bluuebunny/crossref_metadata_2025 huggingface dataset:
Characterization of a Natural Accession of Elymus sibiricus with In Situ Hybridization and Agronomic Evaluation
Authors: Liu Yizhuo , Ding Jiarui , Wu Chunfei , Song Weiwei , Zhao Xinyu , Zhao Haibin , Qu Yunfeng , Jin Hui , Zhang Rui , Li Mingyao , Yan Xinyu , Zhu Liangyu , Bao Yaqi , Liu Dianhao , Li Xinling , Cui Lei , Li Hongjie , Zhang Yanming
Published: January 2025

Elymus sibiricus, valued for its perennial nature, broad adaptability, strong cold tolerance, and high economic value in forage production, plays a crucial role in combating grassland degradation, desertification, and salinization. Using morphological and cytogenetic methods, this study evaluated the cold tolerance, post-harvest regeneration capacity, and perennial characteristics of the E. sibiricus accession 20HSC-Z9 in the Harbin region of China from 2020 to 2023. This accession exhibited a germination rate of over 90% and a 100% green-up rate, with purple coleoptiles indicating its strong cold tolerance. Over the three growing seasons, 20HSC-Z9 maintained stable green-up and regeneration rates, confirming its perennial nature. Morphologically, 20HSC-Z9 had an average tiller count ranging from 56 to 74, similar to that of the control accession 20HSC-ES, and its plant height was significantly lower than that of 20HSC-IWG. Furthermore, 20HSC-Z9 produced over 100 grains per spike, with a seed setting rate exceeding 90%, and a thousand-grain weight comparable to that of 20HSC-IWG. The grain protein content of 20HSC-Z9 reached a maximum of 21.19%, greater than that of the control accessions (15.6% and 18.5%). Chromosome composition analysis, using sequential multicolor genomic in situ hybridization and multicolor fluorescence in situ hybridization, confirmed the StStHH genomic constitution of 20HSC-Z9 and revealed translocations between the St and H subgenome chromosomes. These results suggest that 20HSC-Z9 has significant potential as a new perennial forage grass germplasm for cold regions, suitable for further domestication and breeding efforts.
A Zinc Polyphenolic Compound Increases Maize Resistance Against Infection by Bipolaris maydis
Authors: Lata-Tenesaca Luis Felipe , Barbosa Oliveira Marcos José , Barros Aline Vieira , Silva Leandro Castro , Wordell Filho João Américo , Rodrigues Fabrício Ávila
Published: January 2025

Maize leaf blight (MLB), caused by the fungus Bipolaris maydis, is an important disease affecting maize production. In order to minimize the use of fungicides in agriculture, nutrient-based resistance inducers may become a promising alternative to manage MLB. The goal of this study was to investigate the potential of Semia® (zinc (20%) complexed with a plant-derived pool of polyphenols (10%)) to hamper the infection of maize leaves by B. maydis by analyzing their photosynthetic performance and carbohydrate and antioxidative metabolism, as well as the expression of defense-related genes. Plants were sprayed with water (control) or Semia® (referred to as induced resistance (IR) stimulus hereafter) and not inoculated or inoculated with B. maydis. The mycelial growth and conidium germination were significantly reduced by the IR stimulus in vitro. The MLB severity was significantly reduced by 76% for IR-stimulus-sprayed plants compared to plants from the control treatment. For infected and IR-stimulus-sprayed plants, the glucose, fructose, sucrose, and starch concentrations were significantly higher compared to inoculated plants from the control treatment. The activity levels of superoxide dismutase, ascorbate peroxidase, catalase, and glutathione reductase were significantly higher for the IR-stimulus-sprayed plants compared to plants from the control treatment. Less impairment on the photosynthetic apparatus (higher values for leaf gas exchange (rates of net CO2 assimilation, stomatal conductance to water vapor, and transpiration) and chlorophyll a fluorescence (variable-to-maximum Chl a fluorescence ratio, photochemical yield, and yield for dissipation by down-regulation) parameters)) along with a preserved pool of chlorophyll a+b and carotenoids were noticed for infected and IR-stimulus-sprayed plants compared to infected plants from the control treatment. The defense-related genes IGL, CHS02, PR1, PAL3, CHI, and GLU were strongly up-regulated in the leaves of IR-stimulus-sprayed and infected plants compared to infected plants from the control treatment. These findings highlight the potential of using this IR stimulus for MLB management.
Interactive Effects of LED Spectrum and Nitrogen Levels on Physiological Changes and Yield of Strawberry (Fragaria × ananassa Duch.)
Authors: Salisu Jibia Sirajo , Panjama Kanokwan , Inkham Chaiartid , Sato Takashi , Ohtake Norikuni , Ruamrungsri Soraya
Published: January 2025

