bluuebunny/crossref_metadata_2025 huggingface dataset:
On the Sufficiency of a Single Hidden Layer in Feed-Forward Neural Networks Used for Machine Learning of Materials Properties
Authors: Thant Ye Min , Manzhos Sergei , Ihara Manabu , Nukunudompanich Methawee
Published: January 2025

Feed-forward neural networks (NNs) are widely used for the machine learning of properties of materials and molecules from descriptors of their composition and structure (materials informatics) as well as in other physics and chemistry applications. Often, multilayer (so-called “deep”) NNs are used. Considering that universal approximator properties hold for single-hidden-layer NNs, we compare here the performance of single-hidden-layer NNs (SLNN) with that of multilayer NNs (MLNN), including those previously reported in different applications. We consider three representative cases: the prediction of the band gaps of two-dimensional materials, prediction of the reorganization energies of oligomers, and prediction of the formation energies of polyaromatic hydrocarbons. In all cases, results as good as or better than those obtained with an MLNN could be obtained with an SLNN, and with a much smaller number of neurons. As SLNNs offer a number of advantages (including ease of construction and use, more favorable scaling of the number of nonlinear parameters, and ease of the modulation of properties of the NN model by the choice of the neuron activation function), we hope that this work will entice researchers to have a closer look at when an MLNN is genuinely needed and when an SLNN could be sufficient.
Josephson Junction Dynamics as a Ride on a Roller Coaster
Authors: Nappi Ciro , Camerlingo Carlo , Cristiano Roberto
Published: January 2025

We discuss the dynamics of a roller coaster cart driven by a constant force along the suspended track of a winding roller coaster. The track is assumed to be arbitrarily long and specially shaped. It is composed of semicircular track portions, in the form of valleys and hills, standing vertically in the same plane. This is a mechanical analog of Josephson junction electrodynamics. To demonstrate the explanatory potential of this analogy, we focus particularly on the conditions of de-trapping of the cart from one of the valleys of the track. This mechanical process has its analog in non-noise-generated premature switching to the finite voltage state of a Josephson junction.
Growth Promotion and Secondary Metabolites of Vegetables by Spraying Soil with Psidium guajava, Aloe vera, Allium sativum and Medicago sativa Extracts at Various Stages of Growth
Authors: Ei Ei , Park Hyun Hwa , Kuk Yong In
Published: January 2025

There is a growing need for sustainable, efficient methods to promote plant growth and protect crops, with plant extracts offering natural, multi-component solutions. Based on previous observations, Psidium guajava, Aloe vera, Allium sativum and Medicago sativa were selected from 17 water extracts to investigate how the application times of soil sprays affect the antioxidant enzymes and secondary metabolites in fruity and leafy vegetables at different growth stages. From 1 week after sowing (WAS) to 4 WAS, all applications increased the shoot fresh weight by 42–69% in cucumbers, 40–64% in tomatoes, 46–65% in kale and 42–63% in lettuce. These applications also increased the photosynthesis, flavonoids and antioxidative enzymes (ascorbate peroxide (APOD) and guaiacol peroxidase (GPOD)), which provided the plants with a balanced supply of nutrients essential for growth. In the real world, these results show that the use of natural extracts (P. guajava and A. sativum) can be a sustainable, eco-friendly alternative to synthetic fertilizers and pesticides, helping to improve crop yields and metabolism without harming the environment. This approach could reduce the reliance on chemical inputs and promote more sustainable agricultural practices, especially in controlled environments, like greenhouses, where crops like cucumbers and kale are grown.
Artemisia herba-alba Essential Oil: Chemical Composition, Phytotoxic Activity and Environmental Safety
Authors: Baranová Beáta , Gruľová Daniela , Polito Flavio , Sedlák Vincent , Konečná Mária , Blaščáková Marta Mydlárová , Amri Ismail , De Feo Vincenzo , Poráčová Janka
Published: January 2025

Weeds cause a decrease in the quantity and quality of agricultural production and economic damage to producers. The prolonged use of synthetic pesticides causes problems of environmental pollution, the possible alteration of agricultural products and problems for human health. For this reason, the scientific community’s search for products of natural origin, which are biodegradable, safe for human health and can act as valid alternatives to traditional herbicides, is growing. Essential oils can have useful implications in agriculture by acting as effective alternatives to chemical herbicides. In this work, the chemical composition of an EO from Artemisia herba-alba and its herbicidal properties were studied on two weeds (Lolium multiflorum and Trifolium pratense) and two crops (Brassica napus and Hordeum vulgare) and its environmental safety was also assessed using three model organisms: Chaoborus sp., Tubifex tubifex and Eisenia foetida. The principal component of the EO was camphor (26.02%), with α- and β-thujone (9.60 and 8.38%, respectively), 1,8-cineole (8.02%), piperitenone (5.29%) and camphene (4.95%) as the main components. The EO demonstrated variable phytotoxic effects with a dose-dependent manner, inhibiting both the germination and the radical elongation of the tested seeds, and was also found to be environmentally safe for the selected organisms. The results lay the foundation for considering this EO as a potential weed control agent.
Molecular Mechanisms of Grain Chalkiness Variation in Rice Panicles
Authors: Li Zhong , Xi Min , Xu Youzun , Sun Xueyuan , Tu Debao , Zhou Yongjin , Ji Yalan , Yang Linsheng
Published: January 2025

