bluuebunny/crossref_metadata_2025 huggingface dataset:
Surface Pretreatment with Luteolin to Achieve the Effective Flotation Separation of Sphalerite from Pyrite in a CuSO4-Xanthate System
Authors: Chen Jiaxiu , Zhao Lv , He Haiyang , Cai Jinpeng , Dong Liuyang , Liu Dianwen
Published: February 2025

The flotation separation of sphalerite (ZnS) and pyrite (FeS2) in a copper sulfate (CuSO4)–butyl xanthate (BX) system is challenging because the indiscriminate activation of Cu2+ gives them similar floatability. To this end, the suitability of a novel depressant, luteolin (LUT), on the flotation separation of ZnS from FeS2 in this system was studied. Micro-flotation tests and contact angle measurement results showed that ZnS could be selectively separated from FeS2 using LUT as a depressant. At pH 7.0 ± 0.1, a flotation concentrate with a recovery of 93.90% ZnS and 2.84% FeS2 was obtained after adding LUT in artificial mixed minerals tests. Adsorption differences and characteristics results showed that the affinity of LUT to FeS2 was considerably higher than that of ZnS, which effectively hindered the subsequent adsorption of xanthate on FeS2 but had a relatively weak effect on ZnS. Thus, a large floatability difference between ZnS and FeS2 was achieved. Further analyses revealed that the adsorption behavior of LUT on FeS2 occurred mainly through the interaction between 4–5 sites and Fe(II) at the solid/liquid interface. These findings shed light for the first time on the suitability of LUT for the successful flotation separation of ZnS from FeS2, which has important guiding significance for the development of a lime-free depressant of FeS2.
Construction of Structured Hydrotalcite Supported with Silver Halide and Its Enhanced Visible Light Photocatalytic Degradation of Methyl Orange
Authors: Yang Jingwen , Wang Chunhui , Yu Ziqi , Yu Tao , Bai Bingbing , Chen Gang , Tang Ying
Published: February 2025

To increase the interaction between a catalyst and large pollutant molecules in industrial wastewater, this study employed worm-like micelles created by surfactants as soft templates for synthesizing structured hydrotalcites with high specific surface areas and diverse pore sizes. Following this, the integration of these hydrotalcites with AgBr yielded supported, structured hydrotalcites that exhibited enhanced redox properties. Characterization techniques, including XRD, FT-IR, SEM, and EDS, validated the successful incorporation of AgBr into the structured hydrotalcites. Furthermore, UV–Vis DRS and electrochemical analyses revealed that the integration with AgBr narrowed the band gap of the hydrotalcites, thereby expanding their light absorption range. At 25 °C with an initial solution pH of 5 and an adsorbent dosage of 0.5 g/L, the efficiency of methyl orange removal by the composite material reached 97.69% after 60 min of dark adsorption. EPR and reactive species-trapping experiments revealed that the high-efficiency degradation of methyl orange was primarily attributed to the combined action of highly active h+, •O2−, and 1O2 species.
Sustainable Bacterial Cellulose Production Using Low-Cost Fruit Wastewater Feedstocks
Authors: Mouro Cláudia , Gomes Arlindo , Gomes Ana P. , Gouveia Isabel C.
Published: February 2025

Bacterial cellulose (BC) is a versatile biopolymer prized for its remarkable water absorption, nanoscale fiber architecture, mechanical robustness, and biocompatibility, making it suitable for diverse applications. Despite its potential, the high cost of conventional fermentation media limits BC’s scalability and wider commercial use. This study investigates an economical solution by utilizing fractions from fruit processing wastewater, refined through sequential membrane fractionation, as a supplement to commercial HS medium for BC production. BC films were thoroughly characterized using Fourier transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), X-ray diffraction (XRD), differential scanning calorimetry (DSC), and assessments of mechanical properties and water holding capacity (WHC). FTIR confirmed the BC structure, while TEM validated its nanofibrillar 3D network. XRD analysis revealed a slight increasing trend in crystallinity with the addition of wastewater fractions, and DSC revealed a slight increase in thermal stability for F#6. Adding these fractions notably improved the BC films’ tensile strength, Young’s modulus, and WHC. Overall, the results underscore that fruit processing wastewater fractions can serve as a cost-efficient, eco-friendly alternative to traditional fermentation media. This approach supports circular economy principles by lowering reliance on intensive wastewater treatments, promoting waste valorization, and advancing sustainable production methods for high-value biopolymers.
Spin Physics at PHENIX
Authors: Loomis Devon
Published: February 2025

Situated at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory, the PHENIX experiment has for almost two decades been at the forefront of investigations into spin structure and dynamics in high-energy nuclear physics. Although decommissioned in 2016, the PHENIX collaboration has released a number of new results over the past several years that continue to inform the field. Recent longitudinal spin measurements uncover the role of gluon and sea quark polarization in the proton. Transverse spin measurements probe the transverse momentum-dependent (TMD) distributions and higher-twist multiparton correlators that are needed to fully explain partonic dynamics in the initial and final state. Additionally, the effects of heavy ions on spin have been studied by comparing transverse spin measurements between p+p and p+A collisions. These recent results and their wider implications are presented.
Extraction Optimization and Bioactivity of Polysaccharides from Ganoderma leucocontextum Spores
Authors: Peng Siying , Ou Yanghui , Zhang Yali , Yao Hongliang , Chen Wen-Hua
Published: February 2025

