bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cryogenic front-end circuit for capacitive sensing in superconducting gravimeters
Authors: Li Yaqiong , Liu Lu , Chen Yaqin , Zhang Ning , Chen Liang , Liu Xiangdong 
Published: January 2025

Capacitive sensors are commonly used in superconducting gravimeters due to their high resolution and low drift. This study developed a cryogenic front-end circuit for superconducting gravimeters to reduce the negative effects of parasitic capacitance on capacitive sensors. The front-end circuit comprises a noiseless superconducting transformer and a low-noise cryogenic preamplifier, both of which are positioned adjacent to the capacitive sensor probe. Compared with the front-end circuit operating at 300 K, the transfer coefficient of the front-end circuit increases from 131 to 1070 V/m, and the equivalent displacement noise reduces from 1.4 × 10−10 to 5.0 × 10−11 m/Hz1/2 within a frequency band from 10−3 to 1 Hz. The temperature coefficient of the cryogenic preamplifier is 0.3%/K, and the superconducting transformer’s matching factor has adjusted as low as (2.4 ± 0.2) × 10−4. The cryogenic front-end circuit was finally applied to a superconducting gravimeter. The observed gravity data satisfactorily fit the theoretical tidal model, implying good long-term stability for the developed front-end circuit.
Accurate DFT simulation of complex functional materials: Synergistic enhancements achieved by SCAN meta-GGA
Authors: Ke Da , Sun Jianwei , Zhang Yubo 
Published: January 2025

Complex functional materials are characterized by intricate and competing bond orders, making them an excellent platform for evaluating the newly developed strongly constrained and appropriately normed (SCAN) density functional. In this study, we explore the effectiveness of SCAN in simulating the electronic properties of displacive ferroelectrics (BaTiO3 and PbTiO3) and magnetoelectric multiferroics (BiFeO3 and YMnO3), which encompass a broad spectrum of bonding characteristics. Due to a significant reduction in self-interaction error, SCAN manifests its improvements over the Perdew–Burke–Ernzerhof (PBE) method in three aspects: SCAN predicts more accurate ionicity, produces more compact orbitals, and better captures d-orbital anisotropy. Particularly, these synergistic enhancements lead to notable phenomena in calculating the bandgap of YMnO3: while the PBE+U simulation may suggest a strong correlation appearance attributed to high Hubbard-like U values (∼5 eV), the value is dramatically lower (∼1 eV) in the SCAN+U method. Furthermore, we provide an intuitive analysis of SCAN’s operational principles by examining the complex electron densities involved. These insights are theoretically intriguing and have practical implications, potentially encouraging wider adoption of SCAN in the computational modeling of complex functional materials.
Assessing the efficacy of synthetic compounds foliar sprays in alleviating terminal heat stress in late-sown wheat (Triticum aestivum)
Authors: Singh Tribhuwan , Singh Chandrakant , Kumar Rajiv , C. V. Nandeesha 
Published: January 2025

Detrimental effects of terminal heat stress could be mitigated by exogenous application of synthetic compounds by preserving cell membrane integrity and protecting against oxidative damage. A field experiment was conducted to test the application of seven synthetic compounds on wheat growth traits: (1) thiourea (20 mM and 40 mM); (2) potassium nitrate (1% and 2%); (3) sodium nitroprusside (400 μg mL−1 and 800 μg mL−1); (4) dithiothreitol (25 ppm and 50 ppm); (5) salicylic acid (100 ppm and 200 ppm); (6) thioglycolic acid (200 ppm and 500 ppm); and (7) putrescine (4 mM and 6 mM). These compounds were applied at the anthesis and grain-filling stages to enhance physio-biochemical traits and yield attributes of wheat (Triticum aestivum) cvs GW-11 and GW-496 under terminal heat stress. The results indicated that GW-11 plants treated with 100 ppm salicylic acid exhibited significant improvements (P ≤ 0.05) in canopy temperature depression, proline content, total chlorophyll content, and the membrane stability index. Compared with the control treatment, foliar application of 100 ppm salicylic acid at both stages caused increases in grain yield (19.5%), followed by a 14% increase with 4 mM putrescine. These yield improvements were attributed to higher grains per spike, more effective tillers, and greater 1000-grain weight, reflecting enhanced sink capacity and grain development under stress. Consequently, the foliage application of 100 ppm salicylic acid at the anthesis and grain-filling stages is recommended to improve late-sown wheat productivity and reduce terminal heat stress.
Adaptive management of a remote threatened-species population on Aboriginal lands
Authors: Read J. L. , West R. , Mills Oska , Phillips B. L. 
Published: January 2025

