bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dynamic pricing‐based integration for non‐cooperative ubiquitous sensing and communication network
Authors: Ren Chao , Dai Weiheng , Gong Chao , Li Haojin , Sun Chen , Lu Yang 
Published: October 2024

AbstractAs 5G and early‐stage network technologies mature, a wealth of data and experience is accumulated. The ubiquitous sensing and communication network (USCN) can leverage these existing communication infrastructures to maximize resource utilization and reduce the costs of redeployment through integration with modern 6G and beyond 6G networks. However, implementing future integrated sensing and communication (ISAC) functions in USCN may possess different hardware capabilities and communication protocols, presenting significant challenges. This is due to the lack of a unified framework for managing and optimizing these heterogeneous resources, as well as the absence of reasonable performance metrics. This letter proposes a dynamic pricing coordinated resource allocation (DPCRA) mechanism to realize the emerging ISAC in legacy USCNs. The DPCRA is designed to optimize the spectrum efficiency (SE) of USCN and manages resource interactions between heterogeneous devices through price variables, thereby resolving resource conflicts and deadlocks. The novelties include: (1) employing a price mechanism to foster resource cooperation in non‐cooperative networks; (2) introducing an SE metric incorporating an information similarity factor for optimization; (3) dynamically selecting resources to enhance SE. Simulations demonstrate that the DPCRA effectively resolves device deadlock while maintaining high SE levels, promoting device collaboration.
Enhancing distribution system stability and efficiency through multi‐power supply startup optimization for new energy integration
Authors: Meng Qinglin , Tong Xinyu , Hussain Sheharyar , Luo Fengzhang , Zhou Fei , He Ying , Liu Lei , Sun Bing , Li Botong 
Published: October 2024

AbstractThis paper addresses the challenge of maximizing power capture from new energy sources, including coal, wind, solar, and hydroelectric power, which often lack sufficient inertia support. This deficiency can lead to frequency instability and cascading failures within the power system. A cooperative optimization model for the start‐up of multiple power supplies, designed to enhance the integration of new energy sources while maintaining system stability is proposed. The model incorporates primary frequency modulation and the intrinsic inertia support capabilities of self‐synchronous voltage source field stations, considering dynamic frequency constraints. Additionally, it employs new energy units with primary frequency modulation to provide inertia support during curtailment, particularly when conventional units cannot meet frequency standards due to existing constraints. Extensive simulations and comparative analyses demonstrate that the proposed model improves new energy utilization by up to 37.5% and reduces operational costs by approximately 16%, enhancing overall operational efficiency in high energy consumption scenarios.
A modified synchronverter for a weak grid with virtual power circles‐based PQ decoupling scheme
Authors: Kisinga Daniel Angelo , Makolo Peter , Trodden Paul 
Published: October 2024

AbstractThe high penetration of renewable energy sources (RES) results in a low‐inertia, weak power grid. To mitigate this and restore system inertia, it has been widely proposed to operate the inverters of RES units to mimic synchronous generators; this technology is known as a virtual synchronous generator (VSG). In weak grids there is, however, strong coupling between active power () and reactive power (), and any VSG technique therefore requires decoupling in order to operate effectively. This article proposes a new decoupling technique based on the transformation of the power circle of a VSG connected to a weak grid: first, the power circle is translated from its designed position to that of a conventional synchronous generator (SG) connected to a strong grid, achieving partial decoupling. Then, to achieve full decoupling, the authors propose further to modulate the radius of the translated power circle; this is achieved using a series resistance‐capacitance–inductance () circuit which is virtually implemented in the VSG controller. The efficacy of the proposed scheme is validated using a modified synchronverter connected to the weak grid in representative loading scenarios. It is demonstrated that the technique achieves a decoupled control for the synchronverter connected in a weak grid. Moreover, the modified synchronverter is capable of supporting frequency and voltage regulation in the grid without inducing large transient grid currents during mild frequency and voltage variations.
GALILÉE-1: Verification and processing system for Evaluated Data
Authors: Coste-Delclaux Mireille , Jouanne Cédric , Mounier Claude 
Published: October 2024