Grain chalkiness adversely affects rice quality, and the positional variation of grain chalkiness within a rice panicle presents a substantial obstacle to quality improvement in China. However, the molecular mechanism underlying this variation is unclear. This study conducted a genetic and physiological analysis of grains situated at distinct positions (upper, middle, and bottom primary branches of the rice panicle, denoted as Y1, Y2, and Y3) within a rice panicle using the Yangdao 6 variety. The results indicated that the percentage of chalky grains (PCG) in Y1 was the highest, i.e., 17.12% and 52.18% higher than that of Y2 and Y3, respectively. Y2 exhibited the highest degree of grain chalkiness (DGC), attributable to its greater area of endosperm chalkiness (AEC) than the others. Y3 demonstrated the lowest PCG and DGC. Additionally, Y1 and Y2 were characterized by lower amylose and protein contents, as well as looser starch granule morphology, in comparison to Y3. Compared with Y3, both the average and maximum filling rates of Y1 and Y2 increased markedly; however, the active filling duration was notably reduced by 7.10 d and 5.56 d, respectively. The analysis of genomic expression levels indicated an enrichment of starch and sucrose metabolism in Y1-vs.-Y2, Y2-vs.-Y3, and Y1-vs.-Y3, with 7 genes (5 up-regulated and 2 down-regulated), 53 genes (12 up-regulated and 41 down-regulated), and 12 genes (2 up-regulated and 10 down-regulated) in the Y1-vs.-Y2, Y2-vs.-Y3, and Y1-vs.-Y3. The majority of these genes were down-regulated, linking metabolic activity to grain filling and contributing to the occurrence of grain chalkiness in rice panicles. In conclusion, the metabolic processes associated with sucrose and starch play a crucial role in regulating grain filling and the formation of chalkiness in rice.
RAS, a Pentatricopeptide Repeat Protein, Interacts with OsTRX z to Regulate Chloroplast Gene Transcription and RNA Processing
Authors: Qiu Zhennan , Wen Shiyong , Sun Peinan , Chen Dongdong , Wang Chunmiao , Song Xiliang , Xiao Liying , Zhang Peiliang , Zhao Dongying , Wen Cuiping , Guan Peiyan , Du Xuechu , Sun Yinghui , Xu Chenshan , Song Jian
Published: January 2025

Thioredoxin z (TRX z) plays a significant role in chloroplast development by regulating the transcription of chloroplast genes. In this study, we identified a pentatricopeptide repeat (PPR) protein, rice albino seedling-lethal (RAS), that interacts with OsTRX z. This interaction was initially discovered by using a yeast two-hybrid (Y2H) screening technique and was further validated through Y2H and bimolecular fluorescence complementation (BiFC) experiments. RAS contains 16 PPR motifs and features a small MutS-related (SMR) domain at its C-terminus. CRISPR/Cas9-generated ras mutants exhibited an albino seedling-lethal phenotype characterized by abnormal chloroplast structures and a significantly reduced chlorophyll content. RAS localizes to the chloroplast and is predominantly expressed in young leaves. Mutations in RAS affect RNA editing at the rpl2, rps14, and ndhA sites, as well as RNA splicing at the rpl2, atpF, and ndhA transcripts within the chloroplast. Furthermore, the expression levels of genes associated with chloroplast formation are altered in the ras mutant. Both OsTRX z and RAS were found to interact with chloroplast signal recognition particle (cpSRP) proteins, indicating that their proper localization within the chloroplast may be dependent on the SRP pathway. Collectively, our findings highlight the critical role of RAS in chloroplast development, as it is involved in RNA processing and the regulation of chloroplast gene expression.
Flexible Vibration Sensors with Omnidirectional Sensing Enabled by Femtosecond Laser-Assisted Fabrication
Authors: Mou Yaojia , Wang Cong , Liu Shilei , Liu Linpeng , Duan Ji’an
Published: January 2025

Vibration sensors are integral to a multitude of engineering applications, yet the development of low-cost, easily assembled devices remains a formidable challenge. This study presents a highly sensitive flexible vibration sensor, based on the piezoresistive effect, tailored for the detection of high-dynamic-range vibrations and accelerations. The sensor’s design incorporates a polylactic acid (PLA) housing with cavities and spherical recesses, a polydimethylsiloxane (PDMS) membrane, and electrodes that are positioned above. Employing femtosecond laser ablation and template transfer techniques, a parallel groove array is created within the flexible polymer sensing layer. This includes conductive pathways, and integrates stainless-steel balls as oscillators to further amplify the sensor’s sensitivity. The sensor’s performance is evaluated over a frequency range of 50 Hz to 400 Hz for vibrations and from 1 g to 5 g for accelerations, exhibiting a linear correlation coefficient of 0.92 between the sensor’s voltage output and acceleration. It demonstrates stable and accurate responses to vibration signals from devices such as drills and mobile phone ringtones, as well as robust responsiveness to omnidirectional and long-distance vibrations. The sensor’s simplicity in microstructure fabrication, ease of assembly, and low cost render it highly promising for applications in engineering machinery with rotating or vibrating components.
Tuning the Shape of Spray-Dried Pullulan Particles Through Feed Rheological Behavior
Authors: Selmin Francesca , Cilurzo Francesco , Briatico Vangosa Francesco
Published: January 2025

