bluuebunny/crossref_metadata_2025 huggingface dataset:
Wetting behaviour of mixed surfactants on the mild steel surface
Authors: Yadav Chandradip Kumar , Subedi Vivek , Mukherjee Monami , Khadka Sita , Karn Anoop , Niraula Tulasi Prasad , Yadav Amar Prasad , Bhattarai Jagadeesh , Bhattarai Ajaya
Published: January 2025

Interfacial phenomena such as wetting can be enhanced to a greater extent and mixed surfactant systems are promising candidates for the improvement of wettability of hydrophobic surfaces. In this study, the investigation sought to examine the surface-wetting characteristics of mild steel utilizing a blend of the cationic surfactant cetylpyridinium chloride (CPC) and the anionic surfactant sodium dodecyl sulfate (SDS). The wetting behaviour of mild steel surface is quantified in terms of contact angle corresponding to H2SO4, mixed surfactant acid solutions, and methanol for three hours. The contact angles of 0.0008 M, 0.0017 M, and 0.00034 M of mixed surfactant on polished mild steel solution were found to be 38.62°, 39.73°, and 48.50° respectively. The contact angle increases proportionally with the concentration of mixed surfactant in the solution, leading to a visible increase in its hydrophilic nature. On polished mild steel, contact angles of 0%, 10%, 20%, and 30% methanol were measured at 98.21°, 100.39°, 105.29°, and 109.37°, respectively. It shows that the hydrophobic nature increased with an increase in concentration of methanol resulting in less interaction between metal substrate and corrosive species.
Using checklist and what if analysis for inspection fire pump room at the Faculty of Applied Science Building, KMUTNB
Authors: Nakkam Teravuti , Piyamongkala Kowit
Published: January 2025

The inspection and analysis of the qualitative for the fire protection system of the Faculty of Applied Science Building at King Mongkut’s University of Technology North Bangkok (KMUTNB) was surveyed by a standard checklist. Using the method of consideration according to the Regulations of the Building Control Act, the investigation examined six items of the fire pump room. Then, the risk assessment was observed by a what-if analysis. There were two non-critical items that should be improved including emergency lights and smoke detectors. Therefore, the fire protection system in the Faculty of Applied Sciences Building KMUTNB is ready to operate in the event of a cause of fire because the basic equipment have been estimated to be sufficient to use and in a state of high readiness.
Application Research of Cross-Attention Mechanism for Traffic Prediction Based on Heterogeneous Data
Authors: Feng Zhihao
Published: January 2025

Intelligent transportation systems need to be developed with precise traffic flow predictions to reduce traffic accidents, improve overall urban mobility, and mitigate congestion. The intricacy and variety of traffic conditions are often too complex and variable for traditional approaches to handling, especially when dealing with heterogeneous event data from several sources like weather variations and traffic incidents. This review highlights the significance of cross-attention mechanisms by examining the developments in integrating multi-source heterogeneous event data for traffic prediction. Examining different approaches used in previous work, the study focuses on the Event-aware Graph Attention Fusion Network (EGAF-Net). This cutting-edge model efficiently integrates and analyzes complex spatial-temporal data. Through an analysis of these methods, the research demonstrates how applying advanced deep learning algorithms and cross-attention processes has significantly improved prediction robustness and accuracy. The results underscore the critical role of heterogeneous data integration in enhancing traffic prediction models, providing insights into current challenges and potential future developments in the field. This thorough analysis aims to direct future research endeavors and open the door for more dependable and effective intelligent transportation systems.
The Relationship Between Traffic Flow Forecasting and Traffic Accident Forecasting and the Possible Combination Points
Authors: Wu Haoyu
Published: January 2025

This paper mainly studies the relationship between traffic flow forecasting and traffic accident forecasting and the possible combination points. Firstly, through the introduction of the background, the necessity of combining the two is analyzed. Secondly, the differences between neural networks and traditional machine learning are compared in terms of model structure, feature extraction, applicability, computational resources and time, and model complexity'. This paper emphasizes the importance of neural networks for traffic flow forecasting and traffic accident forecasting and introduces the commonly used neural networks. Then, the concept of temporal and spatial characteristics in traffic data is expounded, which opens the relationship between traffic flow forecasting and traffic accident forecasting and the analysis of possible combination points. Through the analysis of the existing research, it is found that the relationship between the two is mainly divided mto data complementarity, common goal, and common method, and the possible combination points of the two are analyzed and prospected. Finally, the data and methods of improving traffic flow forecasting are summarized, which is conducive to better traffic flow forecasting and the combination of the two.
Machine Learning-Based Network Detection Research for SDNs
Authors: Lai Jiayue
Published: January 2025