Strawberries are valued globally for their nutritional, aesthetic, and economic benefits. Optimizing blue-to-red LED ratios and nitrogen levels is essential for sustainable indoor strawberry cultivation. This factorial study investigated the effects of blue and red LED combination ratios (L1; 1:3, L2; 1:4, and L3; 1:6) and nitrogen levels (N1; 100 and N2; 200 mg/L) on the physiology and performance of strawberries in a plant factory. The results revealed that the interaction of L3 coupled with N2 maximized the vegetative growth of strawberry plants, whereas L2 and N2 produced the greatest biomass, while L2 interacted with N1 to expedite flowering. Photosynthesis and transpiration were enhanced by L3, particularly with 100 mg/L of nitrogen. The highest fruit yield and total soluble solids were obtained at the interaction of L3 and N1. Leaf nutrient analysis showed the highest nitrogen concentration at L1, while potassium increased with higher red LED ratios. The 100 mg/L nitrogen treatment resulted in higher leaf potassium concentrations than the 200 mg/L. These findings emphasize that LED spectra and nitrogen levels interact to optimize the physiology, vegetative and reproductive growth, maximizing fruit yield and quality in indoor strawberry cultivation. The study also concludes that the application of blue and red LED in the ratio of 1:6 with 100 mg/L nitrogen can improve indoor ‘Praratchatan 80’ strawberry performance.
Influence of Parameters Used to Prepare Sterile Solutions of Poloxamer 188 on Their Physicochemical Properties
Authors: Yegorov Alexander , Pushkin Sergei , Arshintseva Elena , Molchanov Maxim , Timchenko Maria
Published: January 2025

The physicochemical properties of emulsions based on poloxamers (triblock copolymers of a hydrophobic polyoxypropylene chain and two hydrophilic polyoxyethylene chains) depend on the composition and preparation method. This study examined the impact of poloxamer P188 concentration, autoclaving mode, heating, and salt presence on the viscosity, particle size distribution, and morphology of particles using viscometric analysis, dynamic light scattering (DLS), and atomic force microscopy (AFM). It was shown that sample preparation affects the particle size and morphology but not the chemical composition of P188. The most similar properties were found for 10% P188 samples sterilized by filtration and autoclaving. The higher autoclave temperature and additional heating of the 10% P188 samples to 70 °C resulted in the formation of larger particles. For 4% P188 samples with 0.6% NaCl, samples heated at 70 °C for 15 h after sterilization filtration and autoclaving were the most similar and homogeneous. The 4% P188 sample with the higher autoclave temperature and subsequent heating had the lowest viscosity. In contrast to 10% P188, for 4% P188 in the presence of salt, the lack of heating resulted in the formation of large particles. The 4% P188 solutions with NaCl were more stable during storage than those with a higher concentration.
From Waste to Worth: Upcycling Plastic into High-Value Carbon-Based Nanomaterials
Authors: M. Abdelfatah Ahmed , Hosny Mohamed , S. Elbay Ahmed , El-Maghrabi Nourhan , Fawzy Manal
Published: January 2025