Pullulan is a natural polysaccharide used in many health products, including dry powders for oral and pulmonary administration. In these cases, the control of the shape and dimensions of particles is crucial for obtaining the desired functionality. Different from other polysaccharides, pullulan cannot be easily shaped without chemical modifications or adjuvants’ addition. This work aims to systematically investigate the impact of the solvent composition and polymer concentration on the possibility of tuning the pullulan particle shape by spray drying. The results revealed that the microparticle-to-fiber transition can be induced using a hydro-alcoholic solution since ethanol increased the relaxation time and reduced the evaporation rate. Furthermore, a high Péclet number during drying favors the formation of wrinkled surfaces at all feed compositions. Overall, these data evidenced the possibility of tuning the spray-dried product morphology without any processing aids, paving the way for new applications of pullulan, especially in the pharmaceutical field.
Characterisation of the Overflow Pipe Structure on the Internal Flow Field of a Hydrocyclone
Authors: Wang Yanchao , Li Peiyang , Liang Zhitao , Yang Huanbo , Li Feng
Published: January 2025

The application of cyclones can be traced back to 100 years ago. Salt, an important carrier of energy exchange in the human body, is one of the essential substances. Currently, salt surface impurities are mostly removed manually, resulting in low sorting efficiency. Cyclones, as important physical separation equipment, are widely used in separating different substances. This paper focuses on using cyclones for salt decontamination. However, due to the limitations of the cyclone’s structure, ensuring grading accuracy is challenging. The flow field, as the main power source in the cyclone grading process, significantly impacts the grading effect. The overflow pipe, where fine particles exit, has a significant effect on the internal flow field. To explore the impact of the overflow pipe structure on the cyclone’s internal flow field, five overflow pipe structures were designed and numerically analyzed. The results indicate that the improved overflow tube structure has higher static pressure than the conventional linear structure. Type 2 (Parabolic) has the highest tangential velocity, which is 27.7 percentage points higher than that of the conventional cyclone, while Type 3 (hyperbola) has the lowest axial velocity(minimum value is only 0.3 m/s) and turbulence intensity(minimum value of the cone segment is only 0.2), resulting in longer particle residence time in the cyclone for better separation. Additionally, vortices are effectively avoided, improving the stability of the flow field to some extent. The obtained data provide a theoretical basis and support for the structural design of new cyclones.
Real-Time Models for Manufacturing Processes: How to Build Predictive Reduced Models
Authors: Horr Amir M. , Drexler Hugo
Published: January 2025

New data science and real-time modeling techniques facilitate better monitoring and control of manufacturing processes. By using real-time data models, industries can improve their processes and identify areas where resources are being wasted. Despite the challenges associated with implementing these data models in transient and multi-physical processes, they can significantly optimize operations, reduce trial and error, and minimize the overall environmental footprint. Implementing real-time data analytics allows industries to make quicker, informed decisions and immediate corrections to material processes. This ensures that manufacturing sustainability targets are regularly met and product quality is maintained. New concepts such as digital twins and digital shadows have been developed to bridge the gap between physical manufacturing processes and their virtual counterparts. These virtual models can be continuously updated with data from their physical counterparts, enabling real-time monitoring, control, and optimization of manufacturing processes. This paper demonstrates the predictive power of real-time reduced models within the digital twin framework to optimize process parameters using data-driven and hybrid techniques. Various reduced and real-time model-building techniques are investigated, with brief descriptions of their mathematical and analytical foundations. The role of machine learning (ML) and ML-assisted data schemes in enhancing predictions and corrections is also explored. Real-world applications of these reduced techniques for extrusion and additive manufacturing (AM) processes are presented as case studies.
Construction of Honeycomb-like ZnO/g-C3N5 Heterojunction for MB Photocatalytic Degradation
Authors: Liu Sitong , Liu Shicheng , Li Letao , Yang Letong , Wu Xiaodong , Si Zhichun , Ran Rui , Wu Hui
Published: January 2025

