrosymmetric Eu(Al,Ga)4 family, have stimulated extensive experimental and theoretical research. In this topical review, we discuss the latest findings on the Eu(Al,Ga)4 topological antiferromagnets and related materials, arising from a wide range of experimental techniques. We show that Eu(Al,Ga)4 represents a suitable platform to explore the interplay between lattice-, charge-, and spin degrees of freedom, and associated emergent phenomena. Finally, we address some key questions open to future investigation.
Freezing of short-range ordered antiferromagnetic clusters in the CrFeTi2O7 system
Authors: Kumar Arun , Panja Soumendra Nath , Keller Lukas , Nair Sunil 
Published: September 2024

Abstract
We report on the CrFeTi2O7 (CFTO) system using a combination of x-ray diffraction, dc magnetization, ac susceptibility, specific heat and neutron diffraction measurements. CFTO is seen to crystallize in a monoclinic P21
/a symmetry. It shows a glassy freezing at T
f∼22 K, characterized by the observation of bifurcation between ZFC and FC χ (T) curves, frequency dispersion across T
f in ac susceptibility, and follows Vogel–Fulcher and power law type critical dynamics, very slow relaxation of iso-thermal remanent magnetization with time and a linear temperature dependence of magnetic contribution to specific heat C
m below T
f. The microscopic neutron diffraction analysis of CFTO not only confirms the absence of long-range antiferromagnetic (AFM) ordering but also exhibits diffuse scattering due to the presence of short-range ordered AFM correlated spin clusters.
Elucidating correlation-driven insulating state in an effective spin—½ antiferromagnet NdVO4
Authors: Ranaut Dheeraj , Sihi Antik , Saravanan M P , Deepshikha Jaiswal-Nagar , Mukherjee K 
Published: September 2024

Abstract
The J
eff = ½ state: a result of interplay of strong electronic correlations (U) with spin–orbit coupling (SOC) and crystal field splitting, offers a platform in the research of quantum materials. In this context, 4f rare-earth based materials offer a fertile playground. Here, strong experimental and theoretical evidences for a J
eff = ½ state is established in a three-dimensional spin system NdVO4. Magnetic measurements show the signatures of a SOC driven J
eff = ½ state along with the presence of antiferromagnetic (AFM) interaction between Nd3+ moments, whereas, heat capacity reveals the presence of an AFM ordering around 0.8 K, within this state. An entropy of Rln2 (equivalent to J = ½) is released around 4 K which implies the presence of J
eff = ½ state at low temperatures. Total energy calculations within the density functional theory (DFT) framework reflect the central role of SOC in driving the Nd3+ ions to host such a state with AFM correlations between them, which is in agreement with experimental results. Further, DFT + SOC calculations with and without the inclusion of U, points that electron–electron correlations give rise to the insulating state making NdVO4 a potential candidate for U-driven correlated Mott insulator.
An optimal goose lithium-ion batteries accurate and rapid RUL prediction method with automatic initial hyperparameters settings
Authors: Li Gang , Huang Yiyi , Sun Caitang , Pang Ying 
Published: September 2024

Abstract
Machine learning has emerged as a highly effective tool for addressing complex data problems, garnering significant attention in the field of equipment degradation and remaining service life prediction. Existing prediction models typically exhibit two primary shortcomings: on the one hand, the accuracy of life prediction reaches the desired level of precision while failing to achieve a sufficiently fast prediction speed, and on the other hand, generalization is not guaranteed while requiring the model to be robust. These two aspects present a significant challenge to the field of machine learning. In light of the aforementioned issues, we propose a prediction model based on the goose algorithm. Initially, we set the goose algorithm using adaptive initialization of the goose population to guarantee that the goose population is set at the appropriate interval, and we incorporate it into the extreme learning machine model through the improved goose algorithm. goose algorithm is used to predict the service life. Finally, we utilize different types of lithium batteries with varying operational conditions to conduct pertinent case studies to validate the proposed prediction model. The results demonstrated that the average accuracy was above 98% in all validated datasets. The shortest computation time was 0.19 s.
A composite power quality disturbance detection method based on extremum extension optimized SVMD and Teager Energy Operator
Authors: Xiang Wu , Anqi Jiang , Shuqing Zhang , Haitao Liu , Shanshan Song 
Published: September 2024