Background: Oxidative stress is associated with the occurrence and progress of aging. Natural polysaccharides have attracted considerable attention in the field of antioxidants and anti-aging products due to their superior biological activity and low toxicity. Ganoderma leucocontextum is primarily found in the Tibetan plateau region and is classified as a subspecies of Ganoderma. Known as the famous white Ganoderma, it is a precious food and medicine that has potent biological activity, including antitumor, hypoglycemic, and immune regulation. Since available resources are limited, there are few studies on the spore of Ganoderma leucocontextum. Methods: In this work, a polysaccharide (named GLSP) was extracted from the spore of Ganoderma leucocontextum using a fast, simple, efficient, and environmentally friendly extraction process: the three-phase partitioning (TPP) method. Results: The extraction condition was optimized under the Box–Behnken design (BBD): ratio of the solute to the solvent, 1:21.126 (w/v); (NH4)2SO4 concentration, 30% (w/v); ratio of the slurry to tert-butanol, 1:1.945 (v/v); and shaking temperature, 54.136 °C. Furthermore, a polysaccharide termed GLSP-A1 was purified from GLSP by column chromatography. The basic physicochemical properties were analyzed by molecular weight, Fourier transform infrared spectroscopy, monosaccharide composition, and scanning electron microscopy. Conclusions: GLSP-A1 down-regulated the expression of the pro-inflammation cytokines interleukin-6 and interleukin-1β, indicating favorable in vitro anti-inflammatory properties. In vivo, the effect of GLSP-A1 on aging was examined using the Caenorhabditis model. The results showed that GLSP-A1 reduced reactive oxygen species levels and lipofuscin accumulation. In general, these findings improve our understanding of the chemical content and bioactivity of a polysaccharide from Ganoderma leucocontextum spore and highlight the possibility of GLSP-A1 being utilized in dietary supplements for its anti-aging properties.
3DVT: Hyperspectral Image Classification Using 3D Dilated Convolution and Mean Transformer
Authors: Su Xinling , Shao Jingbo
Published: February 2025

Hyperspectral imaging and laser technology both rely on different wavelengths of light to analyze the characteristics of materials, revealing their composition, state, or structure through precise spectral data. In hyperspectral image (HSI) classification tasks, the limited number of labeled samples and the lack of feature extraction diversity often lead to suboptimal classification performance. Furthermore, traditional convolutional neural networks (CNNs) primarily focus on local features in hyperspectral data, neglecting long-range dependencies and global context. To address these challenges, this paper proposes a novel model that combines CNNs with an average pooling Vision Transformer (ViT) for hyperspectral image classification. The model utilizes three-dimensional dilated convolution and two-dimensional convolution to extract multi-scale spatial–spectral features, while ViT was employed to capture global features and long-range dependencies in the hyperspectral data. Unlike the traditional ViT encoder, which uses linear projection, our model replaces it with average pooling projection. This change enhances the extraction of local features and compensates for the ViT encoder’s limitations in local feature extraction. This hybrid approach effectively combines the local feature extraction strengths of CNNs with the long-range dependency handling capabilities of Transformers, significantly improving overall performance in hyperspectral image classification tasks. Additionally, the proposed method holds promise for the classification of fiber laser spectra, where high precision and spectral analysis are crucial for distinguishing between different fiber laser characteristics. Experimental results demonstrate that the CNN-Transformer model substantially improves classification accuracy on three benchmark hyperspectral datasets. The overall accuracies achieved on the three public datasets—IP, PU, and SV—were 99.35%, 99.31%, and 99.66%, respectively. These advancements offer potential benefits for a wide range of applications, including high-performance optical fiber sensing, laser medicine, and environmental monitoring, where accurate spectral classification is essential for the development of advanced systems in fields such as laser medicine and optical fiber technology.
A New Pro-197-Ile Mutation in Amaranthus palmeri Associated with Acetolactate Synthase-Inhibiting Herbicide Resistance
Authors: Ji Meijing , Yu Haiyan , Cui Hailan , Chen Jingchao , Yu Jialin , Li Xiangju
Published: February 2025