Context Adoption and refinement of monitoring and management techniques is important for improving the conservation status of threatened fauna, especially in remote areas with high logistical and financial costs. In Australia, many of these remote conservation projects are conducted by Traditional Owners and Indigenous Ranger groups, with input and support from various stakeholders including government and non-government organisations, and third-party ecologists. A collaborative approach to project development and adaptive management in response to stakeholder objectives is essential for long-term project success. Aims In the remote context of the Anangu Pitjantjatjara Yankunytjatjara (APY) Lands, we collaboratively develop a sustainable and robust monitoring and management method for warru (black-flanked rock wallabies) that recognises the skills, interests, and capacity of all project members. In developing this method over 22 years, we also evaluate the influence of rainfall and predator-control strategies on warru populations to inform optimised management. Methods Practical and economic capabilities and preferences of both Traditional Owners and external scientists for monitoring and management actions were evaluated. Data from long-term cage trapping, and scat and spotlight counts of warru were compared with population trajectories, annual rainfall, and management strategies. Key results Population indices with lower resource requirements, such as scat and spotlight counts, provide trends consistent with more resource-intensive capture–mark–recapture studies. The warru scat index was negatively associated with the scat index for a competing herbivore (kanyala, euro). Warru growth rates were positively influenced by rainfall. Contrary to initial results from other regions, warru populations declined during periods when we undertook predator baiting. By contrast, targeted shooting of feral cats and foxes was associated with increased warru population growth rates. Conclusions These results suggest that a minimum of four groups of five scat quadrats in prime refuge areas and equivalent sampling in prime feeding zones (total 40 quadrats) is appropriate for rock-wallaby monitoring. Predator control via shooting appears preferable to baiting, which may have negative effects by removing dingoes, which prey on the competing kanyala. Implications Predator control via shooting is an effective way to support warru populations, and repeated scat counts are an effective monitoring approach for warru.
Eumelanin & keratin sourced from waste: unraveling criss-cross functionalities for green electronic applications
Authors: Ambrico Marianna , Mattiello Sara , Mostert Albertus Bernardus , Phua Jun Wei , Aceto Domenico , Ambrico Paolo F , Guzzini Alessandro , De Stradis Angelo , Liuzzi Federico , Santulli Carlo , Lupidi Giulio , Del Giudice Alessandra , Gunnella Roberto 
Published: January 2025

Abstract
In the framework of the Circular Economy this study provides a detailed analysis of water-based suspensions of two biopolymers derived by sustainable processes: eumelanin from insect farming and keratin from chicken feathers. The latter material was obtained via two different extraction procedures. Colloidal-like suspensions were produced in water either as a single component system or a mixture of both in selected ratios, taking advantage of their high solubility. The suspensions were examined using a comprehensive set of chemical, structural and dielectric techniques to gather information on their properties. Small-Angle x-ray Scattering results provided insights into the elemental polymer sections within the suspension, while Transmission Electron Microscopy images indicate that keratin is the component driving the shape of the aggregation structure in a colloidal environment, and, in some cases, eumelanin internalization. Furthermore, the co-presence of both polymers in water determines the aggregation dimensions and shapes. The discussion focuses on the influence of the aggregation on the dielectric proper-ties by comparing the former to the AC dynamic response returned by Broadband Dielectric Spectroscopy (BDS). Within the BDS framework various items are highlighted including dielectric relaxations, screening effects, counterion condensation and ionic charge transport. The results shown in this work let to foresee the adoption of water or biofriendly aqueous BSF-EuM:Keratin suspensions in the production of devices and sensors with low environmental impact.
Feature-enhanced few-shot method for bearing fault diagnosis based on dynamic sparse attention under noise conditions
Authors: Li Yibing , Duan Qiping , Jiang Li 
Published: January 2025