Abstract
The growth of nonlinear loads and distributed generation in power grids has increased the frequency and complexity of power quality disturbances (PQDs). To improve PQ, it is necessary to accurately detect disturbance parameters, identify the causes of disturbances, and formulate corresponding management measures. Traditional disturbance detection methods primarily target single disturbances. As a contribution to complex disturbances, this paper proposes a composite PQD detection method based on extremum extension successive variational mode decomposition and Teager Energy Operator (EE-SVMD-TEO). Briefly, the SVMD method is utilized to decompose PQD signals. This method is further improved using an EE approach to reduce the influence of endpoint effects. Subsequently, the TEO is applied to the disturbance components obtained from the SVMD for disturbance detection. The results from composite disturbance detection simulation experiments show that the proposed method can differentiate disturbances in composite PQD signals. Combined with TEO, it successfully recognizes the start and end times of each disturbance, achieving a detection accuracy of over 97.5% at a signal-to-noise ratio of 30 dB Gaussian white noise. By comparing the modal decomposition results, the detection accuracy of disturbance time points, and the detection result stability, our method is more suitable for detecting composite PQD events than EEMD-TEO and EWT-TEO.
Temperature compensation method for impedance signals of bolt loosening under temperature varying conditions using TransUnet
Authors: Huang Xin , Qu Wenzhong , Xiao Li 
Published: September 2024

Abstract
Piezoelectric transducer based electro-mechanical impedance technology is an effective and reliable detection method for bolt structure loosening under external load. However, temperature change usually causes some non-loosening factors to change the impedance spectrum of bolt structure. In order to reduce the misjudgment of loosening damage caused by temperature change, it is necessary to construct a temperature compensation model for impedance spectrum. In this paper, the convolutional structure in U-net and Transformer are effectively combined to form a TransUnet deep neural network structure suitable for input and output of one-dimensional data. Using impedance data between 10 °C and 50 °C and temperature as input to the network. After convolution operation, the convolutional block attention module is embedded in the U-net to optimize the encoder transmission characteristics and enhance the performance of the skip connection in the traditional U-shaped structure. The temperature compensation rate (TCR) is defined to measure the effect of temperature compensation. Then the lightweight convolutional neural network structure is used to recognize the bolt loosening damage of the compensated impedance signal. The generalization ability of the TransUnet was tested using impedance data that is not in the training dataset. The results show that the TransUnet proposed in the paper can realize the temperature compensation of multi-peak impedance signals. The TCR and recognition accuracy of bolt loose damage reaches reach 0.003 and 95.7%, respectively, which is 11% higher than that without temperature compensation. At 60 °C, the TCR and the identification accuracy of loosening damage can still reach 0.0055 and 90.2%, respectively, which show that the TransUnet has strong generalization ability.
Core-shell architecture and channel suppression: unleashing the potential of SC_RCS_DGJLFET
Authors: Himral Atul , Sharma Rajneesh , Agarwal Mohit 
Published: September 2024