This research endeavors to fortify the security posture of Software-Defined Networks (SDN) through the strategic utilization of intelligent machine learning techniques, with a primary focus on mitigating detrimental Denial of Service (DoS) attacks. To accomplish this, this study constructed a rigorously designed simulated SDN environment, which served as the cornerstone for meticulously assembling a comprehensive dataset encompassing a diverse array of attack vectors, with particular emphasis on DoS. Employing a tactical blend of established and cutting-edge machine learning algorithms, including Random Forest, Logistic Regression, and Decision Tree, alongside the advanced XGBoost and LightGBM models, this study conducted an exhaustive investigation to pinpoint the most efficacious methods for swiftly and precisely identifying DoS threats. It is necessary to note that XGBoost and LightGBM demonstrate an astonishing level of multiple performance, which testifies their outstanding ability to enhance SDN security. Reasserting the idea of the critically important role of machine learning for securing SDNs against possible intrusions, these results point not only to the highly beneficial applications of machine learning for protecting SDNs against malicious intrusions but also its indispensable role in preserving network stability and optimizing performance. Moreover, it emphasizes the operational advantage of deploying multiple organic sets of machine learning algorithms, which can achieve even greater precision and efficiency than individual machine learning algorithms in practical uses, bringing it closer to developing a more robust and secure SDN environment.
Research on Sarcastic Emotion Recognition Based on Multiple Feature Fusion
Authors: Si Kaihao
Published: January 2025

Sarcasm detection significantly enhances the performance of various natural language processing applications, such as sentiment analysis, opinion mining, and stance detection. Despite considerable advancements in this field, research results remain fragmented across diverse datasets and studies. This paper offers a critical review of two predominant models in sarcasm detection. The first model utilizes BERT within an intermediate task transfer learning framework, leveraging the connection between sarcasm and underlying negative emotions and sentiments. This model enhances the sarcasm detection capability through a strategic knowledge infusion into the transfer learning process. The second model reviewed deploys a multi-head attention-based bidirectional LSTM architecture. This approach incorporates pre-trained word embeddings, multi-head attention mechanisms, and custom-crafted features to proficiently identify sarcasm in social media datasets. Comparative assessments on standard datasets reveal that both models achieve superior performance over many existing approaches in the field. At last, this paper explores the direction for future improvement based on the conclusions.
Human Pose Estimation: Single-Person and Multi-Person Approaches
Authors: Tang Wan
Published: January 2025

Human pose estimation (HPE), as one of the core tasks in computer vision, plays a crucial role in enabling computers to comprehend human behaviour interactions. With the advancement of technology, this task has demonstrated significant potential in various application areas such as motion capture, behavior analysis and augmented reality. Despite significant progress in recent years, HPE still presents challenges when dealing with complex scenarios such as occlusion, illumination changes, and dynamic backgrounds. This paper will provide a comprehensive overview of HPE techniques, focusing on both single-person and multi-person poses. According to their respective characteristics and application scenarios, single-person pose estimation is categorized into traditional methods and deep learning methods, while multi-person pose estimation is classified into top-down and bottom-up aspects. In addition, this paper analyzes commonly used datasets relevant to HPE, discusses the current unsolved issues, and forecasts future research directions, with the aim of providing valuable references and guidance for subsequent research in this field.
Advancements and Challenges in Character Recognition: A Comparative Analysis of CNN and Deep Learning Approaches
Authors: Yang Ximin
Published: January 2025

This paper provides a comprehensive review of character recognition technologies, focusing on the application of Convolutional Neural Networks (CNN) and deep learning methodologies. Through an analysis of three key studies, the research highlights the strengths and limitations of current approaches. Study by Zib emphasizes the challenges in segmenting and recognizing English characters using CNN, revealing the need for supplementary techniques to mitigate errors. Research by Nikitha explores the impact of increasing the dimensionality of analysis, demonstrating that higher dimensions improve accuracy but also extend training times. Similarly, work conducted by Pradeep shows that larger vector sizes enhance recognition accuracy but at the cost of greater computational resources. The collective findings suggest that while CNN and deep learning models have significantly advanced character recognition, there remains a need for enhanced segmentation techniques and a balanced approach to optimizing training efficiency and accuracy. Future research should focus on integrating supportive methods to improve segmentation and finding an optimal trade-off between variable complexity and computational efficiency, thereby advancing the practical application of character recognition systems across various domains.
A Study of the Usage of Artificial Intelligence in Scientific Research and Education
Authors: Peng Ruisen
Published: January 2025

Nowadays, the speed of spearing of artificial intelligence is getting faster. Likely commercialization can make people’s lives more convenient, if scientific research gets help from artificial intelligence, the efficiency of scientific research will significantly increase. Tliis paper shows a general situation of the usage of artificial intelligence hi scientific research and education. By combining the essential information from recent papers about tliis field, this paper analyses the crucial problem scientists face and the general solving method. Ilie mam problems are the randomness and the nature of Blackbox, and the general solving method is to add a part of the model to let the model “understand” the principles and theorems that are in the field. Also, the paper generates a general situation of the usage of artificial intelligence hi education, which is speaking out at an increasing speed. The paper is a conclusion of the situation that the character of artificial intelligence hi scientific research and education. Tliis paper expects to offer a clear cognition and deep understanding about this field.
Comparisons of Machine Learning Models for Prediction of Susceptibility to Diabetes
Authors: Jiao Yutian
Published: January 2025

