bluuebunny/crossref_metadata_2025_split huggingface dataset:
ALDNet: a lightweight and efficient drone detection network
Authors: Cai Hao , Zhang Jinhong , Xu Jianlong 
Published: January 2025

Abstract
With the growing use of unmanned aerial vehicles (UAVs), it poses a potential threat to public safety, so drone detection has become an increasingly important research direction. However, the irregular shooting angles, deformations, significant target scale variations, and complex backgrounds in UAV imagery pose challenges for existing object detection models. To address these issues, we propose ALDNet, a precise and lightweight UAV image object detection network built on an improved RT-DETR model. First, we introduce the position accurate continuous convolution (PAC), which dynamically adjusts convolution kernel coordinates, allowing flexibility in detecting objects of varied shapes. PAC improve the ability of backbone network to capture objects with different shapes. Second, we present an enhanced multi-scale feature fusion approach that integrates spatial information more effectively, reducing the loss of fine-grained details during fusion. Additionally, we propose the Inner-Generalized Intersection over Union loss function, which reduces interference and accelerates the convergence of bounding box optimisation, thus improving the overall detection performance. We conducted experiments on three UAV image datasets, Det-Fly, ARD-MAV and VisDrone, and compared the ALDNet results with the RT-DETR model. The experimental results show that ALDNet achieved 98.3%, 97.4% and 48.1% mAP50 values on Det-Fly, ARD-MAV and VisDrone, which are 1.5%, 0.4% and 1.9% higher than RT-DETR, respectively, and the number of parameters and computation amount of ALDNet are 25% and 14% less than the baseline, respectively. Experimental results show that ALDNet achieves greater efficiency and effectiveness with less computational power.
Mean field limits of particle-based stochastic reaction-drift-diffusion models*
Authors: Heldman M , Isaacson S A , Liu Q , Spiliopoulos K 
Published: January 2025

Abstract
We consider particle-based stochastic reaction-drift-diffusion models where particles move via diffusion and drift induced by one- and two-body potential interactions. The dynamics of the particles are formulated as measure-valued stochastic processes (MVSPs), which describe the evolution of the singular, stochastic concentration fields of each chemical species. The mean field large population limit of such models is derived and proven, giving coarse-grained deterministic partial integro-differential equations (PIDEs) for the limiting deterministic concentration fields’ dynamics. We generalize previous studies on the mean field limit of models involving only diffusive motion, with care to formulating the MVSP representation to ensure detailed balance of reversible reactions in the presence of potentials. Our work illustrates the more general set of PIDEs that arise in the mean field limit, demonstrating that the limiting macroscopic reactive interaction terms for reversible reactions obtain additional nonlinear concentration-dependent coefficients compared to the purely diffusive case. Numerical studies are presented which illustrate that two-body repulsive potential interactions can have a significant impact on the reaction dynamics, and also demonstrate the empirical numerical convergence of solutions to the PBSRDD model to the derived mean field PIDEs as the population size increases.
Fast spot order optimization to increase dose rates in scanned particle therapy FLASH treatments
Authors: Wase Viktor , Widenfalk Oscar , Nilsson Rasmus , Fälth Claes , Fredriksson Albin 
Published: January 2025

Abstract
The advent of ultra-high dose rate irradiation, known as FLASH radiation therapy, has shown promising potential in reducing toxicity while maintaining tumor control. However, the clinical translation of these benefits necessitates efficient treatment planning strategies. This study introduces a novel approach to optimize proton therapy for FLASH effects using traveling salesperson problem (TSP) heuristics. We applied these heuristics to optimize the arrangement of proton spots in treatment plans for 26 prostate cancer patients, comparing the performance against conventional sorting methods and global optimization techniques. Our results demonstrate that TSP-based heuristics significantly enhance FLASH coverage to the same extent as the global optimization technique, but with computation times reduced from hours to a few seconds. This approach offers a practical and scalable solution for enhancing the effectiveness of FLASH therapy, paving the way for more effective and personalized cancer treatments. Future work will focus on further optimizing run times and validating these methods in clinical settings.
Cross-scale turbulence in space plasmas: old concepts, recent findings, and future challenges
Authors: Alberti Tommaso , Benella Simone , Stumpo Mirko , Sorriso-Valvo Luca , Carbone Vincenzo 
Published: January 2025