Plastic waste (PW) presents a significant environmental challenge due to its persistent accumulation and harmful effects on ecosystems. According to the United Nations Environment Program (UNEP), global plastic production in 2024 is estimated to reach approximately 500 million tons. Without effective intervention, most of this plastic is expected to become waste, potentially resulting in billions of tons of accumulated PW by 2060. This study explores innovative approaches to convert PW into high-value carbon nanomaterials (CNMs) such as graphene, carbon nanotubes (CNTs), and other advanced carbon structures. Various methods including pyrolysis, arc discharge, catalytic degradation, and laser ablation have been investigated in transforming PW into CNMs. However, four primary methodologies are discussed herein: thermal decomposition, chemical vapor deposition (CVD), flash joule heating (FJH), and stepwise conversion. The scalability of the pathways discussed for industrial applications varies significantly. Thermal decomposition, particularly pyrolysis, is highly scalable due to its straightforward setup and cost-effective operation, making it suitable for large-scale waste processing plants. It also produces fuel byproducts that can be used as an alternative energy source, promoting the concept of energy recovery and circular economy. CVD, while producing high-quality carbon materials, is less scalable due to the high cost and required complex equipment, catalyst, high temperature, and pressure, which limits its use to specialized applications. FJH offers rapid synthesis of high-quality graphene using an economically viable technique that can also generate valuable products such as green hydrogen, carbon oligomers, and light hydrocarbons. However, it still requires optimization for industrial throughput. Stepwise conversion, involving multiple stages, can be challenging to scale due to higher operational complexity and cost, but it offers precise control over material properties for niche applications. This research demonstrates the growing potential of upcycling PW into valuable materials that align with global sustainability goals including industry, innovation, and infrastructure (Goal 9), sustainable cities and communities (Goal 11), and responsible consumption and production (Goal 12). The findings underscore the need for enhanced recycling infrastructure and policy frameworks to support the shift toward a circular economy and mitigate the global plastic crisis.
Hybrid Natural Fiber Composites of Polylactic Acid Reinforced with Sisal and Coir Fibers
Authors: Sriseubsai Wipoo , Praemettha Ariya
Published: January 2025

This study explored the tensile and impact strength of polylactic acid (PLA) through the incorporation of sisal and coir fibers. Hybrid natural fiber composites were prepared using PLA as the matrix and sisal and coir fibers as the reinforcements. The hybrid composites were prepared with an internal mixer, followed by compression molding. A constrained mixture design was employed to determine the optimal material combinations and their effects on the tensile and impact strength. Confirmatory experiments based on response surface methodology revealed no significant differences in the data means at the 0.05 significance level. PLA reinforced with sisal fibers alone exhibited the highest tensile strength of 75.36 MPa but demonstrated a low impact resistance of 12.94 kJ/m2 at a 95.22:4.78 (PLA:sisal by volume) ratio. Conversely, the maximum impact resistance of 36.71 kJ/m2 was achieved with PLA and coir at the same ratio. An optimal blend, consisting of 95.22% PLA, 0.78% sisal, and 4.0% coir by volume, resulted in a tensile strength of 51.08 MPa and an impact strength of 26.59 kJ/m2, outperforming other mixtures and pure PLA in the mechanical properties. Additionally, water absorption tests showed that reinforcement with sisal and coir fibers increased both water absorption and stability over 60 h.
Investigation into the Mechanism of Waterborne Polyurethane Modification of Ultrafine Talc and Its Impact on the Properties of Polypropylene Plastics
Authors: Yang Xianrong , Shuai Huan , Du Gaoxiang , Wang Jiao , Shen Jie
Published: January 2025

In this study, waterborne polyurethane (WPU), a novel modifier, was used for the wet surface modification of talc, and its mechanism was investigated. Polypropylene (PP)-based composites with modified talc were synthesized and subjected to an examination of their mechanical properties. The wetting contact angle demonstrated that the modified talc exhibited an excellent modification effect at a specific amount of modifier (2.0 wt.%). The X-ray diffraction (XRD), Fourier-transform infrared (FTIR), and X-ray photoelectron spectroscopy (XPS) results indicated the successful coating of WPU on the surface of the talc particles. SEM images revealed that modified talc displayed improved wettability, compatibility, and dispersion in PP/talc + WPU composites. The mechanical properties results showed that the PP/talc + WPU composites ensured superior comprehensive properties with a flexural strength of 55.9 MPa, impact strength of 4.72 kJ/m2, tensile strength of 34.8 MPa, and elongation of breaks of 32.4%. The incorporation of WPU-modified talc into plastic materials has been synthesized to leverage its beneficial properties, leading to reduced production costs and improved performance and functionality of the final product.
The Effect of Repass Treatment on the Mechanical Properties and Microstructure of CF/PEKK Thermoplastic Composite Laminates Manufactured Using Laser-Assisted Automated Fiber Placement
Authors: Zhang Xi , He Xiaodong , Li Hualian , Wang Shenglai
Published: January 2025