Diabetes is a chronic disorder causing millions of people to suffer from severe complications such as heart attacks, kidney failures, and permanent vision loss. This study aims to find an optimal choice among the five selected models that perform the best on diabetes prediction, and thus provide valuable insights in early detection of diabetes. This study compares the predictive performance of machine learning models such as Random Forest (RF), Logistic Regression (LR), and Support Vector Machine (SVM). The study preprocessed the Pima Indians Diabetes (PID) dataset, and the models were trained on it before being assessed using four assessment criteria. According to the results, LR had the best accuracy of 0.76, with RF and SVM coming in second and third, respectively. Results showed that LR achieved the highest accuracy of 0.76, closely followed by RF and SVM. While SVM has the highest precision, it performs poorly on recall, limiting its overall performance on diabetes prediction. On the contrary, LR and RF achieved good results in the F-score, making them outperform the other models in terms of overall performance score in predicting diabetes.
Research on the Application of Deep Learning Methods in the Field of Image Classification
Authors: Peng Yuhui
Published: January 2025

With the rapid development of image classification technology, it has become a current research hotspot to apply image classification technology to various fields and to improve the accuracy and efficiency of image classification technology in various fields. In the field of fruit classification and textile, the application of image classification technology has been widely concerned. This paper reviews the current research status of image classification models, focusing on the application of DenseNet-201, Xception, MobileNetV3-Small and ResNet-50 models in the fruit field. The application of deep learning methods such as Convolutional Neural Network, Recurrent Neural Networks and Long Short-Term Memory in image classification is also discussed. In this paper, it is concluded that these models have achieved high accuracy in fruit classification and the textile field, especially the combination of CNN, RNN and LSTM deep learning methods for feature fusion can enhance the accuracy and robustness of the model. In addition, this paper also discusses the limitations of the current research and makes some suggestion.
Increase in Maximum Sustainable Yield in Multi-patch Rosenzweig-Macarthur predator-prey model
Authors: Moussaoui Ali , Auger Pierre , Elbetch Bilal
Published: January 2025

In this paper, we formulate a Rosenzweig-MacArthur (RM) predator–prey model incorporating the dispersal of both prey and predator among n discrete habitat patches. We assume that only the predator is harvested and not its prey, growing logistically on each site. Our aim is to investigate whether the total catch in a system of interconnected patches through migration can surpass the sum of the optimal catch from n isolated patches, known as the maximum sustainable yield (MSY). We start by revisiting some fundamental properties of the RM model examining the stability of its equilibrium points. We then analyze the MSY for a single patch, deriving conditions on the fishing effort required to achieve MSY. Next, we consider the MSY of the RM model for both separated and connected patches, and provide different answers to the aforementioned question for different cases. In the homogeneous case with symmetric movement between patches, we show that the total yield at MSY for the interconnected system is equivalent to the sum of the yields at MSY for each isolated patch. In the heterogeneous case, we show that the total MSY for the connected patches can surpass the sum of the MSY for each isolated patch.
Cardiac Radiomics Analyses in Times of Photon-counting Computed Tomography for Personalized Risk Stratification in the Present and in the Future
Authors: Ayx Isabelle , Bauer Rouven , Schönberg Stefan O , Hertel Alexander
Published: January 2025

The need for effective early detection and optimal therapy monitoring of cardiovascular diseases as the leading cause of death has led to an adaptation of the guidelines with a focus on cardiac computed tomography (CCTA) in patients with a low to intermediate risk of coronary heart disease (CHD). In particular, the introduction of photon-counting computed tomography (PCCT) in CT diagnostics promises significant advances through higher temporal and spatial resolution, and also enables advanced texture analysis, known as radiomics analysis. Originally developed in oncological imaging, radiomics analysis is increasingly being used in cardiac imaging and research. The aim is to generate imaging biomarkers that improve the early detection of cardiovascular diseases and therapy monitoring.

The present study summarizes the current developments in cardiac CT texture analysis with a particular focus on evaluations of PCCT data sets in different regions, including the myocardium, coronary plaques, and pericoronary/epicardial fat tissue.

These developments could revolutionize the diagnosis and treatment of cardiovascular diseases and significantly improve patient prognoses worldwide. The aim of this review article is to shed light on the current state of radiomics research in cardiovascular imaging and to identify opportunities for establishing it in clinical routine in the future.
Phenomenological theory of superconductivity with spatial symmetry of superconductors
Authors: Poluektov Yu. M.
Published: January 2025

The phenomenological approach to the theory of superconductivity is generalized by taking into account the spatial symmetry of crystalline superconductors. Such a generalization makes it possible to analyze superconducting transitions in which violation of translation symmetry is possible in the density distribution of superconducting electrons along with the change in the rotational symmetry for a constant symmetry of crystal lattice. The technique proposed for determining basis functions of irreducible representations of the space group takes into account the distributions of the centers of mass of Cooper pairs over the crystal as well as the intrinsic symmetry of pairs. The general form obtained for the thermodynamic potential of the superconductor is invariant to the space group symmetry of the normal state. It is shown that a modulated superconducting structure can exist under certain conditions in the presence of terms in the thermodynamic potential of the superconductor, which are linear in the gradients of the order parameter.
Irreversibility curve and dissipative losses in YBaCO films
Authors: Khokhlov V. A. , Drobot’ko V. F.
Published: January 2025

The susceptibility of polycrystalline and epitaxial YBCO films in weak exciting magnetic fields Hac = (0.1–1000) mOe is investigated by using the inductive technique. The behavior of their irreversibility curves (1-Tm/Tc) and the peak of dissipative losses is studied. Two characteristic fields H1* and H2* are observed for which the curves (1-Tm/Tc)(Hac) and χm″(Hac) change their slope. It is shown that the exponent in the equation (1-Tm/Tc)= αHacq depends on the type of weak bonds formed in the film during its growth.
On the theory of high-frequency properties of a ferromagnetoelectric with an “unfrozen” orbital moment
Authors: Chupis I. E. , Govorun A. B.
Published: January 2025