This paper gives an overview of the processing methods available for now in GALILÉE-1 [1], the verification and processing system for evaluated data, developed at CEA. This paper shows also results illustrating the main processing steps.
GALILÉE-1 consists of various components respectively dedicated to read/write the evaluated data independently of the format, to diagnose inconsistencies in the evaluated data and to provide continuous-energy and multigroup data as well as probability tables for particle transport and depletion codes. All these components are written in C++ language and share the same objects.
Magnetic Resonance Assessment of Bone Quality in Metabolic Bone Diseases
Authors: Sollmann Nico , Dieckmeyer Michael , Carballido-Gamio Julio , Van Anh Tu , Karampinos Dimitrios C. , Feuerriegel Georg C. , Foreman Sarah C. , Gersing Alexandra S. , Krug Roland , Baum Thomas , Kirschke Jan S. 
Published: October 2024

AbstractMetabolic bone diseases (MBDs) are a diverse group of diseases, affecting the mass or structure of bones and leading to reduced bone quality. Parameters representing different aspects of bone health can be obtained from various magnetic resonance imaging (MRI) methods such as proton MR spectroscopy, as well as chemical shift encoding-based water-fat imaging, that have been frequently applied to study bone marrow in particular. Furthermore, T2* mapping and high-resolution trabecular bone imaging have been implemented to study bone microstructure. In addition, quantitative susceptibility mapping and ultrashort echo time imaging are used for trabecular and cortical bone assessment. This review offers an overview of technical aspects, as well as major clinical applications and derived main findings, for MRI-based assessment of bone quality in MBDs. It focuses on osteoporosis as the most common MBD.
Radiofrequency Echographic Multi-Spectrometry in the Diagnosis of Metabolic Bone Disease
Authors: Gifuni Rossella , Montatore Manuela , Guglielmi Riccardo , Bazzocchi Alberto , Messina Carmelo , Guglielmi Giuseppe 
Published: October 2024

AbstractDual-energy X-ray absorptiometry (DXA) and bone mineral density (BMD) pose several limitations in some patient categories, such as pregnant women and young people. This review article explores whether the innovative radiofrequency echographic multi-spectrometry (REMS) technology is beneficial for assessing the bone condition of various patient groups. Common consequences in patients with acromegalia, prostate cancer undergoing hormone therapy, osteogenesis imperfecta, anorexia nervosa, and in a peritoneal dialysis setting include decreased BMD and an increased risk of fragility fracture.DXA is currently regarded as the gold standard for BMD assessment. However, using the DXA technique has several drawbacks in a young patient who requires repeated BMD tests because it uses ionizing radiation. Because of its precision and consistency, the REMS technique may be a valuable tool to assess changes in bone condition in patients of all ages, particularly in female patients who are fertile or who are pregnant or nursing.
Proton transport mechanisms in aqueous acids: Insights from ab initio molecular dynamics simulations
Authors: Zhu Zhenghao , Sokolov Alexei P. , Paddison Stephen J. 
Published: October 2024