Palmer amaranth (Amaranthus palmeri S. Watson), native to North America, is one of the most prominent invasive weed species on agricultural land. Acetolactate synthase (ALS)-resistant A. palmeri (Amaranthus palmeri) is widespread, while the research focus on resistance pattern and molecular basis of A. palmeri to imazethapyr is seldom documented in China. An A. palmeri population that survived the recommended rate of imazethapyr was collected in Shandong Province, China. The resistant mechanism and pattern of A. palmeri to imazethapyr was investigated. Dose–response assay showed that the resistant (R) population displayed a high resistance level (292.5-fold) to imazethapyr compared with the susceptible (S) population. Sequence analysis of the ALS gene revealed that nucleotide mutations resulted in three resistance-conferring amino acid substitutions, Pro-197-Ile, Trp-574-Leu, and Ser-653-Asp, in the individual plants of the R population. An in vitro enzyme assay indicated that the ALS was relatively unsusceptible to imazethapyr in the R population, showing a resistance index of 88.6-fold. ALS gene expression and copy number did not confer resistance to imazethapyr in the R population. Pro-197-Ile is the first reported amino acid substitution conferring ALS resistance to A. palmeri. This is the first case of an imazethapyr-resistant A. palmeri biotype in China.
Transcriptome Analysis Revealed Hub Genes Related to Tipburn Resistance in Chinese Cabbage (Brassica rapa L. ssp. pekinensis)
Authors: Bi Yaning , Zhang Wenjing , Yuan Yuxiang , Feng Jianqi , Wang Peiyun , Ding Cong , Zhao Yanyan , Li Lin , Su Henan , Tian Baoming , Wei Fang , Wei Xiaochun , Zhang Xiaowei
Published: February 2025

Tipburn is a physiological disease in Chinese cabbage. In recent years, this disease has become increasingly serious, affecting the quality and economic benefits of Chinese cabbage. However, little is known about the molecular mechanism by which calcium deficiency induces tipburn. Therefore, we performed transcriptome analysis on Y578-2 (tipburn-resistant accession) and Y920-2 (tipburn-susceptible accession) to identify the genes involved in the tipburn defense mechanism in Chinese cabbage. In this study, phenotypic observation showed that Y920-2 began to display symptoms on the 10th day of calcium deficiency treatment. Through weighted gene co-expression network analysis (WGCNA), three gene modules that were highly related to tipburn resistance were identified. Analysis of gene expression regulation in the three modules revealed 13 hub genes related to tipburn resistance, which were involved in the cell wall, photosynthesis, transcription factors, hormones, and the stress response, indicating that these factors play an important role in the tipburn response of Chinese cabbage. These transcriptome data and analysis results provide a basis for the study of the molecular mechanism of calcium deficiency-induced tipburn in Chinese cabbage.
Geometric Models of Speciation in Minimally Monophyletic Genera Using High-Resolution Phylogenetics
Authors: Zander Richard H.
Published: February 2025

High-resolution phylogenetics using both morphology and molecular data reveal surfactant-like trait buffering of peripatric descendant species that facilitate resilience for supra-specific entities across geologic time. Regular polygons inscribed in circles model balanced areas of survival of various numbers of new species in one genus. This model maximizes the peripatric survival of descendant species, with populations partly in allopatric habitats and in sympatric areas. It extends the theory advanced with Willis’s Age and Area hypothesis. Hollow curves of the areas bounded between a series of inscribed regular polygons and their containing circles show a ranked progression governed by similar power laws of other phenomena, including Zipf’s law and a universal meta-law in physics. This model matches best the physics meta-law (law of laws) but is only one of several somewhat different curves generated by somewhat different processes. A rule of four can explain why most genera in vascular plants exhibit a hollow curve of optimally one to five species per genus. It implies a constraint on variation that enhances survival and provides a physics explanation for the monophyletic skeleton of macrogenera. A high-resolution form of ancestor–descendant analysis is compared to traditional phylogenetic analysis to best modeling of the demonstrable results of evolutionary processes. Arguments are advanced for the preservation of scientific concepts of taxa over cladistic clades.
Calmodulin-Binding Transcription Factors: Roles in Plant Response to Abiotic Stresses
Authors: Liu Yayu , Qiao Yali , Liao Weibiao
Published: February 2025

Plants face many abiotic stresses throughout their life cycle, such as drought, high temperature, low temperature, and salinity. To survive and reproduce, plants have evolved a complex and elaborate signal transduction network to sense stress signals and initiate corresponding defense mechanisms. Calcium ion (Ca2+), as a secondary messenger, plays an important role in mediating signal transduction in plant cells. Calmodulin (CaM) is an important class of Ca2+ receptors that sense changes in cellular calcium ion concentration and can interact with a range of proteins to regulate the activity of downstream target proteins. Calmodulin-binding transcription factors (CAMTAs) are a family of transcription factors (TFs) that are widely present in plants and can bind to CaM. The CAMTAs are regarded as the most characterized CaM-binding TF family in the plant Ca2+ signaling pathway. In recent years, studies have shown that CAMTAs play an important regulatory role in plant abiotic stress response and plant growth and development. Therefore, this review summarizes the recent progress in the discovery, structure, and role of CAMTAs under abiotic stresses, with a view to providing a reference for future CAMTA studies. Finally, the prospects and directions for further research on the potential mechanisms of CAMTAs in plants are also discussed.
Resistance Spectrum Analysis and Breeding Utilization of Rice Blast Resistance Gene Pigm-1
Authors: Jin Yidan , He Niqing , Cheng Zhaoping , Lin Shaojun , Huang Fenghuang , Wang Wenxiao , Li Qingshun Q. , Yang Dewei
Published: February 2025