Abstract
Recent advancements in deep learning techniques have significantly improved methods for diagnosing bearing faults. However, most of these methods have poor generalization performance when there are insufficient labeled samples and therefore cannot identify the root causes of bearing failures, especially in noisy environments. Hence, the study proposes a novel feature-enhanced few-shot method for bearing fault diagnosis based on dynamic sparse attention, which prioritizes feature extraction and noise resilience over complex model structures. The method incorporates a dynamic sparse attention mechanism to focus on critical features while suppressing noise efficiently, enabling robust performance in noisy environments and few-shot scenarios. By leveraging continuous wavelet transform, raw signals are transformed into denoised 2D time-frequency representations, enhancing the quality of input data. These representations are processed through a hybrid framework that combines the lightweight and pre-trained EfficientNetV2 with a BiFormer module powered by dynamic sparse attention, ensuring effective feature prioritization and computational efficiency. The proposed method also integrates transfer learning, improving generalization on unseen datasets with minimal labeled samples. The effectiveness of the proposed algorithm was evaluated on the two well-known public fault data sets in environments with high noise and data scarcity. Compared with existing studies, the proposed method shows good diagnostic accuracy and robustness. The proposed method demonstrates exceptional accuracy across varying noise in case study 1. The method still performs well in case study 2, achieving 98.15% accuracy in full-shot learning and demonstrating strong resilience in few-shot scenarios, significantly surpassing competitors, even with limited data availability.
Development of industrial soft sensor based on semi-supervised probabilistic mixture of echo state networks
Authors: Li Xu , Sun Dianhui , Han Wenxue , Shao Weiming 
Published: January 2025

Abstract
The echo state network (ESN) is considered to be an effective tool for soft sensor development owing to its advantages in handling process dynamics and nonlinearities. However, the representation capabilities of a single ESN model are limited for complex processes, leading the ESN-based soft sensors to a compromised performance. Furthermore, the scarcity of labeled samples in industrial processes makes it difficult to fully utilize the advantages of the ESN. In view of this, a novel semi-supervised probabilistic mixture of the ESN (the SsPMESN) is proposed in this paper. In the SsPMESN, multiple localized ESNs are established, which addresses the shortcomings of a single ESN model while avoiding employing the complex deep ESN (DESN). In addition, an efficient variational inference (VI)-based parameter learning algorithm is developed to train the SsPMESN. The performance of the SsPMESN is verified through both numerical and industrial examples. On the debutanizer column process, the SsPMESN-based soft sensor lifts the value of the generalization R
2 index to as high as over 0.9, showing the effectiveness and applicability of the SsPMESN in soft sensor modeling for dynamic industrial processes.
Fixed-time synchronization of kuramoto-oscillator networks with a simpler non-chattering controller
Authors: Cai Yuchen , Liu Xiaoting , Yin Xiangxin , Wu Jie , Sun Yongzheng 
Published: January 2025

Abstract
In this paper, Kuramoto-oscillator networks with identical and non-identical oscillators are studied in terms of fixed-time phase agreement and frequency synchronization. Different from traditional fixed-time controllers, we propose a simpler non-chattering controller that does not contain a sign function to overcome the chattering phenomenon. Additionally, the controller does not include a linear part, enhancing simplicity and practical convenience. The upper time bound of synchronization is estimated, and sufficient conditions for realizing fixed-time synchronization are derived using stability theory. Simulation results show the validity and correctness of our theoretical analyses. Finally, we examine the influence of control parameters on synchronization time.
Fresnel diffraction lithography for fabrication of plasmonic lenses with focal length tunability: a numerical study
Authors: Chen Jingwei , Jiang Zhongjun , He Wei , Wang Liang 
Published: January 2025