Abstract
In this investigation, a suppressed channel-rectangular core–shell double gate junctionless field effect transistor (SC_RCS_DGJLFET) is simulated to enhance the junctionless device’s performance. This study leverages a core–shell architecture and channel suppression technique to improve the gate controllability over the channel region which helps in substantial depletion of the shells in the OFF state of the device. When compared to conventional double gate JLFETs (C_DGJLFET) and rectangular core–shell double gate JLFETs (RCS_DGJLFET), the performance of the SC_RCS_DGJLFET is superior in terms of IOFF, ION/IOFF ratio, DIBL and subthreshold slope (SS). The SC_RCS_DGJLFET achieves an ultra-low IOFF of 7.033 × 10−16 A, indicating a low leakage current with an impressive ION/IOFF = 5.092 × 1011 . Other performance parameters such as subthreshold slope and DIBL has also been improved for the SC_RCS_DGJLFET device. Subthreshold slope has been decresesd by 4.76% whereas the DIBL decreased by 33.82% when compared to existing RCS_DGJLFET. Additionally, to analyze the effect of doping on the device performance, the core doping in SC_RCS_DGJLFET is varied for fixed shell doping. The study found that fixing core doping to an appropriate value is a crucial parameter to achieve good device performance. The impact of variation of oxide extension towards the source and drain LextS/LextD in SC_RCS_DGJLFET is also studied for the first time in the core–shell architecture which has further improved the device’s performance. Finally, a CMOS inverter is designed using the proposed device that provides valuable insights into its suitability for digital circuit applications and verifies its performance benefits compared to existing transistor technologies. The SC_RCS_DGJLFET based CMOS inverter shows a sharp transition in voltage transfer characteristics (VTC), indicating fast switching speed and precise signal processing capabilities when compared to a CMOS inverter based on a conventional double gate junctionless field effect transistor (C_DGJLFET). Moreover, the transient characteristics of the SC_RCS_DGJLFET based CMOS inverter exhibit an improved output voltage swing, suggesting enhanced dynamic behaviour and stability during logic state transitions.
An exploration of enhanced characteristics and efficiency of dye-doped L-Threonine single crystal
Authors: Lakshmi S , Saravanan M 
Published: September 2024

Abstract
The improved crystalline characteristics of a crystal doped with 0.5 mol% methylene blue dye was analyzed and compared using several techniques such as SXRD, FTIR, (Spectrum of absorption and Spectrum of optical transmittance), PXRD, and Second Harmonic Generation (SHG). The crystal was prepared using the slow evaporation method. The work hardening coefficient was evaluated for our synthesized crystal, indicating its soft nature. Additionally, we want to achieve similar levels of second harmonic Generation in both pure L-threonine materials and dye-doped crystals. Research on photoluminescence reveals that fully developed crystals have a reduced number of imperfections. Piezoelectric coefficients (d33) were also calculated for the as- grown Pure L-threonine crystal and L-threonine doped with dye Single crystal. The increased LDT value be attributed to the significantly decreased section, confinement, and mechanical stiffness of both the Pure L-threonine and dye-doped L-threonine Single crystal. The etching tests shown that both the as-grown Pure L-threonine crystal and the dye-doped L-threonine Single crystal had a better level of crystalline fineness and a smaller number of defects. These characteristics are essential for their use in nonlinear optics (NLO) applications.
Optimizing deposition parameters and characterizing TiO2 thin films for future memristor applications
Authors: Shivaram Shilpa , Paul Done Rinshun , S K Suresh Babu , B Vigneshwaran , V Haritha Sree , J Roshan Johns , D Nirmal 
Published: September 2024

Abstract
Titanium dioxide (TiO2) thin films were deposited on glass substrates using Spray Pyrolysis technique, with variations in multiple deposition parameters. The molarity of the precursor was altered within a small range from 0.09 M–0.15 M. The deposition temperature was systematically adjusted from 200 °C to 400 °C while the ratio between precursor and chelating agent varied between 1:1,1:2 and 1:3. The thickness of TiO2 films were found to be in the range of 216 nm to 14.9 μm. Structural analysis conducted by XRD confirmed the formation of anatase TiO2 thin films. Optical studies using UV-Visible spectrophotometer determined the absorption and indirect bandgap ranging from 299 nm to 326 nm and 3.08 eV to 3.44 eV respectively. Electrical studies carried out evaluated the leakage currents and DC resistivity for all individual films with the input voltage applied from ± 0.5 V to ± 5V. Impedance studies were conducted by varying input voltages from 0.2V–3V for each film, so as to examine the resultant impedance, dielectric constant, dielectric loss, conductivity, admittance and modulus spectra. The obtained results were analysed to optimise the deposition parameters for designing future memristors with specific individual or combined characteristics, such as high ON/OFF, switching speed, endurance and retention.