Rice blast is one of the most important diseases of rice, causing significant economic losses to agricultural production. A new gene, Pigm-1, which is allelic to Pigm, was cloned from Shuangkang 77009 using map based cloning. However, it is unclear whether there is a difference in the resistance spectrum between Pigm and Pigm-1. In this study, using 195 rice blast isolates collected from different areas of the Fujian Province, the Pigm-1 and Pigm single gene lines were inoculated to test their resistance. There was only one blast fungus JL-37 that showed a differential response in Pigm and Pigm-1 single gene lines, while the remaining 194 showed no difference. To further explore the application range of Pigm-1, the resistant rice R20-4 containing Pigm-1 was used as the donor, and a sensitive sticky rice S19-118 was used as the receptor. The hybrid F1 was first backcrossed with S19-118 using a molecular marker-assisted selection breeding method, and a strain containing the Pigm-1 gene was selected to continue to backcross with S19-118 until BC3F1. A new blast resistance rice material, Xiannuo 23, containing Pigm-1 was developed and confirmed by laboratory and field tests. This material can be broadly used for the future breeding of rice blast resistant cultivars to reduce the loss of rice production.
Solar Radiation Drives the Plant Species Distribution in Urban Built-Up Areas
Authors: Wei Heyi , Huang Bo , Wang Mingshu , Liu Xuejun
Published: February 2025

Urban areas serve as critical habitats for numerous plant species. Existing studies suggest that, due to human-mediated introductions, urban environments often harbor a greater variety of plant species compared to suburban areas, potentially becoming focal points for biodiversity. Consequently, investigating the driving forces and complex mechanisms by which urban environmental factors influence plant species distribution is essential for establishing the theoretical foundation for urban biodiversity conservation and future urban planning and management. Solar radiation, among these factors, is a critical determinant of plant growth, development, and reproduction. However, there is a notable lack of research on how this factor affects the distribution of urban plant species and influences species’ richness and composition within plant communities. We present for the first time an analysis of how solar radiation drives the spatial distribution of plant species within the built-up areas of Nanchang City, China. Based on three years of monitoring and survey data from experimental sites, this study employs three evaluation models—Species Richness Index (R), Simpson’s Diversity Index (D), and Shannon–Wiener Index (H)—to analyze and validate the survey results. Additionally, MATLAB and ArcGIS Pro software are utilized for the numerical simulation and visualization of spatial data. Our study shows that areas with low solar radiation exhibit higher plant species richness, while plots with high plant diversity are primarily concentrated in regions with strong solar radiation. Moreover, the Diversity Index D proves to be more sensitive than the Shannon–Wiener Index (H) in evaluating the spatial distribution of plant species, making it a more suitable metric for studying urban plant diversity in our study area. Among the 18 plant species analyzed, Mulberry and Dandelion are predominantly dispersed by birds and wind, showing no significant correlation with solar radiation. This finding indicates that the spatial distribution of urban plant species is influenced by multiple interacting factors beyond solar radiation, highlighting the critical need for long-term observation, monitoring, and analysis. This study also suggests that shaded urban areas may serve as hubs of high species richness, while regions with relatively strong solar radiation can sustain greater plant diversity. These findings underscore the practical significance of this research, offering essential insights to guide urban planning and management strategies. Additionally, this study offers valuable insights for the future predictions of plant species distribution and potential areas of high plant diversity in various urban settings by integrating computational models, building data, Digital Elevation Models (DEMs), and land cover data.
Enhancing Piezoelectricity of Polyacrylonitrile–Cellulose Composite Nanofibers via Zigzag Conformation
Authors: Lim Joong Yeon , Kwak Won Suk , Park Minwook , Kim Young Seong
Published: February 2025

A novel piezoelectric material, polyacrylonitrile (PAN) nanofibers, exhibits significant piezoelectric effects when a high content of planar zigzag structures is present. To enhance the contribution of planar zigzag structures to energy conversion while preserving the structure of PAN nanofibers, a novel approach was developed to increase planar zigzag content by incorporating cellulose nanocrystals (CNCs) rather than modifying conventional synthesis conditions. In this study, CNCs were introduced during the electrospinning process of PAN formation, and the increased planar zigzag content was confirmed through X-ray diffraction (XRD), electrical characterization, and Fourier transform infrared spectroscopy (FTIR) analyses. This study, for the first time, demonstrates that CNC addition to PAN enhances the mechanical properties and piezoelectric performance by promoting the formation of zigzag structures, which play a crucial role in the piezoelectric effect. The PAN–CNC composite holds great potential for applications in new piezoelectric devices. With CNC incorporation, the voltage increased by 68.9%, and the current increased by 80% compared to regular PAN. The generated energy is suitable for human applications and can also power commercial devices, making these findings pivotal for the advancement of piezoelectric materials and devices.
Acoustic Emission/Mine Microseismic Sensor Network Optimization Based on Grid Loop Search and Particle Swarm Source Location
Authors: Chen Yiling , Shang Xueyi , Ren Yi , Liu Linghao , Li Xiaoying , Zhang Yu , Wu Xiao , Li Zhuqing , Tai Yang , Pu Yuanyuan , Xiang Guanghua
Published: February 2025