The solvation and transport of protons in aqueous solutions of phosphoric acid (PA), sulfuric acid (SA), and nitric acid (NA) were studied using ab initio molecular dynamics simulations. Systems with acid-to-water ratios of 1:1 and 1:3 were examined to understand the similarities and differences in transport mechanisms. The solvation structure of H3O+ in these systems is similar to that in slightly acidic water, with variations in the strength of hydrogen bonds (H-bonds) accepted by acid molecules. In aqueous PA systems, strong H-bonds between PA molecules are slightly affected by water, leading to significantly greater H3O+ diffusion compared to aqueous SA and NA systems. This enhanced diffusion is attributed to the participation of PA molecules in H3O+ transport, where the PA molecule can shuttle a proton for H3O+, facilitating a large displacement via collective proton hopping. This shuttling mechanism is prominent in aqueous PA but rare in aqueous SA and absent in aqueous NA. Moreover, the decomposition of H3O+ diffusion into vehicular and structural components indicates that the higher diffusion in aqueous PA is primarily due to the structural mechanism with the aid of PA molecules. In the aqueous NA systems, the vehicular diffusion is dominant at low water contents and the increase in water content improves the structural diffusion by forming connected H-bonds within water molecules. Our findings elucidate the role of acid molecules in proton transport within their aqueous solutions, thereby advancing the fundamental understanding of proton transport mechanisms.
Molecular dynamics simulations of uranyl and plutonyl cations in a task-specific ionic liquid
Authors: Maerzke Katie A. , Goff George S. , Runde Wolfgang H. , Schneider William F. , Maginn Edward J. 
Published: October 2024

Ionic liquids (ILs) are a unique class of solvents with potential applications in advanced separation technologies relevant to the nuclear industry. ILs are salts with low melting points and a wide range of tunable physical properties, such as viscosity, hydrophobiciy, conductivity, and liquidus range. ILs have negligible vapor pressure, are often non-flammable, and can have high thermal stability and a wide electrochemical window, making them attractive for use in separations processes relevant to the nuclear industry. Metal salts generally have a low solubility in ILs; however, by incorporating new functional groups into the IL cation or anion that promote complexation with the metal, the solubility can be greatly increased. One such task-specific ionic liquid (TSIL) is 1-carboxy-N, N, N-trimethylglycine bis(trifluoromethylsulfonyl)imide ([Hbet][Tf2N]) [Nockemann et al., J. Phys. Chem. B 110, 20978–20992 (2006)]. Water, which is detrimental for electrochemical separations, is a common impurity in ILs and can coordinate with actinyl cations, particularly in ILs containing only weakly coordinating components. Understanding the behavior of actinides in TSIL/water mixtures on a molecular level is vital for designing improved separations processes. Classical molecular dynamics simulations of uranyl(VI) and plutonyl(VI) in 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][Tf2N]) with deprotonated Hbet (betaine) and water have been performed to understand the coordination and dynamics of the actinyl cations. We find that betaine is a much stronger ligand than water and prefers to coordinate the metal in a bidentate manner. Potential of mean force simulations yield a relative free energy for betaine coordination of approximately −120 to −90 kJ/mol in mixtures with water. As the amount of betaine coordinated to the actinide increases, the diffusion coefficient of the actinyl cation decreases. Moreover, the betaine ligand is able to bridge between two metal centers, resulting in dimeric complexes with actinide–actinide distances of ∼5 Å. Potential of mean force simulations show that these structures are stable, with relative free energies of up to −40 kJ/mol. The crystal structure for [(UO2)2(bet)6(H2O)2][Tf2N]4 shows that the betaine bridges between two uranium atoms to form dimeric complexes similar to those found in our simulations [Nockemann et al. Inorg. Chem. 49, 3351–33601 (2010)].
Cavity Born–Oppenheimer approximation for molecules and materials via electric field response
Authors: Bonini John , Ahmadabadi Iman , Flick Johannes 
Published: October 2024

We present an ab initio method for computing vibro-polariton and phonon-polariton spectra of molecules and solids coupled to the photon modes of optical cavities. We demonstrate that if interactions of cavity photon modes with both nuclear and electronic degrees of freedom are treated on the level of the cavity Born–Oppenheimer approximation, spectra can be expressed in terms of the matter response to electric fields and nuclear displacements, which are readily available in standard density functional perturbation theory implementations. In this framework, results over a range of cavity parameters can be obtained without the need for additional electronic structure calculations, enabling efficient calculations on a wide range of parameters. Furthermore, this approach enables results to be more readily interpreted in terms of the more familiar cavity-independent molecular electric field response properties, such as polarizability and Born effective charges, which enter into the vibro-polariton calculation. Using corresponding electric field response properties of bulk insulating systems, we are also able to obtain the Γ point phonon-polariton spectra of two dimensional (2D) insulators. Results for a selection of cavity-coupled molecular and 2D crystal systems are presented to demonstrate the method.
The journey metaphor in Huawei mobile phone commercials
Authors: Jia Zhangjingwen 
Published: October 2024