The emerging thermoplastic composite material PEKK exhibits superior thermal stability compared to PEEK. In this work, CF/PEKK laminates were fabricated using laser-assisted heating in AFP, and the effects of repass treatment on the mechanical properties and microstructure of the laminates were compared. The results show that after a single repass treatment, the tensile strength of the laminates increased by 28.39%, while the interlaminar shear strength increased by 11.9%, likely due to the distinct load-bearing components under the two loading conditions. Additionally, the repass treatment significantly improves the fiber/resin interface and surface roughness of the laminates.
Constructing a Broad-Pore-Domain Structure of Adsorbents for Acteoside Adsorption
Authors: Ru Weibo , Liu Jiaxing , Xiong Feng , Sun Yu , Zhang Yong , Li Yipei , Lv Yin , Li Xueqin
Published: January 2025

Acteoside (ACT) is an important medicinal component, but its content is scarce. To obtain higher purity of ACT, the adsorption method was used to purify it. In this study, a broad-pore-domain hyper-crosslinked polymer (BHP-Kae) was prepared to adsorb ACT from Cistanche tubulosa, which is a medicinal plant. BHP-Kae-3 possessed a unique broad-pore-domain structure. This structure reduced the transfer resistance of ACT and facilitated the rapid diffusion of ACT into BHP-Kae-3, increasing the adsorption capacity. In addition, the surface and pore channels of BHP-Kae-3 contained abundant functional groups (-OH, C=O), which provided a large number of adsorption sites and facilitated ACT adsorption, thereby improving selectivity. The experimental results showed that BHP-Kae-3 exhibited a good adsorption capacity for ACT; the adsorption capacity was 105.12 mg/g, and the selectivity was 3.41. This study demonstrates the potential for efficient separation of natural products using broad-pore-domain adsorbents.
Polymeric Coatings with Electrolyzed Acidic Water: A Novel Approach to Extending Egg Shelf Life and Quality
Authors: Parra A Gina , Clavijo Claudia , Castillo Alejandro , Ortega-Toro Rodrigo
Published: January 2025

Electrolyzed acidic water (EAW) contains hypochlorous acid as its active compound, which is a potent antimicrobial. It was encapsulated in polymeric coatings and applied to the surface of eggs. The antimicrobial activity and the ability to extend the shelf life of eggs at ambient temperature for 45 days were evaluated, by physical, microbiological, and sensory analyses. The analysis also included the evaluation of mechanical, thermal, and crystallinity properties and the interaction between the coating components and the eggshell. The results showed that eggs from young, middle-aged, and adult hens, encapsulated and coated with EAW, hydroxypropyl methylcellulose, polyvinyl alcohol, and chitosan, gained resistance and a glossy appearance. The thickness of the coating was 2.9 µm for young and adult hens’ eggs and 2.60 µm for those of old hens, as observed by SEM. Shelf life was extended to 45 days under refrigeration and more than 30 days at ambient temperature. Coated eggs were acceptable for 85% of the panelists compared to 57% acceptance of non-coated eggs. The encapsulation and coating with EAW as an antimicrobial agent improved the surface protection of commercial eggs, reduced albumen liquefaction, and maintained quality by acting as a barrier against air, thereby preserving sensory characteristics.
A Metaheuristic Approach to Analyze the Techno-Economical Impact of Energy Storage Systems on Grid-Connected Microgrid Systems Adapting Load-Shifting Policies
Authors: Dey Bishwajit , Krishnamurthy Senthil , Fose Nande , Ratshitanga Mukovhe , Moodley Prathaban
Published: January 2025