The layout of acoustic emission sensors plays a critical role in non-destructive structural testing. This study proposes a grid-based optimization method focused on multi-source location results, in contrast to traditional sensor layout optimization methods that construct a correlation matrix based on sensor layout and one source location. Based on the seismic source travel time theory, the proposed method establishes a location objective function based on minimum travel time differences, which is solved through the particle swarm optimization (PSO). Furthermore, based on location accuracy across various configurations, the method systematically evaluates potential optimal sensor locations through grid search. Synthetic tests and laboratory pencil-lead break (PLB) experiments are conducted to compare the effectiveness of PSO, genetic algorithm (GA), and simulated annealing (SA), with the following conclusions. (1) In the synthetic tests, the proposed method achieved an average location error of 1.78 mm, outperforming that based on the traditional layout, GA and SA. (2) For different noise cases, the location accuracy separately improved by 24.89% (σ = 0.5 μs), 12.59% (σ = 2 μs), and 15.06% (σ = 5 μs) compared with the traditional layout. (3) For the PLB experiments, the optimized layout achieved an average location error of 9.37 mm, which improved the location accuracy by 59.15% compared with the traditional layout.
Drill Cuttings Test of Coal Under Different Stresses and Characteristics of Coal Particle Distribution During Borehole Collapse
Authors: Yin Yanchun , Zhang Qingzhi , Guo Lei , Wang Cunwen , He Shudong , Zhang Dongdong
Published: February 2025

The drill cuttings method is a commonly used method for evaluating coal burst risk in mines. In engineering applications, due to the development of fractures in coal seams, borehole collapse can easily occur during drilling, which leads to a greater quantity of drill cuttings. This in turn affects the accuracy of the evaluation results of coal burst risk. Through laboratory tests on drill cuttings from intact coal and fractured coal specimens, the impact of coal stress and diameter of the borehole on the quantity of drill cuttings and the occurrence of borehole collapse was studied. When there is no collapse, the quantity of drill cuttings increases in proportion to the diameter of the borehole and the coal stress and has a power function relationship with the diameter of the borehole and an exponential function relationship with the coal stress. When the collapse occurs, the failure characteristics of coal specimens mainly present two forms. One is the cylindrical collapse area, and the other is the conical collapse area. Compared to normal drilling, there are notable changes in the particle size of drill cuttings after borehole collapse, and the characteristic value of drill cuttings size D50 increases significantly after the collapse of the borehole, which can be used to determine whether the borehole collapse occurs.
Understanding Young Consumers’ E-Waste Recycling Behaviour in Bangladesh: A Developing Country Perspective
Authors: Islam Md Hasibul , Islam Md. Tamzidul , Hoque Mohammad Rashedul , Haque Shahnaz Zarin , Barua Bikash , Islam M. M. Obaidul , Hossain Md. Faruque
Published: February 2025

The rising amount of electronic waste (e-waste) presents serious threats to the environment and public health. Addressing this challenge necessitates a focus on improving the e-waste recycling rate, which is facilitated by consumers’ spontaneous participation. This paper explores the factors influencing young consumers’ e-waste recycling behavior (EWRB) from a developing country’s perspective. Though existing literature has addressed various factors affecting EWRB, the role of individuals’ pro-environmental goals (PEG) remains underexplored. This paper provides an integrated theoretical model that incorporates PEG alongside factors drawn from the Theory of Planned Behavior (TPB), Norm Activation Model (NAM), and Behavioral Reasoning Theory (BRT). Data were collected through a survey and analyzed using structural equation modeling. The results reveal that young consumers’ intentions toward EWRB are significantly influenced by economic benefits, perceived behavioral control, moral norms, and PEG, while economic benefits emerge as the most influential factor. However, the impact of attitude and subjective norm on intention was found to be insignificant. Results indicate that despite having positive intentions, young consumers were often deterred from recycling e-waste due to perceived risks, indicating a negative moderating effect of perceived risk on the intention–behavior relationship. Conversely, PEG positively moderates the impact of intention on EWRB, reducing the intention–behavior gap. This paper contributes to the literature by enhancing our understanding of how PEG interacts with other factors affecting EWRB. Practically, the findings offer valuable recommendations for policymakers and practitioners aiming to promote EWRB among young consumers, particularly in Bangladesh.
The Origins and Symbolism of Vaiśravaṇa Iconography and the Impact of the Royal Image as Donor and Protector
Authors: Shim Yeoung Shin
Published: February 2025

This study examines the origins and symbolic meanings of the iconography of Vaiśravaṇa, which gained prominence in East Asia during the 200 years after the 8th century, through the lens of royal imagery as both a devotee and protector. As Vaiśravaṇa’s iconography spread along the Silk Road, it integrated diverse cultural traditions from the ancient Near East and the Indo-Iranian world, with Gandhāra and Khotan as central hubs. The iconography evolved into a distinctive form, featuring a cylindrical crown adorned with bird motifs, shoulder flames, a cross belt, a Stūpa, a spear, and celestial maidens. Previous studies often limited its origin to either Gandhāra or Khotan; however, this research highlights contributions from both regions, emphasizing their roles in shaping iconography. By focusing on Gandhāra and the Kushan Empire, this study explores how these elements reflect the diversity of regional cultures, political ideals, and religious values. It contextualizes these developments within historical and cultural exchanges between regions, offering a broader understanding of Vaiśravaṇa’s formation. The findings reveal that Vaiśravaṇa’s iconography reflects cultural exchange and symbolizes the sacred earthly ruler. This perspective highlights how regional diversity and intercultural interactions shaped its development, enriching the study of Buddhist iconography.
Compact Integrated On-Chip MIMO Antenna with Reconfigurability for mmWave Frequencies
Authors: Boubekeur Khaled , Zerounian Nicolas , Ratni Badr Eddine
Published: February 2025