Abstract
This paper investigates the creative use of the structural, embodied journey metaphor within the genre of
video advertising using Conceptual Metaphor Theory (CMT). Conducting a qualitative analysis of eight Huawei mobile phone
commercials, I examine how multimodal resources — visual, verbal and written language, as well as music and sound — are
orchestrated to construct and communicate the metaphorical narrative of using a Huawei mobile phone in terms of a journey. The
analysis reveals a heavy reliance on visual elements, supported by the strategic use of sound and music, to create metaphors that
communicate progress and exploration — themes central to the journey concept. This paper shows how the journey
metaphor in audio-visual advertising diverges from its purely verbal varieties by drawing on medium-specific capabilities such as
time and space compression, and on hyperbole. It is argued that the journey metaphor’s embodied nature and its potency in
aligning the mobile phone with consumer aspirations contribute to the universal appeal and understanding of the commercials.
Schrödinger connections: from mathematical foundations towards Yano–Schrödinger cosmology
Authors: Csillag Lehel , Agashe Anish , Iosifidis Damianos 
Published: October 2024

Abstract
Schrödinger connections are a special class of affine connections, which despite being metric incompatible, preserve length of vectors under autoparallel transport. In the present paper, we introduce a novel coordinate-free formulation of Schrödinger connections. After recasting their basic properties in the language of differential geometry, we show that Schrödinger connections can be realized through torsion, non-metricity, or both. We then calculate the curvature tensors of Yano–Schrödinger geometry and present the first explicit example of a non-static Einstein manifold with torsion. We generalize the Raychaudhuri and Sachs equations to the Schrödinger geometry. The length-preserving property of these connections enables us to construct a Lagrangian formulation of the Sachs equation. We also obtain an equation for cosmological distances. After this geometric analysis, we build gravitational theories based on Yano–Schrödinger geometry, using both a metric and a metric-affine approach. For the latter, we introduce a novel cosmological hyperfluid that will source the Schrödinger geometry. Finally, we construct simple cosmological models within these theories and compare our results with observational data as well as the ΛCDM model.
Novel sparse auto-encoder framework with pseudo-labeled reinforcement for cross domain fault diagnosis with imbalanced samples
Authors: Zhang Faye , Liu Fuzheng , Liu Minghui , Zhang Yilan , Jiang Mingshun , Sui Qingmei 
Published: October 2024

Abstract
By applying diagnostic expertise from one area to another that is closely related, transfer fault diagnosis is an efficient strategy for guaranteeing the secure and dependable operation of mechanical equipment. However, the majority of rotating machinery monitoring data are gathered in industrial applications under normal operating settings, which leads to an imbalance between positive and negative samples. Consequently, performing high-precision fault diagnosis with imbalanced data and different working conditions becomes challenging due to the escalating difficulty and cost of acquiring labeled fault samples. For cross domain fault diagnosis, an enhanced deep transfer sparse auto-encoder (SAE) framework is provided. This approach leverages a SAE to delve deeper into fault features within imbalanced data and reconstruct the samples accordingly. Furthermore, the research proposes a feature domain penalty term to facilitate cross-domain training by aligning the distribution of the source and target domain data which can reduce data distribution deviation. A pseudo-labeled reinforcement training method is presented to further improve cross-domain classification accuracy with imbalanced samples. Extensive experiments were conducted on two datasets to assess the proposed method. The results were compared with other algorithms, demonstrating the effectiveness and superiority of the proposed approach.
Estimating the GPS time-varying differential code bias between C1 and P1 observations to provide a model product
Authors: Li Haojun , Xiao Jingxin , Li Xiaoming 
Published: October 2024