In this study, a combination of calcination and hydrothermal methods was employed to synthesize a honeycomb-like ZnO/g-C3N5 (ZCN) heterojunction in situ. The ZCN heterojunction photocatalyst exhibits remarkable photocatalytic degradation performance, achieving a 97% methyl blue (MB) degradation rate with the rate constant of 0.0433 min−1 (almost twice that of ZnO). Optical performance tests reveal that the ZCN heterojunction broadens the absorption edge to 710 nm and enhances the charge carrier separation. The presence of abundant oxygen vacancies, as revealed by X-ray photoelectron spectroscopy analysis, effectively suppresses the recombination of photogenerated electron–hole pairs. Furthermore, density functional theory simulations indicate that the combination of ZnO and g-C3N5 creates an internal electric field due to their differing work functions. This leads to the formation of a Z-scheme heterojunction that effectively suppresses charge carrier recombination and preserves the strong redox capabilities of ZnO and g-C3N5. Finally, electron spin resonance results indicate that O2− and OH are the primary active radicals involved in the degradation process. This study introduces a potential approach for the development of highly efficient Z-scheme photocatalysts for water treatment applications.
Evaluating YOLOv4 and YOLOv5 for Enhanced Object Detection in UAV-Based Surveillance
Authors: Alhassan Mugtaba Abdalrazig Mohamed , Yılmaz Ersen
Published: January 2025

Traditional surveillance systems often rely on fixed cameras with limited coverage and human monitoring, which can lead to potential errors and delays. Unmanned Aerial Vehicles (UAVs) equipped with object detection algorithms, such as You Only Look Once (YOLO), offer a robust solution for dynamic surveillance, enabling real-time monitoring over large and inaccessible areas. In this study, we present a comparative analysis of YOLOv4 and YOLOv5 for UAV-based surveillance applications, focusing on two critical metrics: detection speed (Frames Per Second, FPS) and accuracy (Average Precision, AP). Using aerial imagery captured by a UAV, along with 20,288 images from the Microsoft Common Objects in Context (MS COCO) dataset, we evaluate each model’s suitability for deployment in high-demand environments. The results indicate that YOLOv5 outperforms YOLOv4 with a 1.63-fold increase in FPS and a 1.09-fold improvement in AP, suggesting that YOLOv5 is a more efficient option for UAV-based detection. However, to align with recent advancements, this study also highlights potential areas for integrating newer YOLO models and transformer-based architectures in future research to further enhance detection performance and model robustness. This work aims to provide a solid foundation for UAV-based object detection, while acknowledging the need for continuous development to accommodate newer models and evolving detection challenges.
Music Drama as a Christian Parable: Mozart’s Idomeneo
Authors: Petersen Nils Holger
Published: January 2025

This article discusses Wolfgang Amadeus Mozart’s opera Idomeneo: Re di Creta (1781, to a text by Giambattista Varesco) as a Christian parable in the historical context of its genesis. Mozart’s Idomeneo is based on a short episode in François Fénelon’s Télémaque, but also on Antoine Danchet’s adaptation of this episode for the theater in his tragédie lyrique Idoménée (1712; set to music by André Campra). In important aspects, Mozart’s Idomeneo changed the narrative with a marked independence of Fénelon as well as Danchet. In recent scholarship, important new information has come to light concerning Mozart’s composition of the Oracle scene, constituting the dénouement of the music drama. Based partly on these new insights, I attempt to provide a picture of a basic spiritual intention governing Mozart’s composition of the opera for the Carnival season of 1781 at the Munich court. Mozart’s Idomeneo is a Christian sacrifice drama modeled on the Aqedah (the sacrifice of Isaac; Gen 22: 1–14), which, in Christian traditions, is understood typologically as pointing to the Passion of Christ. Oppositely, Fénélon’s and Danchet’s versions rather correspond to the biblical story of Jephthah (Judges 11: 29–30). In a brief concluding section of this article, I also discuss the contemporary cultural importance of reading a classical opera such as Mozart’s Idomeneo as a conscious product of Enlightened Christianity. In modern times, ecclesiastical boundaries and religious doctrines often seem to matter little in the music and theater culture of the Western world; classical opera is often staged more in order to respond to contemporary political or social issues than to communicate the original intentions of its creators (the so-called Regieoper). I argue that Idomeneo, with its historical intention, potentially can have an impact in a cultural theology (or a theologically informed modern worldview), and further, in dialogue with a recent volume discussing the “music of theology”, that such a role for a piece of music must be developed in concrete musical (or music dramatic) contexts, not as a general philosophical contention. Mozart’s Idomeneo may work in a modern cultural context because it functions as a parable, easily understandable also in a modern political or social context, because of its deep human (psychological) insight and the empathy brought to bear on all the characters of the opera.
Exploring the Characteristics of Modern Korean Buddhist Education: Focusing on the Religious Studies Lecture Notes from the Buddhist Central Seminary (Pulgyo Chungang Hangnim, 佛敎中央學林)
Authors: Kim Eunyoung
Published: January 2025