This paper presents a compact on-chip multiple-input multiple-output (MIMO) antenna designed for future communication systems, featuring frequency-agile elements. The antenna achieves enhanced decoupling and reduced cross-section through the integration of a metasurface, which also introduces frequency agility. Designed for the millimeter-wave band using low-loss BenzoCycloButene (BCB) polymer, the antenna is manufactured with microelectronic processes, and the dimensions are 7.54 × 7.54 × 0.055 mm3. Simulations and measurements demonstrate excellent frequency agility around 60 GHz, with gains of 6.5 to 9 dBi. As a proof of concept, open and short circuits were used for switching, with future designs aiming to incorporate diodes for a full dynamic reconfiguration. This work highlights the potential for compact, high-performance, and frequency-reconfigurable on-chip antennas in next-generation millimeter-wave systems.
Running Parameter Analysis in 400 m Sprint Using Real-Time Kinematic Global Navigation Satellite Systems
Authors: Onodera Keisuke , Miyamoto Naoto , Hirose Kiyoshi , Kondo Akiko , Kajiwara Wako , Nakano Hiroshi , Uda Shunya , Takeda Masaki
Published: February 2025

Accurate measurement of running parameters, including the step length (SL), step frequency (SF), and velocity, is essential for optimizing sprint performance. Traditional methods, such as 2D video analysis and inertial measurement units (IMUs), face limitations in precision and practicality. This study introduces and evaluates two methods for estimating running parameters using real-time kinematic global navigation satellite systems (RTK GNSS) with 100 Hz sampling. Method 1 identifies mid-stance phases via vertical position minima, while Method 2 aligns with the initial contact (IC) events through vertical velocity minima. Two collegiate sprinters completed a 400 m sprint under controlled conditions, with RTK GNSS measurements validated against 3D video analysis and IMU data. Both methods estimated the SF, SL, and velocity, but Method 2 demonstrated superior accuracy, achieving a lower RMSE (SF: 0.205 Hz versus 0.291 Hz; SL: 0.143 m versus 0.190 m) and higher correlation with the reference data. Method 2 also exhibited improved performance in curved sections and detected stride asymmetries with higher consistency than Method 1. These findings highlight RTK GNSS, particularly the velocity minima approach, as a robust, drift-free, single-sensor solution for detailed per-step sprint analysis in outdoor conditions. This approach offers a practical alternative to IMU-based methods and enables training optimization and performance evaluation.
Frequency Diverse Array and Spotlight Synthetic Aperture Radar 2D Imaging Based on Multiple Repeated Subpulses
Authors: Li Qinlin , Liao Kefei , Xie Ningbo , Chen Hanbo
Published: February 2025

Frequency diverse array (FDA) beams show an “S” shape in space and cannot form a spot beam; thus, they cannot be directly combined with spotlight synthetic aperture radar (SSAR). In this paper, we propose a 2D imaging system emitting multiple repeated subpulses using an FDA and spotlight synthetic aperture radar (MRS-FDA-SSAR). This system carries the FDA on an airborne platform and uses the frequency difference between the array elements to synthesize broadband signals and obtain the distance-direction resolution, and then it uses a synthetic aperture technique to obtain the azimuth-direction resolution. Subsequently, 2D imaging results are obtained using the BP algorithm. A deconvolution algorithm is introduced to address the problem of high target sidelobes in the BP imaging results, which can result in the masking of weak targets. This allows 2D imaging results to be obtained with lower sidelobes. Finally, the MRS-FDA-SSAR model was simulated in experiments to verify its effectiveness.
Is the Assessment of the Non-Paretic Lower Limb in Patients After Stroke Important When Planning Rehabilitation?
Authors: Wareńczak-Pawlicka Agnieszka , Lisiński Przemysław
Published: February 2025

(1) Background: Hemiparetic patients after stroke have deficits on the side of the body opposite to the brain lesion. The aim of this study is to assess the occurrence of deficits in the ipsilesional lower limb. (2) Methods: Twenty-nine stroke patients (SG) and 29 healthy volunteers (CG) were recruited for this study. Passive (PROM), active (AROM), fast range of motion (FROM), and joint position sense (JPS) in the knee joint were measured using a wireless motion system. Participants were also assessed using the step test, balance platform, and the isometric protocol of measuring the strength of the extensor and flexor muscles of the knee. We compared non-paretic lower limb outcomes to the paretic side and a control group. (3) Results: The results showed a difference between the results of the ipsilesional side of the body of stroke patients and the control group. In the non-paretic limb, we observed deficits in PROM (p = 0.018) and AROM (p = 0.048), a lower average (p < 0.001) and maximum speed (p < 0.001) in FROM, worse proprioception (JPS, p < 0.001), and a lower number of repetitions in the step test (p < 0.001) compared to the control group. We also observed a decrease in the average isometric strength of the extensor (p < 0.001) and flexor (p = 0.040) muscles of the non-paretic knee joint compared to the CG. The balance assessment on a balance platform showed worse postural control in people after stroke in all tested conditions (eyes open and closed on a firm and foam surface; p < 0.001). (4) Conclusions: The non-paretic lower limb in stroke patients is characterized by limited ROM at the knee joint, reduced movement speed, decreased proprioception, weakness of the knee flexors and extensors, and resulting impaired balance. The deficits identified require improvement and should be considered when planning rehabilitation.
Structural Stability Assessment for Optimal Order Picking in Box-Stacked Storage Logistics
Authors: Choi Haegyeom , Yoon Hojin , Jung Eunbin , Lee Donghun
Published: February 2025