Abstract
Based on the time-varying characteristics of GPS satellite differential code biases (DCB) between C1 and P1 observations, a method for directly estimating its model coefficients is proposed to streamline processing and enhance product accuracy. Evaluation over three days compares estimated DCB (C1–P1) values and assesses real-time service capabilities in single point positioning (SPP). Three-day DCB (C1–P1) estimates match single-epoch time-varying DCB (C1–P1) series fitting accuracy. SPP results show significant improvement over Orbit Determination in Europe (CODE), reducing average root mean square error in three dimensions by 12 cm and by 4 cm compared to Chinese Academy of Sciences. Real-time DCB (C1–P1) service maintains stable and accurate performance, comparable to fitted values of single-epoch time-varying series. Real-time SPP application shows the method enhances positioning accuracy compared to CODE by up to 35%, confirming the feasibility and effectiveness of the proposed model estimation method.
Infrared target detection algorithm based on multipath coordinate attention mechanism
Authors: Da Mei , Jiang Lin , Tao YouFeng , Zhang Zhijian 
Published: October 2024

Abstract
The current generation of infrared target detection algorithms frequently exhibits a high degree of dependency on parameter configurations within complex operational environments. This often results in a reduction in detection accuracy, an increase in the number of model parameters, and a slowing of the detection process. To address these limitations, a new algorithm, CGhostNet-Attention-YOLO (CAY), is proposed in this paper. Firstly, we designed a lightweight backbone network, CGhostNet, with the objective of improving feature extraction efficiency, thereby enabling accurate and real-time feature extraction. Furthermore, we proposed a multipath coordinate attention mechanism, which incorporates both channel and positional information, thereby facilitating enhanced context awareness and the comprehension of relationships between different positions. This effectively enhances the model’s ability to comprehend the overall meaning and addresses the issue of missed detections in infrared targets, significantly improving detection accuracy. Moreover, we employed the Inner-SIoU loss function to accelerate model convergence, reduce loss, and enhance the robustness of the model. Finally, comparative experiments were conducted on our dataset (IFD) as well as publicly available datasets, including FLIR, Pascal VOC, and NEU-DET. The results demonstrate that the CAY algorithm achieved a mean Average Precision (mAP@0.5) of 81.3% on the IFD dataset, 86.1% on the FLIR dataset, 79.2% on the Pascal VOC dataset, and 79.9% on the NEU-DET dataset, with a 27% reduction in the number of parameters. These findings validate the feasibility of the proposed algorithm.
Research on faults diagnosis of dynamic balance in scroll compressor based on CWT-MViTV2
Authors: Xingshen Dong , Lin Lu , Haisheng Li , Jun Bao , Yinghua Chen , Xun Zhang , Wenyu Miao 
Published: October 2024

Abstract
The dynamic balancing of rotor systems is a critical factor affecting the vibration of scroll compressors. Traditionally, the detection and correction of rotor dynamic balancing systems have relied on time-domain and frequency-domain analysis of vibration signals, as well as validation using rotor dynamic balancing test platforms. This paper proposes a novel fault diagnosis method for the dynamic balancing of scroll compressor rotor systems. This method acquires the time-domain vibration signals of the scroll compressor through online detection experiments. These signals are then transformed into time-frequency maps using continuous wavelet transform (CWT). By integrating the MViTV2 neural network, this approach enables effective identification of dynamic balancing fault types without requiring disassembly or shutdown of the machine. The fault types, corresponding to the offset of the balancing weight’s centroid, will provide direct data support for subsequent validation work. This study compares various neural network models combined with time-frequency maps and demonstrates that the proposed model achieves the highest accuracy of 99.749% compared to other models, and the method’s generalizability is validated in the public dataset. Furthermore, the proposed model maintains a high accuracy of 94.872% in high-noise environments. After improvement, the accuracy of the model has been increased to 95.641%, the training time and the diagnosis time has been reduced to 0.240 iter/s and 0.0277 s.