Elementary excitations of an axial ferromagnetoelectric with a weakly “unfrozen” orbital magnetic moment are considered. The magnetic subsystem is described by two moments, viz., the spin and orbital magnetic moment of an ion, which are coupled through a weak spin-orbit interaction. The spectrum of magnetic and ferroelectric excitations is determined in magnetic fields parallel and perpendicular to the easy axis. It is shown that different dependences of the spin and orbital magnetic moments on the magnetic field perpendicular to spontaneous magnetization lead to crossover of the spin and orbital branches and to a gap in the ferromagnetic resonance spectrum. The contribution of orbital excitations to the total magnetic moment is calculated; this contribution has a temperature dependence differing from that for contribution of spin waves. The obtained results are also applicable to a system with two groups of magnetic ions with magnetic moments of the first group of purely spin origin and of the second group of spin and orbital origin. In this case, the weak interaction between the magnetic moments of these groups is of the exchange type and not of the spin-orbit type.
Dynamics of vortex ensemble in high-anisotropy planar ferromagnets with spin s=1
Authors: Ivanov B. A. , Sheka D. D.
Published: January 2025

The dynamics of an intraplanar vortex in a strongly anisotropic planar ferromagnet (PFM) with spin s = 1 and strong effects of quantum spin contraction in an applied magnetic field H perpendicular to the easy plane is considered. The structure, dynamics, and relaxation of such vortices are discussed. Effective equations of motion are constructed for the coordinates of vortices in the ensemble of interacting vortices existing in the PFM above the topological phase transition point. The root-mean-square velocity of vortices is calculated as well as the components of the PFM dynamic structural factor in the presence of a magnetic field.
Jahn–Teller ordering in the Ising magnet KEr(MoO4)2 induced by an external magnetic field
Authors: Kut’ko V. I. , Kobets M. I. , Pashchenko V. A. , Khats’ko E. N.
Published: January 2025

The EPR spectra of the Ising magnet KEr(MoO4)2 are studied in the frequency interval 18−30 GHz at temperatures 1.8−4.2 K. Measurement of the angular dependence of the EPR spectrum has led to the detection and investigation of the first-order structural phase transition induced in the paramagnet by an external magnetic field. The critical temperature and field corresponding to the phase transition are estimated. A plausible microscopic model of the cooperative Jahn–Teller effect is proposed to explain the observed transition.
Persistent currents in one-dimensional systems of strongly correlated electrons (review)
Authors: Zvyagin A. A. , Krive I. V.
Published: January 2025

Charge persistent currents in single-channel ballistic rings are investigated in various models of strongly correlated electrons (Wigner crystal, Luttinger liquid, Hubbard model, t–J model, and the fermion representation of the Heisenberg–Ising model). The primary objective of the survey is to compare the properties of Aharonov–Bohm oscillations for weakly and strongly correlated electrons and to formulate a set of persistent current characteristics that will unambiguously support the anomalous (departing from a Fermi liquid) behavior of one-dimensional electron systems. For this purpose the onset of the parity effect (dependence of the system response on whether the number of particles in the ring is odd or even) and various properties of the persistent current are analyzed in detail for model spinless fermions and real electrons. The influence of solitary impurities on the value and temperature dependence of the amplitude of the Aharanov–Bohm oscillations is also investigated. It is shown that the formation of a Wigner crystal (which is possible for weakly shielded Coulomb interaction) leads to a very pronounced anomalous (nonmonotonic) temperature dependence of the current in a nonideal ring. The properties of the charge current near the Mott metal–insulator transition are altered to the greatest degree by local types of electron–electron interaction.
Influence of a neon impurity at concentrations exceeding maximum miscibility on the thermal conductivity of solid parahydrogen
Authors: Gorodilov B. Ya. , Krivchikov A. I. , Manzheliĭ V. G. , Zholonko N. N. , Korolyuk O. A.
Published: January 2025

The thermal conductivity of solid mixtures of Ne in p-H2 is investigated at Ne concentrations of 1 · 10−3–1.3· 10−2 in the temperature interval 1.5–8 K. The thermal conductivity is observed to increase with increasing Ne concentration for crystals obtained by condensation from the gaseous phase. The annealing of samples in the premelting range lowers the thermal conductivity relative to its value of unannealed crystals obtained from the gaseous phase. The thermal conductivity of solid mixtures obtained by crystallization from the liquid phase is found to be lower than that of annealed and unannealed samples obtained from the gaseous phase. A qualitative explanation is proposed for the unusual behavior of the thermal conductivity of solid p-H2 mixtures with Ne concentrations above 1 · 10−4.
Phenomenological relativistic theory of superfluidity for systems with two types of condensates
Authors: Vil’chinskiĭ S. I. , Fomin P. I.
Published: January 2025