Battery energy storage systems (BESSs) and plug-in hybrid electric vehicles (PHEVs) are essential for microgrid operations to be financially viable. PHEVs can serve as mobile storage devices, storing excess energy during times of low demand and delivering it during times of high demand. By offering reliable on-site energy storage, BESSs improve cost efficiency by allowing the microgrid to store cheap, off-peak electricity and release it when prices increase. To minimize generation costs and alleviate grid stress during periods of high demand, load-shifting policies shift inelastic loads to off-peak hours when energy prices are lower. When combined, these tactics support dependable, affordable, and effective microgrid management. A recently developed RIME algorithm is used as the optimization tool to reduce the total operating cost (TOC) of an MG system for three cases and three situations. The cases emphasize a modified load demand style influenced by the optimal load-shifting method (OLSM) and order characteristics load-shifting policy (OCLSP), whereas the situations refer to the inclusion of ESS in the MG system. The TOC decreased from $2624 without ESS to $2611 and $2331 with PHEVs and BESSs, respectively. These costs were further reduced to $1192, $1162, and $1147, respectively, when OLSM was implemented to restructure the base load demand. Additionally, a balance between a minimal TOC and carbon emission was obtained when an OLSM-based load demand model was used with BESSs. The RIME algorithm outperformed many recently developed algorithms and is consistent and robust, yielding better quality solutions.
Impact of Deep Shale Gas Dense-Cutting Fracturing Parameters on EUR
Authors: Wang Tianyi , Ji Guofa , Liu Jiansheng , Xie Zelong
Published: January 2025

Deep shale formations pose significant challenges in forming high-conductivity fractures, leading to low ultimate recoverable reserves (EUR) per well under conventional fracturing techniques. Dense-cutting fracturing is a commonly employed method to enhance the EUR of individual wells; however, the critical process parameters influencing EUR remain unclear. This study develops a novel EUR calculation model tailored for deep shale gas dense-cutting, integrating the Warren-Root model with the constant-volume gas reservoir material balance equation. The model comprehensively incorporates Knudsen diffusion and adsorption-desorption phenomena in deep shale gas, corrects apparent permeability, and employs the finite element method to simulate dynamic pressure depletion during production. The study examines the impact of fracture half-lengths, cluster spacing, fracture conductivity and horizontal section lengths on EUR under tight-cutting fracturing. Orthogonal experiments combined with multiple linear regression analysis reveal the hierarchy of influence among the four factors on EUR: horizontal section length > fracture half-length > cluster spacing > fracture conductivity. The study derives EUR correlation expressions that incorporate the effects of crack half-length, cluster spacing, fracture conductivity, and horizontal segment length. The orthogonal experimental results indicate that EUR exhibits positive correlations with crack half-length, fracture conductivity, and horizontal segment length, while showing a negative correlation with cluster spacing. The multiple regression equation achieves a coefficient of determination (R2) of 0.962 and an average relative error of 3.79%, outperforming traditional prediction methods in both accuracy and computational simplicity. The findings are of substantial significance for the rapid estimation of EUR in individual wells following deep shale gas fracturing and offer valuable theoretical insights for practical engineering applications.
A Comprehensive Review of Green Energy Technologies: Towards Sustainable Clean Energy Transition and Global Net-Zero Carbon Emissions
Authors: Sharma Vinod Kumar , Monteleone Giulia , Braccio Giacobbe , Anyanwu Cosmas N. , Aneke Nneoma N.
Published: January 2025

The present paper seeks to showcase the significant potential of alternative energy technologies in driving clean energy transition. Renewable energy sources, including hydro, geothermal, biomass, solar, and wind energy, are developed and marketed as low- or non-carbon alternatives to conventional energy sources. However, the high upfront costs of these energy resources, coupled with their intermittency, are demerits that must be dealt with. Since certain nuclear technologies generate significantly less waste than coal and oil, nuclear energy is occasionally regarded as a green energy source, though the primary source of nuclear energy, namely uranium, is a finite resource. The main goal of developing green energy technologies is to provide energy in a sustainable manner while cutting down on waste and greenhouse gas emissions, thus reducing the overall carbon footprint of energy production.
Microbiological and Physicochemical Characterization During Biodrying of Organic Solid Waste
Authors: Orozco-Álvarez Carlos , Gervacio-Hernández Aniela , Moreno-Rivera María de Lourdes , Piña-Guzmán Belem , Robles-Martínez Fabián
Published: January 2025