Abstract
A plasmonic lens (PL) has the potential to match the different length scales associated with photonics and electronics due to its subwavelength focusing ability. Most PL fabrication schemes utilize focus ion beam milling or e-beam lithography. However, PL fabrication through the aforementioned methods has a low throughput and a high operating cost, making it difficult to scale up for mass production. Here, we numerically report a PL fabrication scheme using Fresnel diffraction lithography, in which photolithography is performed using the focusing field of the radially polarized (RP) Fresnel diffraction field by an oil-immersion lens. We demonstrate the tunability of our proposed method, allowing the focal length of the PL to be adjusted from 0.4 μm to 2.5 μm by modifying the lithography process condition. We also show that our method is capable of fabricating bifocal PLs, and the relative intensity ratio between two foci is also adjustable. Our method provides a truly convenient and economical way of fabricating PLs with focal length tunability.
Consensus Tracking Control of Incommensurate Fractional Order Multiagent Systems Using Sliding Mode for Secure Communication Systems
Authors: Sharafian Amin , Ghandi Farzaneh , Ali Ahmad , Ullah Inam , Zhang Bo , Bai Xiaoshan 
Published: January 2025

Abstract
This paper presents a novel approach to secure communication systems leveraging the chaotic behavior of incommensurate fractional-order systems. The primary challenge addressed is the design of a secure and cost-efficient communication framework that ensures robust performance under uncertainties and disturbances. Unlike conventional methods that rely on single long-range transmitters, we propose a distributed system with multiple short-range transmitters. This innovation significantly enhances reliability by reducing the risk of single-point failure and lowers operational costs. To ensure security, we introduce a unique technique wherein the parameters and fractional orders of incommensurate chaotic systems are used as cryptographic keys for message encoding and decoding. To realize this, we develop a leader-follower consensus tracking methodology tailored for incommensurate fractional-order multi-agent systems. An adaptive Radial Basis Function (RBF) neural network-based sliding mode control is designed under a Lyapunov framework to estimate system uncertainties and compensate for dynamic disturbances. The effectiveness of the proposed system is demonstrated through simulations utilizing fractional Duffing and Arneodo systems. Results highlight rapid system response, the absence of overshoot in the closed-loop system, and the successful elimination of external disturbances in control design. These findings validate the practicality and robustness of the proposed approach, establishing a secure and stable communication framework based on incommensurate fractional-order chaotic systems. These results confirm the viability of our approach to ensure a stable and secure communication based on chaotic systems.
Switching from perfect absorption to plasmon induced transparency in graphene-vanadium dioxide metamaterials with high sensitivity
Authors: Wang Jianping , Fan Chunzhen 
Published: January 2025

Abstract
A multifunctional metamaterial, composed of patterned graphene layer atop the dielectric and vanadium dioxide (VO2) layer has been proposed. It can switch from a perfect absorption to plasmon induced transparency (PIT) as the VO2 transits from the metallic state into the dielectric state. By adjusting graphene’s Fermi energy, the perfect absorption can be finely tuned from a single-band to a dual-band. PIT occurs when the VO2 is in the dielectric state and the transparency window blue-shifts with a higher Fermi energy. Notably, it demonstrates the sensing ability and the resonant peaks embody a linear tendency with different substrates or embedding solutions. Thus, our findings not only provide new perspectives on the innovative design of multifunctional metamaterials but also underscore their potential applications in filters, optoelectronic detectors, and environmental monitors.
Dynamical analysis and DSP implementation of discrete memristor coupled discrete bi-neuron Hopfield neural networks
Authors: Liu Deheng , Cao Yinghong , Mou Jun , Alharbi khalid H 
Published: January 2025

Abstract
Among the studies on neural modeling of the human brain, Hopfield neural network (HNN) is more famous and has been widely analyzed and studied. However, discrete HNN has been studied relatively less. The study of coupling into a memristor in a discrete HNN is even rarer. In this paper, a memristor model is proposed to introduce discrete HNN to simulate synapses. And there is crosstalk between the memristors. In turn, a discrete memristor coupled discrete bi-neuron HNN (DMCBHNN) model is constructed. Using various methods such as bifurcation diagrams (BD), Lyapunov exponential spectra (LEs), phase diagrams, and chaotic sequences, the extensive and complex dynamical behavior of the model is highlighted. It includes hyperchaos, chaos, cycles, attractor coexistence, complexity, firing patterns, and state transfer. In addition, the hardware implementation of DMCBHNN is completed by using DSP platform. The feasibility of the system is verified. This provides a basis for studying the complex workings of the human brain.
EMG-based wake gestures eliminate false activations during out-of-set activities of daily living: an online myoelectric control study
Authors: Eddy Ethan , Campbell Evan , Bateman Scott , Scheme Erik 
Published: January 2025