Equations are derived phenomenologically for the relativistic theory of superfluidity with two types of condensates in the nondissipative approximation. Three-velocity relativistic thermodynamics and hydrodynamics are deduced from the conditions of consistency of the conservation laws for energy–momentum, generalized charge, and entropy with the superfluid velocity equations.
EPR studies of Mn-doped YBa2Cu3O7–δ composites
Authors: Stepanov A. A. , Gaillard B. , Regnier S. , Marfaing J.
Published: January 2025

The preliminary results of EPR experiments on superconducting Mn-YBaCuO composites are reported. The measurements were done in X band in the temperature range 4–300 K. Three distinct EPR components were observed possessing different g-factors and a rather different temperature behavior. For similar nonsuperconducting samples, only two signals were observed. The nature of the different components is discussed from the comparison of the results. It is shown that, among the superconducting samples, two of them originate from Mn2+ paramagnetic centers while the third one presumably comes from Cu2+ paramagnetic center. For the nonsuperconducting samples, a magnetic phase transition in an ordered state has been revealed at 25 K. This transition seems to be stimulated by the presence of Mn ions or clusters, probably located in the CuO chains.
Effects of weak localization of electrons in the conductivity of gold films irradiated with argon ions
Authors: Belevtsev B. I. , Belyaev E. Yu. , Bobkov V. V. , Glushko V. I.
Published: January 2025

The effects of weak localization and electron–electron interaction in the conductivity of vacuum-deposited gold thin films (thickness L ⩽ nm) before and after irradiation with argon ions at energies 0.5–3.5 keV are investigated. The influence of irradiation (at fluences up to ≃ 8 · 1015cm−2) is essentially to decrease the thickness of the films and to intensify disorder in the crystal lattice. The temperature and magnetic-field dependences of the quantum corrections Δσ to the conductivity of the films are measured at temperatures 0.5 K ⩽ T ⩽ 50 K and in magnetic fields up to 20 kOe. These dependences are processed numerically to determine the rates of inelastic, spin–orbit, and spin–spin relaxation of electrons. The spin–orbit relaxation rates in the investigated films are observed to decrease as the degree of disorder is intensified by ion irradiation. It is shown that this behavior (which appears, at first glance, to contradict the existing notion) is possible in thin films with a decrease in the mean free path if the predominant contribution to spin–orbit scattering is from the surface scattering of electrons.
Magnetization reversal of orthorhombic noncentroantisymmetric antiferromagnet DyFeO3
Authors: Gnatchenko S. L. , Chizhik A. B. , Bedarev V. A. , Kharchenko N. F.
Published: January 2025

Magnetization reversal in the noncentroantisymmetric orthorhombic antiferromagnetic (AFM) DyFeO3 is investigated using visual and magnetooptical methods. Energy inequivalence of time-inversed AFM states is created in a tilted field H = (Hx, Hy, Hz) by quadratic magnetization. The diagram of AFM states of the crystal under investigation in the tilted field is reconstructed, and the coercive energy Ec≈1.1·102 erg/cm3(T = 21 K) of AFM domain walls is determined. Elastic stresses present in the crystal and inducing the piezomagnetic moment noticeably affect the magnetization reversal AFM+ ⟷ AFM− in DyFeO3 due to low coercivity of AFM domain walls. The elastic stresses in the crystal are estimated as 50–100 kgf/cm2.
Anomalous transparency of layered conductors in magnetic field
Authors: Peschanskiĭ V. G. , Espeho G. , Bedassa D. Tesgera
Published: January 2025

It is shown that the anomalous transparency of layered conductors with a quasi-two-dimensional electron energy spectrum depends on the intensity of the Fermi-liquid interaction of charge carriers for certain orientations of a strong magnetic field, but the position of sharp peaks in the angular dependence of impedance remains unchanged when the Fermi-liquid effects are taken into account.
Quantum tunneling and quantum coherence in a topological soliton of a quasi-one-dimensional antiferromagnet
Authors: Ivanov B. A. , Kolezhuk A. K.
Published: January 2025

A new type of quantum tunneling of magnetization, i.e., tunneling between equivalent states of a topological soliton in a quasi-one-dimensional antiferromagnet (AFM), is proposed. The tunneling in AFM with a half-integral spin of magnetic ions is suppressed due to effects of destructive quantum interference.
Manifestations of latent ferromagnetism during magnetization of YBa2Cu3O6+x thin films
Authors: Gnatchenko S. L. , Baran M. , Szymczak R. , Szymczak H.
Published: January 2025

Magnetization of YBa2Cu3O6+x thin films (0.2≲x≲0.4) is studied in the temperature range 4.2<T<300 K in magnetic fields H‖c and H⊥c up to 50 kOe. The following peculiarities in the magnetic behavior of YBa2Cu3O6+x are observed: (1) irreversibility of the temperature dependences of magnetizations mZFC(T) and mFC(T) similar to that in spin glasses; (2) nonlinearity in the field dependences m(H), (3) hysteresis in field dependences of magnetization, and (4) the existence of remanent magnetic moment in zero field. It is concluded that antiferromagnetically ordered YBa2Cu3O6+x contains ferromagnetic clusters. The illumination by visible light causes an increase in the ferromagnetic phase volume and a decrease in the antiferromagnetic phase volume. The obtained experimental results can be explained by the phase separation model presuming the existence of ferrons (magnetic polarons) in high-Tc cuprates.
High-throughput screening and research of nitrogen reduction on 2D metal–organic framework: First-principles study
Authors: Xiong Zheng-Yun , Hong Wen-qing , Zhao Yu Qing , Yin Wen Jin , Xu Ying
Published: January 2025