The correct management of high-moisture organic waste (HMOW) is crucial to minimize its environmental impact and take advantage of its potential as a valuable resource, thus linking it to the circular economy, sustainable production and recycling. Processes such as anaerobic digestion, composting and, more recently, biodrying have been applied to support the sustainable management of HMOW. However, the latter has not yet been well characterized, so this study focuses on elucidating the behavior of microbial populations and their relationship with physical and chemical conditions during biodrying. In a greenhouse, a semi-static pile with an initial water content of 88%, composed of orange peel waste (80%), sugarcane bagasse (16.5%) and mulch (3.5%) was biodried for 50 days. Biodrying went through three stages: (1) the mesophilic stage, when different microbial populations decompose some organic matter, causing a temperature increase from 25 to 40 °C; (2) the thermophilic stage, in which the highest microbial counts were found, most of which corresponded to the highest temperatures reached and maintained between 40 and 62 °C, and, consequently, to the greatest decrease in water content (from 78 to 41%); and (3) the cooling phase, when the temperature dropped to 23–25 °C. The aeration and mainly the microbial activity were responsible for most of the water evaporation. Microbial activity in biodrying of HMOW ended on day 32, when the humidity was lower than 30% and the water activity (aw) was below 0.8. After that, moisture loss was carried out only by convection and radiation. Obtained biodried organic waste (10% water-content) could be used as an alternative fuel in many industries.
Monitoring Dietary Supplements for Undeclared Diuretics as a Strategy for Preventing Unintentional Doping
Authors: Kozhuharov Vanya Rangelov , Ivanov Kalin , Ivanova Stanislava
Published: January 2025

Diuretics are essential medicines used in the management of hypertension, heart failure, edema, and other medical conditions. Due to their effectiveness in promoting water loss, many cases of undeclared diuretics in dietary supplements (DSs) have been reported. Most of these DSs were marketed for “weight loss promotion” and “detoxification”. Diuretics are regarded as doping compounds as well because of their significant potential to cause weight loss or mask the usage of other doping compounds. The intake of DSs that contain undeclared diuretics can result in serious consequences, including side effects, drug–drug interactions, and the violation of anti-doping rules if such products are taken by professional athletes. The aim of the present study was to develop a rapid, sensitive, and cost-effective high-performance liquid chromatography (HPLC) method for monitoring DSs for undeclared diuretics. The validated method allows for simultaneous monitoring for furosemide, hydrochlorothiazide, and torasemide. The LOD and LOQ were 0.78 μg/mL and 2.38 μg/mL for hydrochlorothiazide, 0.99 μg/mL and 3.01 μg/mL for torasemide, and 0.69 μg/mL and 2.08 μg/mL for furosemide. The method was successfully utilized to screen ten DSs for undeclared diuretics. Contamination was detected in only one sample. These results underscore the critical need for regulatory oversight and independent quality control of DSs. Implementing routine screening could significantly reduce the risk of adverse health effects and unintentional doping among athletes. Ultimately, this study contributes to enhancing consumer safety and ensuring fair competition in sports.
Improved Surface Solar Irradiation Estimation Using Satellite Data and Feature Engineering
Authors: Kim Jinyong , Kim Eunkyeong , Jung Seunghwan , Kim Minseok , Kim Baekcheon , Kim Sungshin
Published: January 2025