Abstract
Turbulence, a fascinating and intricate phenomenon, has captivated scientists over different domains, mainly for its complex cross-scale nature spanning a wide range of temporal and spatial scales. Despite significant advances in theories and observations in the last decades, some aspects of turbulence still remain unsolved, motivating new efforts to understand its underlying physical mechanisms and refine mathematical theories along with numerical models. This topical review explores recent findings from the Parker Solar Probe mission, providing a distinctive opportunity to characterize solar wind features at varying heliocentric distances. Analyzing the radial evolution of magnetic and velocity field fluctuations across the inertial range, a transition has been evidenced from local to global self-similarity as proximity to the Sun increases. This behavior has been reconciled with magnetohydrodynamic theory revising an old concept by emphasizing the evolving nature of the coupling between fields. This offers inspiration for novel modeling approaches to understand open challenges in interplanetary plasma physics as the heating and acceleration of the solar wind, as well as, its evolution within the inner Heliosphere.
Perpendicular magnetic anisotropy of Pd/Co2MnSi/Co/Pd multilayer
Authors: Qin Xiaoqi , Tan Jiaxing , Xiu Xianwu , Cao Wentian , Wang Shuyun 
Published: January 2025

Abstract
Pd/Co2MnSi(CMS)/Co/Pd multilayer films were designed based on the idea of combining highly spin-polarized materials with strong perpendicular magnetic anisotropy(PMA) films. The PMA of Pd/CMS/Co/Pd multilayer films were studied by optimizing the growth conditions and thickness of each film layer. The optimal structure of the multilayer films were Pd(6 nm)/CMS(5 nm)/Co(2 nm)/Pd(1 nm). Its Abnormal Hall resistance (R
Hall), coercivity (H
c) and effective magnetic anisotropy constant (K
eff) are 0.08Ω, 284Oe and 1.36Merg/cm3, respectively, which are 100%, 492%, and 183% higher than the corresponding values (0.04Ω, 48Oe, and 0.48Merg/cm3) of the Pd (6 nm)/Co (1 nm)/Pd (3 nm) trilayer films. The analysis shows that the increase of the above values are the result of Pd/CMS interface effect and CMS/Co interface ferromagnetic coupling, and it is closely related to the thickness of each film layer in the multilayer films and the growth conditions of the multilayer films.
Community stakeholder perspectives for empowering EJ initiatives through Public Participation Geographic Information Systems (PPGIS)
Authors: Rice-Boayue Jacelyn , Garo Laurie , Ilboudo Nebie Elisabeth 
Published: January 2025

Abstract
This study explores the use of Public Participation Geographic Information Systems (PPGIS) to support environmental justice (EJ) efforts in Charlotte, North Carolina by incorporating community knowledge and engagement. Through a workshop with representatives from community-based organizations (CBOs), participants learned about PPGIS, NASA remote sensing data, and environmental screening tools. A hands-on web-Geographic Information Science (GIS) demonstration allowed them to identify how PPGIS might address challenges in their EJ efforts. Using a mixed-methods approach, both surveys and focus group discussions were conducted to collect community and individual perspectives on the strategic implications of incorporating PPGIS into current EJ efforts. Thematic analysis of the focus groups revealed key themes of community engagement and representation, challenges with coordination, the power of GIS and data, political and policy advocacy, and holistic and intersectional approaches. Descriptive statistics and comparative insights from survey data revealed nuances in individual CBO representative’s perceived strengths, weaknesses, opportunities and threats, complementing focus group narratives. Assessment of the strengths, weaknesses, opportunities, and threats of current efforts showed that coalition building, community involvement, and local knowledge were key strengths. In contrast, weaknesses included a perceived lack of influence over decision-makers and difficulty securing funding. The study concludes that PPGIS could strategically enhance community mobilization, facilitate collaboration, and advocate for policy change.
Optimization and design for multi-valued quantum comparator circuits
Authors: Zhang Tingyan , Li Yi , Lu Sijun , Ai Jingwen , Bai Mingqiang , Mo Zhiwen , Du Wenbo , Jiang Pengheng , Liu Jiawei 
Published: January 2025