This study examines the identity and characteristics of modern Korean Buddhist education through an analysis of the religious studies lecture notes of a student from the Buddhist Central Seminary (Pulgyo Chungang Hangnim, 佛敎中央學林), preserved at Songgwang-sa Temple. Established in 1915 and operating until 1919, the seminary introduced a significant shift from traditional scripture-centered monastic education to a modern academic system. Western and Japanese academic traditions, religious studies, philosophy, and the general educational system influenced its curriculum. The lecture notes provide insight into the adoption of modern academic disciplines within Korean Buddhist education, revealing the influence of Japanese religious studies and Western comparative religion. They also demonstrate the possibility of early introduction of religious studies as an educational field in Korea. The seminary played a dual role as a hub for national education and reflection of the colonial context, embodying the complexities of nationalism and colonial influence during Japanese occupation. This study underscores the need for further scholarly exploration to understand the multifaceted nature of modern Korean Buddhist education and its unique role within the broader historical context of East Asian Buddhist history.
Optimal Design of Multi-Asset Options
Authors: Balbás Alejandro , Balbás Beatriz , Balbás Raquel
Published: January 2025

The combination of stochastic derivative pricing models and downside risk measures often leads to the paradox (risk, return) = (−infinity, +infinity) in a portfolio choice problem. The construction of a portfolio of derivatives with high expected returns and very negative downside risk (henceforth “golden strategy”) has only been studied if all the involved derivatives have the same underlying asset. This paper also considers multi-asset derivatives, gives practical methods to build multi-asset golden strategies for both the expected shortfall and the expectile risk measure, and shows that the use of multi-asset options makes the performance of the obtained golden strategy more efficient. Practical rules are given under the Black–Scholes–Merton multi-dimensional pricing model.
A Novel Algorithm for Estimating the Sand Dune Density of the Taklimakan Desert Based on Remote Sensing Data
Authors: Wang Mingyu , Liu Yongqiang , Li Huoqing , Wang Minzhong , Huo Wen , Liu Zonghui
Published: January 2025

The dune density is an important parameter for representing the characteristics of desert geomorphology, providing a precise depiction of the undulating topography of the desert. Owing to the limitations of estimation methods and data availability, accurately quantifying dune density has posed a significant challenge; in response to this issue, we propose an innovative model to estimate dune density using a dune vertex search combined with four-directional orographic spectral decomposition. This study reveals several key insights: (1) Taklimakan Desert distributes approximately 5.31 × 107 dunes, with a linear regression fit R2 of 0.79 between the estimated and observed values. The average absolute error and root mean square error are calculated as 25.61 n/km2 and 30.48 n/km2, respectively. (2) The distribution of dune density across the eastern, northeastern, southern, and western parts of the Taklimakan Desert is relatively lower, while there is higher dune density in the central and northern areas. (3) The observation data constructed using the improved YOLOv8s algorithm and remote sensing imagery effectively validate the estimation results of dune density. The new algorithm demonstrates a high level of accuracy in estimating sand dune density, thereby providing crucial parameters for sub-grid orographic parameterization in desert regions. Additionally, its application potential in dust modeling appears promising.
A Novel Gridless Non-Uniform Linear Array Direction of Arrival Estimation Approach Based on the Improved Alternating Descent Conditional Gradient Algorithm for Automotive Radar System
Authors: Shao Mingxiao , Fan Yizhe , Zhang Yan , Zhang Zhe , Zhao Jie , Zhang Bingchen
Published: January 2025

In automotive millimeter-wave (MMW) radar systems, achieving high-precision direction of arrival (DOA) estimation with a limited number of array elements is a crucial research focus. Compressive sensing (CS) techniques have been demonstrated to offer superior performance in DOA estimation compared to spectral estimation methods. However, traditional CS methods suffer from an off-grid effect, which causes their reconstruction results to deviate from the actual positions of the signal sources, thereby reducing the accuracy. Currently, as a gridless method, atomic norm minimization (ANM) has shown effectiveness in DOA estimation for uniform linear arrays (ULAs). However, the performance of ANM is suboptimal in non-uniform linear arrays (NULAs), and their computational efficiency is not satisfactory. In this paper, we propose a novel algorithm for DOA estimation in NULA, drawing inspiration from the alternating descent conditional gradient algorithm framework. First, we construct an atomic set based on the observation scene and select the atoms with the highest correlation to the residuals as potential signal sources for global estimation. Then, we construct a mapping function for the signal sources in the continuous domain and perform conditional gradient descent in the neighborhood of each signal source, addressing the bias introduced by the off-grid effect. We compared the proposed algorithm with ANM, Iterative Shrinkage Thresholding (IST), and Multiple Signal Classification (MUSIC) algorithms. Simulation experiments validate that the proposed algorithm effectively addresses the off-grid effect and is applicable to DOA estimation in coprime and random arrays. Furthermore, real data experiments confirm the effectiveness of the proposed algorithm.
Spatiotemporal Analysis of Atmospheric Chemical Potential Anomalies Associated with Major Seismic Events (Ms ≥ 7) in Western China: A Multi-Case Study
Authors: Jiao Qijun , Liu Qinqin , Lin Changgui , Jing Feng , Li Jiajun , Tian Yuxiang , Zhang Zhenxia , Shen Xuhui
Published: January 2025