Developing efficient nitrogen reduction reaction (NRR) catalysts remains challenging. Two-dimensional metal–organic frameworks (MOFs) stand out because of their large holes and high metal utilization. Based on first-principles high-throughput calculations, we studied the catalytic capacity of MOF catalyst TM3 (HITP)2 for NRR. Our calculated results indicate that among 29 catalytic structures, Mo3(HITP)2 and Os3(HITP)2 exhibit excellent activity for NRR, with the overpotential being 0.39 and 0.43 V, respectively. The unoccupied 4d orbitals of Mo are especially closer to the antibonding N-2p orbitals, leading to better nitrogen activation and lower overpotential. In addition, a descriptor related to charge variation and the electronegativity of metals and coordinating atoms is established, which has a good volcano plot relationship with the limiting potential of NRR and can provide ideas for catalyst screening. This research contributes valuable insights for the screening of NRR catalysts based on MOF.
Non-hexagonal symmetry-induced QH-graphene as a promising anode material for sodium-ion batteries: Effects of solvent, vacancy defect, and interlayer coupling
Authors: Ma Tian-Ci , Yang Shuang-Long , Zheng Xiao-Hong , Ye Xiao-Juan , Lin He , Liu Chun-Sheng
Published: January 2025

Developing two-dimensional (2D) carbon electrode materials with high performance has become an increasingly fascinating pursuit. However, the most popular carbon allotrope, graphene, possesses chemical inertness arising from its delocalized π-electron network. Breaking of the hexagonal symmetry in graphene can disrupt its π-conjugated system, thus increasing the surface reactivity. Here, by employing first-principles calculations, we predict a 2D carbon allotrope (called QH-graphene), which exhibits remarkable stability across the dynamic, thermal, and mechanical aspects. It has several advantages as an anode material for sodium-ion batteries (SIBs), including a high theoretical capacity (1116.7 mA h g−1), a moderate Na migration barrier (0.35–0.60 eV), a suitable average open-circuit voltage (0.55 V), and a small change in lattice parameters (∼3%). When contacted with electrolyte solvents, the Na adsorption and diffusion capabilities are enhanced. Moreover, introducing a monovacancy defect in QH-graphene improves the adsorption strength of Na but reduces its mobility. Compared with single-layer QH-graphene, QH-graphene bilayer has a stronger binding affinity for Na while maintaining rapid ion diffusion on its exterior surface.
Observer-based suppression of the wing-rock oscillations using function approximation technique
Authors: Mobayen Saleh , Izadbakhsh Alireza
Published: January 2025

The dynamics of wing rock motion with varying angles of attack are notably uncertain and subject to external disturbances. This study introduces a robust adaptive control method, using an observer-based strategy with Fourier Series (FS) expansion as uncertainty estimators to mitigate wing rock oscillations in slender delta wings. The lumped uncertainties, including external disturbances and unmodeled dynamics, are initially represented using the FS. Adaptation laws, based on stability analysis, are then applied to adjust the FS coefficients. An essential aspect of the proposed strategy is that it eliminates the need for an accurate plant model, precise knowledge of uncertainties, and roll rate measurements, making it more cost-effective and suitable for practical applications. Using the Lyapunov lemma, the paper guarantees that the error signals in the controlled system remain Uniformly Ultimately Bounded. Simulation results highlight the efficiency and versatility of the proposed approach. The outcomes are compared with two advanced estimation methods to showcase the efficiency and accuracy of the suggested controller design.
A coarse-grained discrete element method based on the principle of energy density mapping conservation: Efficient simulation of particle dynamic mixing and interaction using larger particles
Authors: Jin Gaohan , Zhou Zongqing , Liu Yuhan , Gao Chenglu , Xie Yunpeng , Tao Guangzhe
Published: January 2025

A novel coarse-grained methodology has been developed, which is founded on the principle of energy density mapping conservation. Energy density conservation is maintained by this methodology throughout the particle size scaling, wherein kinetic, elastic strain, frictional, and damping energy densities are preserved. The methodology has been designed to address both dynamic particle flow and quasi-static interaction, whereby a comprehensive characterization model for microscopic parameters between particles in a coarse-grained system was established. The performance and accuracy were systematically evaluated through numerical simulations of rotating drum and direct shear tests. Excellent agreement with the original system was demonstrated by the numerical results in terms of particle mixing, Lacey mixing index, velocity field distribution, and stress field patterns. Significant improvements in shear rate distribution, force chain morphology, and force chain magnitude were observed in direct shear simulations when compared to the without coarse-grained system, by which the efficacy of the proposed methodology was substantiated.
Atmospheric rivers bring anomalously high temperatures
Authors: Lopatka Alex
Published: January 2025

Narrow bands of water vapor, long known for the torrential rains they deliver, also transport vast amounts of heat.
Coding relationship links RNA G-quadruplexes and protein RGG motifs in RNA-binding protein autoregulation
Authors: Adlhart Marlene , Hoffmann Daniel , Polyansky Anton A. , Žagrović Bojan
Published: January 2025