Abstract
Multi-valued quantum systems have more significant advantages in computational performance than binary quantum system, since the circuit design is more compact and efficient in multi-valued quantum systems. Hence, synthesizing multi-valued logic circuits is a better choice for future quantum computing technology. A subcircuit in the Grover’s algorithm is called an oracle, which inputs a set of quantum qudits and gives an output according to the search conditions. Greater-than/less-than/equality comparators are widely used in search conditions. In this paper, the ternary Toffoli gate proposed by Monfared and Haghparast is extended to multi-valued under certain conditions, and the existing optimal quaternary n-qudit comparator is optimized using the multi-valued Toffoli gate. In addition, we design universal multi-valued equality/greater-than/less-than comparators and complementary component, which constitute a comprehensive multi-valued n-qudit comparator. Compared to existing comparator circuits, these comparator circuits are more efficient in terms of quantum cost, garbage output, hardware complexity, and constant input.
On particular integrability for (co)symplectic and (co)contact Hamiltonian systems
Authors: Azuaje R , Escobar-Ruiz A M 
Published: January 2025

Abstract
As a generalization and extension of our previous paper (Escobar-Ruiz and Azuaje 2024 J. Phys. A: Math. Theor.
57 105202), in this work, the notions of particular integral and particular integrability in classical mechanics are extended to the formalisms of cosymplectic, contact and cocontact geometries. This represents a natural framework for studying dissipative systems, enabling a reduction of the equations of motion and, in certain cases, allowing explicit solutions to be found within a subset of the overall dynamics where integrability conditions are met. Specifically, for Hamiltonian systems on cosymplectic, contact and cocontact manifolds, it is demonstrated that the existence of a particular integral allows us to find certain integral curves from a reduced, lower dimensional, set of Hamilton’s equations. In the case of particular integrability, these trajectories can be obtained by quadratures. Notably, for dissipative systems described by contact geometry, a particular integral can be viewed as a generalization of the important concept of dissipated quantity as well.
Relative descriptors for quantum agents
Authors: Möckli David , Perraro Lorenzo Spies 
Published: January 2025

Abstract
We use the Heisenberg picture of Everettian quantum mechanics to work out the relative descriptors for the Frauchiger–Renner thought experiment. While Everettian mechanics reveals no paradox within the thought experiment, the decoherence-free setup offers an instructive branching tree. Traditionally, branching structures derived from the Schrödinger picture suggest that foliations are always sharply defined. However, the Heisenberg picture demonstrates that the tree contains regions with inherently non-sharp foliations, leading to the conclusion that, in Everettian mechanics, quantum agents possess a history with a non-sharp memory registry.
Current methods for halitosis diagnosis and the impact of COVID-19 pandemic: an international survey
Authors: Laleman Isabelle , Dadamio Jesica 
Published: January 2025