Planning an optimal installation site to maximize power-generation efficiency is crucial for the effective operation of photovoltaic power plants. Achieving this requires accurate, reliable information on solar irradiation across different regions. However, ground-based measurements using pyranometers are resource-intensive, requiring substantial time and human effort, and their measurement range is limited, complicating data collection. To address this, we propose a method to accurately estimate surface solar irradiation (SSI) using satellite data and feature engineering. By leveraging satellite data as the primary input, we overcome the spatial and temporal limitations of ground-based measurements. Additionally, we improve SSI-estimation performance through designed features based on the geometric information of the Sun and satellite. A hybrid deep neural network model is used for SSI estimation, effectively handling data of varying dimensions. Hourly SSI data from 12 synoptic observation stations collected over one year, excluded from the model’s training and validation sets, are utilized to evaluate the proposed method. Experimental results demonstrate strong SSI-estimation performance, with an average root mean square error (RMSE) of 0.1813 MJ/m2, a relative RMSE of 0.1601, mean absolute error of 0.1159 MJ/m2, and coefficient of determination of 0.9680.
The Architectural Layout and Degree of Preservation of the Sanctuary of Pachacamac Archaeological Complex (2nd to 16th Centuries AD, Peru) from the Morphometric Analysis of Orthophotogrammetric Data
Authors: Magnini Luigi , Del Gaudio Pierdomenico , Apa Maria Ilaria Pannaccione , Pozzi-Escot Denise , Oshiro Janet , Angeles Rommel , Ventura Guido
Published: January 2025

Archaeological complexes are characterized by different degrees of damage related to both natural events and anthropogenic triggers. The damage may be assessed through direct observation or remotely acquired data. Here, we present a morphometric analysis of a digital surface model (DSM) obtained from an orthophotogrammetric survey at the Sanctuary of Pachacamac Archaeological Complex, Peru (2nd to 16th centuries AD), which includes temples, enclosures, huacas, and roads. We determine different morphometric parameters to quantitatively describe the architectural layout of the site. These are aspect, slope, range, and topographic position index (TPI). We applied a modified TPI classification to measure the different degrees of preservation of the walls of the archaeological structures and recognize preserved, partly preserved, partly destroyed, and destroyed walls. The walls of the site show different degrees of preservation related to the damage associated with earthquakes and El Niño destructive events. The architectural layout of the archaeological site is defined by NW-SE and NE-SW striking walls. This is due to buildings constructed along the two main NW-SE and NE-SW striking roads of the Qhapac–Ñan road network. The prevailing El Niño wind direction may also explain the observed architectural layout. Morphometric parameters can be used to estimate the degree of conservation of archaeological sites. Our analytical approach can be applied to modern buildings damaged by natural events or human activities.
Aftershock Spatiotemporal Activity and Coseismic Slip Model of the 2022 Mw 6.7 Luding Earthquake: Fault Geometry Structures and Complex Rupture Characteristics
Authors: Hu Qibo , Liang Hongwei , Li Hongyi , Shan Xinjian , Zhang Guohong
Published: January 2025

On 5 September 2022, the moment magnitude (Mw) 6.7 Luding earthquake struck in the Xianshuihe Fault system on the eastern edge of the Tibet Plateau, illuminating the seismic gap in the Moxi segment. The fault system geometry and rupture process of this earthquake are relatively complex. To better understand the underlying driving mechanisms, this study first uses the Interferometric Synthetic Aperture Radar (InSAR) technique to obtain static surface displacements, which are then combined with Global Positioning System (GPS) data to invert the coseismic slip distribution. A machine learning approach is applied to extract a high-quality aftershock catalog from the original seismic waveform data, enabling the analysis of the spatiotemporal characteristics of aftershock activity. The catalog is subsequently used for fault fitting to determine a reliable fault geometry. The coseismic slip is dominated by left-lateral strike-slip motion, distributed within a depth range of 0–15 km, with a maximum fault slip > 2 m. The relocated catalog contains 15,571 events. Aftershock activity is divided into four main seismic clusters, with two smaller clusters located to the north and south and four interval zones in between. The geometry of the five faults is fitted, revealing the complexity of the Xianshuihe Fault system. Additionally, the Luding earthquake did not fully rupture the Moxi segment. The unruptured areas to the north of the mainshock, as well as regions to the south near the Anninghe Fault, pose a potential seismic hazard.
Increased Contribution of Extended Vegetation Growing Season to Boreal Terrestrial Ecosystem GPP Enhancement
Authors: Yu Meng , Cao Yunfeng , Tian Jiaxin , Ren Boyu
Published: January 2025