Focusing on major earthquakes (EQs; MS ≥ 7) in Western China, this study primarily analyzes the fluctuation in Atmospheric Chemical Potential (ACP) before and after the Wenchuan, Yushu, Lushan, Jiuzhaigou, and Maduo EQs via Climatological Analysis of Seismic Precursors Identification (CAPRI). The distribution of vertical ACP revealed distinct altitude-dependent characteristics. The ACP at lower atmospheric layers (100–2000 m) exhibited a high correlation, and this correlation decreased with increasing altitude. Anomalies were detected within one month prior to each of the five EQs studied, with the majority occurring 14 to 30 days before the events, followed by a few additional anomalies. The spatial distribution of anomalies is consistent with the distribution of fault zones, with noticeable fluctuation in surrounding areas. The ACP at an altitude of 200 m gave a balance between sensitivity to seismic signals and minimal surface interference and proved to be optimal for EQ monitoring in Western China. The results offer a significant reference for remote sensing studies related to EQ monitoring and the Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) model, thereby advancing our understanding of pre-seismic atmospheric variations in Western China.
Optimization of Ultra Lightweight Mirror and Opto-Mechanical–Thermal Coupling Analysis Based on Solar Thermal Radiation
Authors: Dong Quanliang , Yang Jinhe , Zhang Tong , Wang Xiaoming
Published: January 2025

To improve maneuverability, the focus of photoelectric theodolites is on reducing the weight of the primary mirror and enhancing its optical performance. This study uses MOAT and Sobol methods to identify key parameters that affect design. Using the high-sensitivity part as the optimization domain, six optimization results were obtained based on the multi-objective SIMP topology optimization method and synthesized into a compromise optimization structure. The performance of the mirror before and after optimization was compared on the opto-mechanical–thermal level. Modal analysis shows the optimized structure has a first natural frequency of 716.84 Hz, indicating excellent stiffness and avoiding low-frequency resonance, with a 30.37% weight reduction. Optical performance is also improved, with a 6 μm reduction in the spot diagram radius and an 8.95 nm decrease in RMS. Simulations under real-world conditions show that the lightweight mirror performs better in resisting gravity deformation and maintaining imaging quality. At maximum thermal deformation, the spot diagram radius of the optimized mirror is 1521.819 μm, with only a 0.145% difference in imaging quality compared to the original. In conclusion, the optimized structure shows comprehensive advantages. Constructing the optical system components and the real physical environment of the site provides a valuable reference for the optimization and analysis of the mirror.
Implementation and Testing of V2I Communication Strategies for Emergency Vehicle Priority and Pedestrian Safety in Urban Environments
Authors: Oliva Federica , Landolfi Enrico , Salzillo Giovanni , Massa Alfredo , D’Onghia Simone Mario , Troiano Alfredo
Published: January 2025

This paper explores the development and testing of two Internet of Things (IoT) applications designed to leverage Vehicle-to-Infrastructure (V2I) communication for managing intelligent intersections. The first scenario focuses on enabling the rapid and safe passage of emergency vehicles through intersections by notifying approaching drivers via a mobile application. The second scenario enhances pedestrian safety by alerting drivers, through the same application, about the presence of pedestrians detected at crosswalks by a traffic sensor equipped with neural network capabilities. Both scenarios were tested at two distinct intelligent intersections in Lioni, Avellino, Italy, and demonstrated notable effectiveness. Results show a significant reduction in emergency vehicle response times and a measurable increase in driver awareness of pedestrians at crossings. The findings underscore the potential of V2I technologies to improve traffic flow, reduce risks for vulnerable road users, and contribute to the advancement of safer and smarter urban transportation systems.
Advancing Platelet Research Through Live-Cell Imaging: Challenges, Techniques, and Insights
Authors: Tan Yuping Yolanda , Liu Jinghan , Su Qian Peter
Published: January 2025

Platelet cells are essential to maintain haemostasis and play a critical role in thrombosis. They swiftly respond to vascular injury by adhering to damaged vessel surfaces, activating signalling pathways, and aggregating with each other to control bleeding. This dynamic process of platelet activation is intricately coordinated, spanning from membrane receptor maturation to intracellular interactions to whole-cell responses. Live-cell imaging has become an invaluable tool for dissecting these complexes. Despite its benefits, live imaging of platelets presents significant technical challenges. This review addresses these challenges, identifying key areas in need of further development and proposing possible solutions. We also focus on the dynamic processes of platelet adhesion, activation, and aggregation in haemostasis and thrombosis, applying imaging capacities from the microscale to the nanoscale. By exploring various live imaging techniques, we demonstrate how these approaches offer crucial insights into platelet biology and deepen our understanding of these three core events. In conclusion, this review provides an overview of the imaging methods currently available for studying platelet dynamics, guiding researchers in selecting suitable techniques for specific studies. By advancing our knowledge of platelet behaviour, these imaging methods contribute to research on haemostasis, thrombosis, and platelet-related diseases, ultimately aiming to improve clinical outcomes.
Simultaneous Classification of Objects with Unknown Rejection (SCOUR) Using Infra-Red Sensor Imagery
Authors: Cuellar Adam , Brignac Daniel , Mahalanobis Abhijit , Mikhael Wasfy
Published: January 2025