RNA G-quadruplexes (rG4s), the four-stranded structures formed by guanine-rich RNA sequences, are recognized by regions in RNA-binding proteins (RBPs) that are enriched in arginine-glycine repeats (RGG motifs). Importantly, arginine and glycine are encoded by guanine-rich codons, suggesting that some RGG motifs may both be encoded by and interact with rG4s in autogenous messenger RNAs (mRNAs). By analyzing transcriptome-wide rG4 datasets, we show that hundreds of RGG motifs in humans are at least partly encoded by rG4s, with an increased incidence for longer RGG motifs (~10 or more residues). Using randomized genetic codes, we demonstrate that the rG4/RGG coding relationship derives from the universal genetic code’s structure. Moreover, we show that proteins, which contain RGG motifs encoded by experimentally detected rG4s, are significantly enriched in RNA binding relative to all RGG-containing proteins. Finally, using enhanced crosslinking and immunoprecipitation (eCLIP) data, we identify several prominent RBPs, including FUS, FMRP, and G3BP1, which interact with autogenous mRNAs in regions where RGG motifs are encoded by rG4s. Our results define a physically realistic mechanism behind autogenous mRNA/protein interactions that is hardwired in the genetic code structure and may contribute to the establishment of autoregulatory feedback loops in the cell.
Centriolar cap proteins CP110 and CPAP control slow elongation of microtubule plus ends
Authors: Iyer Saishree S. , Chen Fangrui , Ogunmolu Funso E. , Moradi Shoeib , Volkov Vladimir A. , van Grinsven Emma J. , van Hoorn Chris , Wu Jingchao , Andrea Nemo , Hua Shasha , Jiang Kai , Vakonakis Ioannis , Potočnjak Mia , Herzog Franz , Gigant Benoît , Gudimchuk Nikita , Stecker Kelly E. , Dogterom Marileen , Steinmetz Michel O. , Akhmanova Anna
Published: January 2025

Centrioles are microtubule-based organelles required for the formation of centrosomes and cilia. Centriolar microtubules, unlike their cytosolic counterparts, are stable and grow very slowly, but the underlying mechanisms are poorly understood. Here, we reconstituted in vitro the interplay between the proteins that cap distal centriole ends and control their elongation: CP110, CEP97, and CPAP/SAS-4. We found that whereas CEP97 does not bind to microtubules directly, CP110 autonomously binds microtubule plus ends, blocks their growth, and inhibits depolymerization. Cryo-electron tomography revealed that CP110 associates with the luminal side of microtubule plus ends and suppresses protofilament flaring. CP110 directly interacts with CPAP, which acts as a microtubule polymerase that overcomes CP110-induced growth inhibition. Together, the two proteins impose extremely slow processive microtubule growth. Disruption of CP110–CPAP interaction in cells inhibits centriole elongation and increases incidence of centriole defects. Our findings reveal how two centriolar cap proteins with opposing activities regulate microtubule plus-end elongation and explain their antagonistic relationship during centriole formation.
Surface receptor-targeted protein-based nanocarriers for drug delivery: advances in cancer therapy
Authors: Theivendren Panneerselvam , Pavadai Parasuraman , Veerachamy Suganthan , Palanisamy Ponnusamy , Kunjiappan Selvaraj
Published: January 2025

Significant progress has been made in cancer therapy with protein-based nanocarriers targeted directly to surface receptors for drug delivery. The nanocarriers are a potentially effective solution for the potential drawbacks of traditional chemotherapy, such as lack of specificity, side effects, and development resistance. Peptides as nanocarriers have been designed based on their biocompatible, biodegradable, and versatile functions to deliver therapeutic agents into cancer cells, reduce systemic toxicity, and maximize therapy efficacy through utilizing targeted ligands such as antibodies, amino acids, vitamins, and other small molecules onto protein-based nanocarriers and thus ensuring that drugs selectively accumulate in the cancer cells instead of healthy organs/drug release at a target site without effects on normal cells, which inherently caused less systemic toxicity/off-target effect. Moreover, their intrinsic protein backbone naturally degrades in vivo, providing another level of safety over synthetic materials. Various issues like immunogenicity, mass production, and quality control must be addressed for widespread use. However, further studies are necessary to perfect protein engineering and improve drug loading, protein modification, and targeting. Thus, it can be concluded that protein-based nanocarriers targeted against the surface receptors would help achieve cancer management in a more focused manner, thus minimizing toxicity. The further development of these nanoparticles could bring a significant change in cancer treatment so that more personalized, targeted, and safe therapies would be available to all patients.
Enhanced multi-keV x-ray emission with a low-coherence laser
Authors: Zhou Xichen , Liu Huiya , Kang Ning , Wang Ruirong , Hu Guangyue , Zhang Jiyan , Tu Shaoyong , Zhao Yao , Xu Guoxiao , An Honghai , Xie Zhiyong , Fang Zhiheng , Wang Wei , Lei Anle
Published: January 2025