Abstract

Objective. While myoelectric control has been commercialized in prosthetics for decades, its adoption for more general human–machine interaction has been slow. Although high accuracies can be achieved across many gestures, current control approaches are prone to false activations in real-world conditions. This is because the same electromyogram (EMG) signals generated during the elicitation of gestures are also naturally activated when performing activities of daily living (ADLs), such as when driving to work or while typing on a keyboard. This can lead the myoelectric control system, which is trained on a closed set of gestures and thus unaware of the muscle activity associated with these ADLs, to be falsely activated, leading to erroneous inputs and user frustration. Approach. To overcome this problem, the concept of wake gestures, whereby users could switch between a dedicated control mode and a sleep mode by snapping their fingers, was explored. Using a simple dynamic time warping model, the real-world user-in-the-loop efficacy of wake gestures as a toggle for myoelectric interfaces was demonstrated through two online ubiquitous control tasks with varying levels of difficulty: (1) dismissing an alarm and (2) controlling a robot. Main results. During these online evaluations, the designed system ignored almost all (

>

99.9%) non-target EMG activity generated during a set of ADLs (i.e. walking, typing, writing, phone use, and driving), ignored all control gestures (i.e. wrist flexion, wrist extension, hand open, and hand close), and enabled reliable mode switching during intentional wake gesture elicitation. Additionally, questionnaires revealed that participants responded well to the use of wake gestures and generally preferred false negatives over false positives, providing valuable insights into the future design of these systems. Significance. These results highlight the real-world viability of wake gestures for enabling the intermittent use of myoelectric control, opening up new interaction possibilities for EMG-based inputs.
Social Network Interaction Mapping and the Impact of Land Use Change in Malino Tourism Area, Gowa Regency, Indonesia
Authors: Abbas Jamilah , Baja Sumbangan , Neswati Risma , Yamin Muhammad , Rahmat Syaeful 
Published: January 2025

Abstract
In recent years, Malino has experienced rapid development as a tourist destination. This is characterized by the increasing number of visitors and the development of tourist infrastructure. With its development as a tourist destination, Malino has experienced significant land use changes. Forests and agricultural land are transformed into inns, restaurants, and other tourist infrastructure. The loss of flora and fauna habitat, damage to biodiversity, erosion, sedimentation, a decrease in water quality, and environmental pollution are a long list within the scope of the environmental crisis that occurs. Not only related to the environmental crisis, the impact of land use changes can also cause social conflict between communities related to access to natural resources, as well as the loss of livelihoods for people who depend on the agricultural and forestry sectors. In this study, we want to see how the dynamics of land use change that occur in the Malino tourist area affect the structure and dynamics of social networks between actors and the impact of land use change on environmental, social, and economic aspects. The method used in this research is a field survey with in-depth interviews and participatory mapping using the Arcgis Survey123 platform from Esri to visitors, local residents, and tourism managers with 130 respondents. The spatial approach was carried out to determine the extent of the dynamics of land use change identified in the scheme of village areas included in Malino tourism in Gowa Regency, including 7 villages, including Bonto Lerung Village, Bulutana Village, Kanreapia Village, Gantarang Village, Manimbahoi Village, Pattapang Village, and Malino Village. Based on the results of the field survey, 32.37 percent said that the role of the community in managing the tourist area was very important, as well as the argument that the economic impact on tourism revenue increased by about 3.62% of the usual income. However, the rate of land use changed from high-density secondary dryland forest to shrubs in the last 9 years increased to 327.01 hectares. The rate of land use changes from forested to vacant and abandoned land is 62.00 hectares, and from forested to tourist support infrastructure is about 2.72 hectares. This shows that the growth of tourism affects the loss of forest in the Malino tourism area.