Recognizing targets in infra-red images is an important problem for defense and security applications. A deployed network must not only recognize the known classes, but it must also reject any new or unknown objects without confusing them to be one of the known classes. Our goal is to enhance the ability of existing (or pretrained) classifiers to detect and reject unknown classes. Specifically, we do not alter the training strategy of the main classifier so that its performance on known classes remains unchanged. Instead, we introduce a second network (trained using regression) that uses the decision of the primary classifier to produce a class conditional score that indicates whether an input object is indeed a known object. This is performed in a Bayesian framework where the classification confidence of the primary network is combined with the class-conditional score of the secondary network to accurately separate the unknown objects from the known target classes. Most importantly, our method does not require any examples of OOD imagery to be used for training the second network. For illustrative purposes, we demonstrate the effectiveness of the proposed method using the CIFAR-10 dataset. Ultimately, our goal is to classify known targets in infra-red images while improving the ability to reject unknown classes. Towards this end, we train and test our method on a public domain medium-wave infra-red (MWIR) dataset provided by the US Army for the development of automatic target recognition (ATR) algorithms. The results of this experiment show that the proposed method outperforms other state-of-the-art methods in rejecting the unknown target types while accurately classifying the known ones.
A Comprehensive Review of Vision-Based Sensor Systems for Human Gait Analysis
Authors: Han Xiaofeng , Guffanti Diego , Brunete Alberto
Published: January 2025

Analysis of the human gait represents a fundamental area of investigation within the broader domains of biomechanics, clinical research, and numerous other interdisciplinary fields. The progression of visual sensor technology and machine learning algorithms has enabled substantial developments in the creation of human gait analysis systems. This paper presents a comprehensive review of the advancements and recent findings in the field of vision-based human gait analysis systems over the past five years, with a special emphasis on the role of vision sensors, machine learning algorithms, and technological innovations. The relevant papers were subjected to analysis using the PRISMA method, and 72 articles that met the criteria for this research project were identified. A detailing of the most commonly used visual sensor systems, machine learning algorithms, human gait analysis parameters, optimal camera placement, and gait parameter extraction methods is presented in the analysis. The findings of this research indicate that non-invasive depth cameras are gaining increasing popularity within this field. Furthermore, depth learning algorithms, such as convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, are being employed with increasing frequency. This review seeks to establish the foundations for future innovations that will facilitate the development of more effective, versatile, and user-friendly gait analysis tools, with the potential to significantly enhance human mobility, health, and overall quality of life. This work was supported by [GOBIERNO DE ESPANA/PID2023-150967OB-I00].
A Method to Evaluate Orientation-Dependent Errors in the Center of Contrast Targets Used with Terrestrial Laser Scanners
Authors: Muralikrishnan Bala , Lu Xinsu , Gregg Mary , Shilling Meghan , Czapla Braden
Published: January 2025

Terrestrial laser scanners (TLS) are portable dimensional measurement instruments used to obtain 3D point clouds of objects in a scene. While TLSs do not require the use of cooperative targets, they are sometimes placed in a scene to fuse or compare data from different instruments or data from the same instrument but from different positions. A contrast target is an example of such a target; it consists of alternating black/white squares that can be printed using a laser printer. Because contrast targets are planar as opposed to three-dimensional (like a sphere), the center of the target might suffer from errors that depend on the orientation of the target with respect to the TLS. In this paper, we discuss a low-cost method to characterize such errors and present results obtained from a short-range TLS and a long-range TLS. Our method involves comparing the center of a contrast target against the center of spheres and, therefore, does not require the use of a reference instrument or calibrated objects. For the short-range TLS, systematic errors of up to 0.5 mm were observed in the target center as a function of the angle for the two distances (5 m and 10 m) and resolutions (30 points-per-degree (ppd) and 90 ppd) considered for this TLS. For the long-range TLS, systematic errors of about 0.3 mm to 0.8 mm were observed in the target center as a function of the angle for the two distances (5 m and 10 m) at low resolution (28 ppd). Errors of under 0.3 mm were observed in the target center as a function of the angle for the two distances at high resolution (109 ppd).
L-Shaped Coplanar Strip Dipole Antenna Sensor for Adulteration Detection
Authors: Menon Sreedevi K. , Donelli Massimo
Published: January 2025

The present study proposes an L-shaped coplanar strip dipole antenna for sensing the presence of adulterants in liquid food samples. The proposed antenna dimensions are optimized using ANSYS HFSS, and a prototype is fabricated and validated. The sensing region is optimized based on the current distribution and measured reflection coefficients. Adulterant detection is performed by monitoring the variation in the reflection coefficient and resonance frequency of the antenna sensor. To verify the effectiveness of the proposed planar dipole as a sensor, an adulterant, which is hydrogen peroxide, is added to various liquid samples – milk, pineapple juice, and mango juice. The reflection coefficient of the antenna sensor is found to vary with various concentrations of the samples in the study. The sensitivity analysis of the antenna sensor and the repeatability of the results is also analyzed in the work. The experimental analysis assures the use of the proposed antenna as a sensor for the detection of adulterants in liquid food samples.
Enhancing Off-Road Topography Estimation by Fusing LIDAR and Stereo Camera Data with Interpolated Ground Plane
Authors: Sten Gustav , Feng Lei , Möller Björn
Published: January 2025