Abstract
Halitosis specialists can be found all over the world, but very little is known about how they approach patients with halitosis complaints. Therefore, this web-based questionnaire study tried to reach as many of them to gain insight in their methods and tools used to diagnose the condition. Since this study was carried out in the aftermath of the COVID-19 pandemic, its impact was also examined. This survey encompassed 19 questions interrogating the responders’ profile; their diagnostic process in general; the methods and tools used to examine the breath; and the impact of COVID-19 on them. It was accessible online from May till October 2022. Eighty halitosis professionals from 19 different countries replied. Their answers showed that the community behind the field of halitosis seems to be largely driven by oral health professionals. The respondents had been active in this niche for on average 12 years in consultations (41%), research (23%) or a combination (36%). To achieve a diagnosis 96% believed a thorough history is a must and 94% felt that a breath odor examination (instrumental and/or organoleptically) was necessary. The Halimeter® was the most common instrument used for breath odor analysis. There was a large variation in the organoleptic examination regarding the calibration and number of judges and the specific odors sources that were assessed (i.e. mouth odor versus nose odor). Less variation was noted on the rating scale used: 87% made use of the 6-point odor strength scale. For those that performed organoleptic examinations COVID-19 forced them to modify their examination (20%) or to stop performing it (67%). This international survey showed that there is not a consensus between specialists on how the diagnosis of halitosis should be carried out. However, a common thread can be noted: thoroughly interviewing the patients and examining the breath odor are of upmost importance.
Bibliometrics and altmetrics on halitosis: exploring the top 100 most-cited papers
Authors: Carvalho Ana Paula , Viana Karolina Skarlet Silva , Costa Fernando Oliveira , Lima Rafael Paschoal Esteves , Martins-Júnior Paulo Antônio , Cota Luís Otávio Miranda 
Published: January 2025

Abstract
Halitosis has a multifactorial etiology being of interest by different health areas. The aim of this study was to perform a bibliometric and altmetric analyzes of the top 100 most-cited papers on halitosis to provide a comprehensive view of their scientific and alternative metrics. This would give perspectives on citation dynamics and online attention of the research outputs. A search strategy was designed, tested and applied in the Web of Science database on August 1st, 2023. The 100 most-cited papers were selected by two reviewers. Data on title, year of publication, number of citations, authorship, journal title, study design, halitosis etiology and subject/field of the study or pathogenesis of halitosis were extracted from each paper. Altmetric attention score (AAS) for each paper was registered. Papers were published between 1972 and 2019. Most cited papers were non-systematic reviews (28%). USA was the country with the greatest number of publications (20%). Journals with the greater number of citations were related to dentistry. The altmetric analysis did not show correlation with the citation count but showed a few papers with elevated AAS and a good diffusion in social media. The level of evidence of the study design did not influence the citation number. This can indicate the need for citing studies with more robust designs in order to provide better scientific evidence of citations in epidemiology, etiology, diagnosis and treatment. Databases showed positive correlation among citation counts, but no correlation with the online attention.
Improving the electrical conductivity and photo-conductivity of the photo-active layer P3HT:PCBM doped by Schiffbase for organic photo-sensor applications
Authors: Al-Saymari Furat A , Fakher Sundes J , Tuma Fadhil A , Alharis Raed A , Alshawi Jasim M S , Mahdi M A , Al-Saidi Imad Al-Deen H A , Hassan Qusay M A 
Published: January 2025

Abstract
A Schiff-base material was synthesized and characterized by the 1H- and 13C-NMR, FTIR, Mass, and UV-visible spectroscopy. A thin layer of pure P3HT:PCBM and P3HT:PCBM:Schiffbase with two concentrations 2 mM and 4 mM are prepared using spin coating method. At room temperature, doping of P3HT:PCBM active-layer by Schiff-base material at concentration of 4 mM led to enhance the electrical current and conductivity by a factor of 24x under dark conditions and by a factor of 27x under white-light illumination (Io = 50 mW cm−2). The electrical current, conductivity, and resistivity are measured as a function of time under illumination for three different wavelengths, white, green, and red, proving that the photo-sensors based on P3HT:PCBM:schiffbase thin films exhibit a good reproducibility, fast-response time, and high optical-sensitivity. It was also found that the photo-electrical characterization of the photo-sensors are wavelength dependent, where, under red-light, the samples exhibit the lowest optical-response while the highest value was obtained under white-light. The study revealed that the photo-responsivity and quantum efficiency of the P3HT:PCBM:Schiffbase(4 mM) based photo-sensors exposed by white light are higher than those the corresponding values of the photo-sensors based on P3HT:PCBM by a factor of ∼31x. Moreover, the performance of the photo-sensors were improved due to depositing an ultra-thin film of carbon on top of the active-layer, exhibiting a significant enhancement in the electrical and photo-electrical properties. The photo-sensors based on P3HT:PCBM:Schiffbase/carbon-nano-sheet show a superior quantum efficiency (∼6%) with photo-responsivity of ∼24 mA W−1, confirming that the doped P3HT:PCBM active-layer are very interesting for organic optical sensors and photovoltaic devices.
Impact of surface roughness on the antimicrobial efficacy and cytotoxicity of SiO-ZnO coatings on mechanically abraded PET surfaces
Authors: Shao Nengqi , Wang Yulei , Wu Yipeng , Xu Wenhao , Feng Fanzhe , Yu Zhongzheng , Liang Jinlong , Cai Zhijun , He Xiaoqing , Zhou Hongkang , Cui Yi , Xu Yongqing 
Published: January 2025