This study proposes a method for time-efficient order picking based on a structural stability assessment (SSA) when target boxes inside box-stacking storage (BSS) on multi-layer racks are removed. This method performs optimal order picking by generating a path to directly pick the target box without first picking the upper boxes in the BBS, if it is possible to pick the target box directly. The SSA algorithm generates images of the complement structure by removing the target box within BBS and uses them as input data for the CNN model to evaluate the stability of the structure. To create the CNN model, we generated a dataset using CoppeliaSim simulation, considering the size and shape of the overall structure of the BBS, the size and number of each box, and the number of target boxes. The accuracy of the generated CNN model was 95.1% on test data, while it achieved 97% accuracy when using real-world data. This validation process confirmed that the algorithm can be effectively applied to real BBS logistics environments to perform optimal order picking.
Object Recognition and Positioning with Neural Networks: Single Ultrasonic Sensor Scanning Approach
Authors: Karagoz Ahmet , Dindis Gokhan
Published: February 2025

Ultrasonic sensing may become a useful technique for distance measurement and object detection when optical visibility is not available. However, the research on detecting multiple target objects and locating their coordinates is limited. This makes it a valuable topic. Reflection signal data obtained from a single ultrasonic sensor may be just enough for the measurements of distance and reflection strength. On the other hand, if extracted properly, a scanned set of signal data by the same sensor holds a significant amount of information about the surrounding geometries. Evaluating this dataset from a single sensor scanning can be a perfect application for convolutional neural networks (CNNs). This study proposes an imaging technique based on a scanned dataset obtained by a single low-cost ultrasonic sensor. So that images are suitable for desired outputs in a CNN, a 3D printer is converted to an ultrasonic image scanner and automated to perform as a data acquisition system for the desired datasets. A deep learning model demonstrated by this work extracts object features using convolutional neural networks (CNNs) and performs coordinate estimation using regression layers. With the proposed solution, by training a reasonable amount of obtained data, 90% accuracy was achieved in the classification and position estimation of multiple objects with the CNN algorithm as a result of converting the signals obtained from ultrasonic sensors into images.
AI Agent-Based Intelligent Urban Digital Twin (I-UDT): Concept, Methodology, and Case Studies
Authors: Choi Sebin , Yoon Sungmin
Published: February 2025

The concept of digital twins (DTs) has expanded to encompass buildings and cities, with urban building energy modeling (UBEM) playing a crucial role in predicting urban-scale energy consumption via modeling individual energy use and interactions. As a virtual model within urban digital twins (UDTs), UBEM offers the potential for managing energy in sustainable cities. However, UDTs face challenges with regard to integrating large-scale data and relying on bottom-up UBEM approaches. In this study, we propose an AI agent-based intelligent urban digital twin (I-UDT) to enhance DTs’ technical realization and UBEM’s service functionality. Integrating GPT within the UDT enabled the efficient integration of fragmented city-scale data and the extraction of building features, addressing the limitations of the service realization of traditional UBEM. This framework ensures continuous updates of the virtual urban model and the streamlined provision of updated information to users in future studies. This research establishes the concept of an I-UDT and lays a foundation for future implementations. The case studies include (1) data analysis, (2) prediction, (3) feature engineering, and (4) information services for 3500 buildings in Seoul. Through these case studies, the I-UDT was integrated and analyzed scattered data, predicted energy consumption, derived conditioned areas, and evaluated buildings on benchmark.
From Waste to Resource: Exploring the Current Challenges and Future Directions of Photovoltic Solar Cell Recycling
Authors: Badran Ghadeer , Lazarov Vlado K.
Published: February 2025

The rapid proliferation of photovoltaic (PV) solar cells as a clean energy source has raised significant concerns regarding their end-of-life (EoL) management, particularly in terms of sustainability and waste reduction. This review comprehensively examines challenges, opportunities, and future directions in the recycling of PV solar cells, focusing on mechanical, thermal, and chemical recycling techniques. It also evaluates the scalability and practicality of these methods to different PV technologies, including crystalline silicon and thin-film modules. It explores the economic and environmental impacts of these processes, highlighting the necessity of developing robust recycling infrastructure and innovative technologies to address the anticipated surge in PV waste. Additionally, this review discusses the critical role of government policies and industry collaboration in overcoming the barriers to effective recycling. Furthermore, the importance of integrating design-for-recyclability principles into PV module development is emphasized, as it can significantly enhance material recovery and process efficiency. By advancing these strategies, the solar industry can achieve greater sustainability, reduce resource depletion, and mitigate environmental risks, thereby ensuring the long-term viability of solar energy as a key component of global renewable energy initiatives.
The Sleep, Recovery, and Nutrition Characteristics of Elite Adolescent Athletes
Authors: Mason Lorcán , Connolly James , Devenney Lydia E. , Lacey Karl , O’Donovan Jim , Faulkner Maria , Doherty Rónán
Published: February 2025