Multi-keV x-rays are essential for diagnostic applications in inertial confinement fusion and high energy density physics. In this paper, enhancement of the multi-keV x-ray emission is achieved by using a low-coherence green laser to irradiate Ti foil targets at a fractional bandwidth of 0.6%. Compared to the widely used narrowband lasers, the above broadband laser generated 17%–23% more intense He-like alpha x-rays of Ti in the experiments at laser intensities of 4–6 × 1014 W cm-2. The improved laser absorption due to the reduction of stimulated Brillouin scattering introduced by the bandwidth is responsible for the enhancement of x-ray emission. The results suggest a promising application of broadband lasers on x-ray generations and further diagnostics.
Scalar bosons in Bonnor-Melvin-Λ universe: exact solution, Landau levels and Coulomb-like potential
Authors: Barbosa L G , Barros C C
Published: January 2025

In this work, we study spin-0 particles in a spacetime whose structure is determined by a homogeneous magnetic field and a cosmological constant. For this purpose, we take into account a framework based on the Bonnor-Melvin solution with the inclusion of the cosmological constant. We write the Klein–Gordon equation, solve it, and determine the Landau levels. The effects of scalar and vector potentials are considered, and we investigate the influence of the parameters of the theory on the results, which present observable effects. The implications of the physics of a stellar model based on this framework are also discussed.
Metal-insulator transition in MnS
Authors: Chernov Evgenii D , Lukoyanov Alexey V
Published: January 2025

In this article, we have studied phase transitions in the cubic (α-MnS) and hexagonal (γ-MnS) structures of MnS under pressure in the framework of theoretical calculations, accounting for electron correlations in the manganese ions. The value of the band gap is found to be about 2 eV for the chosen approach. We theoretically demonstrate that the insulator-metal phase transition may occur in both cubic and hexagonal structures of MnS under uniform compression. The magnetic moments of manganese were also calculated depending on the value of the Coulomb interaction parameter and lattice volume. The value of the magnetic moments reaches 4.41–4.59 μ
B for the certain conditions. Finally, the spin transition of the manganese ions from the high-spin to the low-spin state under high pressure was found.
Enhancing Planck All-Sky Maps through Fourier Transform-Based Smoothing
Authors: Saowanit Grit , Wechakama Maneenate , Sawangwit Utane
Published: January 2025

The microwave wavelength range of the sky encompasses a rich variety of astro-physical signals, including emissions from the Galactic interstellar medium and the Cosmic Microwave Background (CMB). The Planck satellite has significantly contributed to capturing these signals, providing a vast dataset in its Public Data Release 3 (PR3). This study focuses on the effective processing of this data, which consists of approximately 12.5 million points, through a binning method that reduces the data to 64,800 points, thus enhancing the efficiency of subsequent analysis. To further improve the signal quality, the Fast Fourier Transform (FFT) is applied, enabling noise reduction and smoothing of the data. The methodology highlights the transformation of intensity measurements to an astrophysically relevant format and the application of locally adaptive filtering techniques in the Fourier domain. The study specifically evaluates the performance of fitting a 2-dimensional Lorentzian model to both binned and FFT-processed maps, revealing that FFT maps demonstrate superior fitting efficiency with lower reduced chi-square values and reduced processing times. These results indicate the efficacy of FFT in enhancing data quality for analyzing large-scale structures within the all-sky map, ultimately facilitating a more accurate understanding of underlying astrophysical phenomena.
Bandwidth Analysis for a Combined Horizontal and Vertical Correcting Magnet for Siam Photon Source II
Authors: Tangyotkhajorn Warissara , Sunwong Prapaiwan , Prawanta Supachai , Sudmuang Porntip , Phacheerak Wiwek , Leetha Thongchai , Naeosuphap Sakdinan
Published: January 2025

Bandwidth analysis is performed for the corrector magnet to meet the transversal electron beam stability and low emittance requirement of Siam Photon Source II. The magnet will operate as a Slow and Fast Orbit Feedback system (SOFB and FOFB), where the fast correction rate is 10 kHz. The bandwidth is investigated for the isolated solid and laminated iron yoke magnets, the chamber, and the magnet-chamber system. Eddy current of the magnet pole and yoke as well as the chamber are observed during ac-excitation, leading to losses. With CST Studio Suite, optimization of the lamination sheet stacking factor, vacuum chamber thickness, and vacuum chamber material are performed and reported. The net bandwidth of the magnet-chamber system is determined to be 41 kHz.
Indirect control of 13C nuclear spin in nitrogen vacancy center in diamond
Authors: Saego Kritsana , Sangtawesin Sorawis
Published: January 2025

The nitrogen vacancy (NV) center in diamond is one of the solid-state spin systems that can be manipulated as a qubit for quantum computing. However, scaling up the system to perform as a quantum register is challenging due to weak dipole interaction between two NV centers. On the other hand, 13C nuclear spins that reside within the diamond lattice can be used as additional qubits for scaling up the system, as they have hyperCine interactions with the NV center electronic spin. In general, nuclear spins exhibit a longer coherence time compared to the electron spin due to the lower gyromagnetic ratio. Nevertheless, this weak interaction also makes it difficult to directly control the nuclear spin via RF transition. In this work, we demonstrated a scheme to control and observe the dynamics of nuclear spin with a hyperCine splitting of 6.5 MHz using an indirect pulse sequence that operated only the electron spin in absence of any RF signal. Our results reveal a nuclear spin free precession with a gyromagnetic ratio of 6.9 ± 0.1 kHz/Gauss. Furthermore, one can observe the nuclear spin phase accumulation in electronic spin m

s
= - 1 manifold and show the reduced contrast results from incomplete population transfer during the operation.