Topography estimation is essential for autonomous off-road navigation. Common methods rely on point cloud data from, e.g., Light Detection and Ranging sensors (LIDARs) and stereo cameras. Stereo cameras produce dense point clouds with larger coverage but lower accuracy. LIDARs, on the other hand, have higher accuracy and longer range but much less coverage. LIDARs are also more expensive. The research question examines whether incorporating LIDARs can significantly improve stereo camera accuracy. Current sensor fusion methods use LIDARs’ raw measurements directly; thus, the improvement in estimation accuracy is limited to only LIDAR-scanned locations The main contribution of our new method is to construct a reference ground plane through the interpolation of LIDAR data so that the interpolated maps have similar coverage as the stereo camera’s point cloud. The interpolated maps are fused with the stereo camera point cloud via Kalman filters to improve a larger section of the topography map. The method is tested in three environments: controlled indoor, semi-controlled outdoor, and unstructured terrain. Compared to the existing method without LIDAR interpolation, the proposed approach reduces average error by 40% in the controlled environment and 67% in the semi-controlled environment, while maintaining large coverage. The unstructured environment evaluation confirms its corrective impact.
Playing for the Planet? A Serious Game Approach to Land Use Planning with Students in Rural Iceland
Authors: Hennig Benjamin D. , Roberts Ben F. , Welling Johannes T. , Pinal Marissa , Ólafsson Jón
Published: January 2025

Effective nature conservation and citizen participation are essential for sustainable development and biodiversity preservation. This paper introduces the ‘Land Use Game’, a prototype serious game designed to engage citizens—particularly younger demographics—in participatory land use planning. Developed within the context of the EU Horizon 2020 PHOENIX project, the game was tested with students in two rural Icelandic municipalities as part of a pilot study. The game enables participants to assign land use preferences through interactive mapping, supporting a better understanding of land use complexities while promoting active learning and dialogue. The study evaluates the game’s feasibility, technological features, and practical applications, highlighting insights from gameplay observations, participant feedback, and spatial analysis. The results demonstrate the potential of serious games to collect meaningful data, support inclusive decision-making, and empower citizens to contribute to sustainable policies. By incorporating such tools, planners can enhance public understanding, promote equitable land use, and strengthen participatory democracy.
The Impacts of the US Inflation Reduction Act on EV Supply Chains
Authors: Zhang Linghong , Shi Wence
Published: January 2025

The Inflation Reduction Act (IRA) passed by the United States in 2022 affected the global layout of electric vehicle (EV) supply chains. This paper explores the impacts of the IRA on the decisions of overseas battery suppliers and domestic EV manufacturers in the US. The main findings are that (1) the suppliers’ and manufacturers’ optimal decisions depend on the local subsidy, tariff, and battery R&D costs: tariffs (subsidies) reduce (increase) the battery R&D level for overseas (local) suppliers, EV prices, and supply chain members’ profits; (2) subsidies and tariffs are key factors in distinguishing manufacturers from overseas procurement and local procurement when R&D cost coefficients are determined; cost coefficients and service fees are the key factors for manufacturers to choose local procurement or R&D cooperation strategies; and (3) when local supply chains compete with overseas supply chains, subsidies will give the local supply chains a sales advantage while giving overseas supply chains a price advantage, and when local supply chains compete with cooperative supply chains, subsidies will give local supply chains a price disadvantage and a sales disadvantage.
The Impact of Intelligent Logistics on Logistics Performance Improvement
Authors: Ye Aishan , Cai Jiayi , Yang Zhenjie , Deng Yangyang , Li Xiaohua
Published: January 2025

The logistics industry is essential to global economic development but continues to grapple with challenges related to quality improvement, cost reduction, and efficiency enhancement. Addressing these issues is crucial for promoting high-quality growth within the sector. The emergence of intelligent logistics—leveraging automation, data analytics, and Internet of Things (IoT) technologies—offers a promising approach to transforming traditional logistics operations. This study develops a theoretical framework that integrates these intelligent logistics components to investigate their mechanisms and limitations in influencing logistics performance. Using an empirical analysis of Chinese provincial panel data, we identify significant disparities in logistics industry performance across the provinces, with most regions exhibiting an initial improvement followed by a subsequent decline. Our findings reveal a notable spatial interaction effect between intelligent logistics and logistics performance, indicating that intelligent logistics substantially enhance performance. However, the impact varies by region: it significantly promotes performance in the eastern and western regions but has a limited effect in the central and northeastern regions, potentially due to distortions in production factors and other regional specificities. Additionally, the degree of openness to the outside world positively influences logistics performance in the western region. The proposed mechanisms are validated in all regions except the eastern region. This study provides valuable insights for policymakers on leveraging intelligent logistics to improve logistics industry performance, highlighting the need for region-specific strategies to maximize the benefits of intelligent logistics technologies.