Background: Elite sport participation creates a significant burden on adolescent athletes due to demanding training schedules, high training intensities, and the complexity of puberty. As such, an athletes’ ability to effectively balance stress and recovery is essential for their athletic performance and requires appropriate management throughout the competitive season. This research aimed to investigate: (i) the quantity, quality, and timing of sleep; (ii) general and sport-specific nutrition knowledge; (iii) recovery practices; and (iv) the relationships between sleep, nutrition, and recovery practices in elite adolescent athletes. Methods: A total of 51 athletes completed a battery of previously validated and reliable questionnaires which investigated their sleep characteristics, nutrition knowledge, and recovery practices. Results: Statistically significant moderate correlations were observed between their Pittsburgh Sleep Quality Index (PSQI) global score, Sleep Difficulty Classification (SDC), and Recovery Stress Questionnaire for Athletes (REST-Q Sport) scales, with small significant correlations observed between the SDC and REST-Q recovery scales. Participants had lower scores in both their sport (36.10 ± 12.13) and total (40.25 ± 11.18) nutrition knowledge compared to their general nutrition knowledge (49.53 ± 16.46). Moderate levels of general (1.50 ± 0.86) and sport-specific (1.57 ± 0.85) stress and high levels of general (3.92 ± 0.74) and sport-specific (3.72 ± 0.96) recovery were demonstrated. Furthermore, 94% reported their sleep quality to be “fairly good” (n = 30) or “very good” (n = 18). Conclusions: These findings highlight the necessity of further investigating the effect of educational strategies on improving sleep, nutrition, and recovery knowledge in athletes to aid recovery and dietary behaviours.
STATom@ic: R Package for Automated Statistical Analysis of Omic Datasets
Authors: Treves Rui S. , Gripshover Tyler C. , Hardesty Josiah E.
Published: February 2025

Background: The evolution of “omic” technologies, which measure all biological molecules of a specific type (e.g., genomics), has enabled rapid and cost-effective data acquisition, depending on the technique and sample size. This, however, generates new hurdles that need to be addressed and should be improved upon. This includes selecting the appropriate statistical test based on study design in a high-throughput manner. Methods: An automated statistical analysis pipeline for omic datasets that we coined STATom@ic (pronounced stat-o-matic) was developed in R programming language. Results: We developed an R package that enables statisticians, bioinformaticians, and scientists to perform assumption tests (e.g., normality and variance homogeneity) before selecting appropriate statistical tests. This analysis package can handle two-group and multiple-group comparisons. In addition, this R package can be used for many data formats including normalized counts (RNASeq) and spectral abundance (proteomics and metabolomics). STATom@ic has high precision but lower recall compared to DeSeq2. Conclusions: The STATom@ic R Package is a user-friendly stand-alone or add-on to current bioinformatic workflows that automatically performs appropriate statistical analysis based on the characteristics of the data.
Can Digital Financial Inclusion Promote the Sustainable Growth of Farmers’ Income?—An Empirical Analysis Based on Panel Data from 30 Provinces in China
Authors: Xia Yun , Xu Guozhang
Published: February 2025

The issue of farmers’ income is a widespread concern in countries worldwide, and the Chinese government has always prioritized promoting the sustainable growth of farmers’ income. The development of digital financial inclusion provides a new opportunity for farmers’ income to achieve sustainable growth. With the implementation of digital financial inclusion, whether it can effectively promote farmers’ income growth deserves in-depth study. Based on the panel data from 30 provinces in China from 2011 to 2021, this study uses a dual fixed effects model to empirically analyse the impact of digital inclusive finance on farmers’ income and further analyses the impact of various dimensions of digital financial inclusion on farmers’ income. From a policy perspective, the DID (difference in differences) method is used to analyse, in general, the impact of the implementation of digital financial inclusion policies on farmers’ income and, in particular, the impact of such inclusion on farmers’ income from the perspective of income structure. The results of this study show that digital financial inclusion can significantly promote farmers’ income growth. The dimensions of the breadth of coverage and depth of use can significantly contribute to the increase in farmers’ income, whereas digitization has a negative effect on this increase. Furthermore, the DID results show that digital financial inclusion policy implementation has a significantly positive effect on farmers’ income growth, that is, it can significantly contribute to their wage income, can contribute to family operating income but at a low level of significance, and does not significantly contribute to their property income. Moreover, regional heterogeneity analysis demonstrates that the marginal contribution of digital financial inclusion to the growth of farmers’ income in the eastern region is less than that in the central and western regions. Therefore, the development of digital inclusive finance in rural areas should be vigorously promoted in order to provide high-quality financial services and achieve sustainable growth in farmers’ incomes.