Abstract
Surface topographical roughness plays a crucial role in enhancing biological activities by providing biomechanical stability, optimal osseointegration, and torsion resistance. However, the surface roughness impacting on the antibacterial and cytotoxicity performances are still challenges to implant applications. This study investigates the effect of surface roughening on polyethylene terephthalate (PET) using sandpaper prior to applying a SiO-ZnO nanocomposite coating. Results show that surface roughness increased from approximately 100 nm on untreated PET to 1.8 micrometers with 60-grit sandpaper, directly correlating with the grit size used. Efficacy against E. coli varied with surface roughness, with higher roughness surfaces showing only 27% efficacy, while lower roughness surfaces achieved over 95% efficacy. In contrast, antimicrobial efficacy against S. aureus was consistently high, reaching up to 99% regardless of surface roughness. Cytotoxicity tests using CCK-8 with MC3T3-E1 cells indicated increased toxicity over time, with only surfaces treated with 180-grit sandpaper exhibiting mild toxicity combined with excellent antibacterial efficacy after 7 days of culture. Excessive surface roughness (e.g. above Ra 1.8 μm) resulted in a rapid increase in cell death. Additionally, increased PET roughness improved the mechanical performance of the coating due to enhanced contact area between the coating and PET, facilitated by chemical bonding. This study demonstrates that excessive surface roughness can compromise antimicrobial performance or even lead to failure, highlighting the need to optimize surface roughness to ensure effectiveness.
An LJDRNN-based efficient energy intensity prediction in carbon fiber composite material manufacturing process
Authors: Nikhil Rangaswamy , A G Karthikeyan , Loganathan Prabhu , Khan Tabrej , Sebaey Tamer A 
Published: January 2025

Abstract
Carbon Fibers (CFs) are usually derived from a polyacrylonitrile precursor during composite fiber production. Due to high-temperature needs, the CF composite manufacturing process is considerably energy-consuming and costly. Hence, energy intensity prediction is required. Energy intensity is predicted by the prevailing research techniques; however, it is not predicted accurately. Thus, a Limit Jordan Deep Recurrent Neural Network (LJDRNN)-centric energy intensity prediction was proposed for accurately predicting the energy intensity. Primarily, the material values and processes are detected. Next, for the determined values, pre-processing is done; in addition, the components are extracted from the input values. Then, by employing the Linear Interpolated Honey Badger Optimization (LIHBO), the optimal components are selected. Next, LJDRNN predicts the energy intensity by deploying the optimal components. The proposed LJDRNN achieved an accuracy of 98.32%, outperforming the JRNN (92.10%), RNN (87%), ANN (78%), and CNN (86%), thus demonstrating its superiority in energy intensity prediction. Grounded on the performance measures, the proposed technique’s performance is weighed against the prevailing research techniques where the proposed system attained enhanced performance when analogized to the prevailing methodologies. This study is of high significance to CF producers, offering a robust tool to predict and manage energy consumption effectively. By enabling more precise energy intensity forecasting, the proposed method supports producers in optimizing their manufacturing processes, reducing energy costs, and aligning with sustainable production goals, ultimately driving greater operational efficiency and competitiveness in the CF industry.