Rapid Arctic warming is driving significant changes in boreal vegetation phenology and productivity. The potentially asynchronous response of these processes could substantially alter the relative impacts of phenological shifts on variations in gross primary productivity (GPP), but this remains poorly understood. The objective of this study is to quantify the impact of phenology extension on boreal ecosystem GPP changes across different periods from 1982 to 2018. To achieve this, we developed a statistical model that integrates vegetation phenology and physiology, and introduced a new metric, the Relative Increment Effect (RIE), to assess the contribution of phenology extension to GPP increase. Our analysis revealed that phenology extension became the dominant driver of GPP increment over time. Specifically, the overall RIE for boreal vegetation increased by 22% from the earlier period (P1: 1982–2000, 3.2) to the more recent period (P2: 2001–2018, 3.93). This increase was more pronounced for grass and shrub ecosystems. Spatial patterns showed that RIE increases were particularly concentrated at high latitudes, especially in northern Siberia. These findings suggested that phenology extension was playing an increasing role in regulating boreal ecosystem productivity, with significant implications for the boreal carbon budget under future warming scenarios.
CloudTran++: Improved Cloud Removal from Multi-Temporal Satellite Images Using Axial Transformer Networks
Authors: Christopoulos Dionysis , Ntouskos Valsamis , Karantzalos Konstantinos
Published: January 2025

We present a method for cloud removal from satellite images using axial transformer networks. The method considers a set of multi-temporal images in a given region of interest, together with the corresponding cloud masks, and produces a cloud-free image for a specific day of the year. We propose the combination of an encoder-decoder model employing axial attention layers for the estimation of the low-resolution cloud-free image, together with a fully parallel upsampler that reconstructs the image at full resolution. The method is compared with various baselines and state-of-the-art methods on Sentinel-2 datasets of different coverage, showing significant improvements across multiple standard metrics used for image quality assessment.
Intelligent Target Detection in Synthetic Aperture Radar Images Based on Multi-Level Fusion
Authors: Liu Qiaoyu , Ye Ziqi , Zhu Chenxiang , Ouyang Dongxu , Gu Dandan , Wang Haipeng
Published: January 2025

Due to the unique imaging mechanism of SAR, targets in SAR images present complex scattering characteristics. As a result, intelligent target detection in SAR images has been facing many challenges, which mainly lie in the insufficient exploitation of target characteristics, inefficient characterization of scattering features, and inadequate reliability of decision models. In this respect, we propose an intelligent target detection method based on multi-level fusion, where pixel-level, feature-level, and decision-level fusions are designed for enhancing scattering feature mining and improving the reliability of decision making. The pixel-level fusion method through the channel fusion of original images and their features after scattering feature enhancement represents an initial exploration of image fusion. Two feature-level fusion methods are conducted using respective migratable fusion blocks, namely DBAM and FDRM, presenting higher-level fusion. Decision-level fusion based on DST can not only consolidate complementary strengths in different models but also incorporate human or expert involvement in proposition for guiding effective decision making. This represents the highest-level fusion integrating results by proposition setting and statistical analysis. Experiments of different fusion methods integrating different features were conducted on typical target detection datasets. As shown in the results, the proposed method increases the mAP by 16.52%, 7.1%, and 3.19% in ship, aircraft, and vehicle target detection, demonstrating high effectiveness and robustness.
Research on the Wavelet Denoising Algorithm for Thorpe Analysis Based on the Radiosonde Data
Authors: Liao Qixiang , Sheng Zheng , Guo Peng
Published: January 2025

Thorpe analysis is a commonly used method to study turbulence, an important research object in the field of atmospheric science. However, using Thorpe analysis to retrieve turbulence parameters from radiosonde data can reduce inversion accuracy due to instrument noise. Therefore, this paper presents a new wavelet denoising method to determine the optimal decomposition layer based on adaptative Monte Carlo simulation, and the denoising effect of this method is tested by simulation data and real detection data. Numerical experiments shows that the stability and accuracy of the proposed new method are better than those of the previous methods.
Retrieval and Evaluation of Global Surface Albedo Based on AVHRR GAC Data of the Last 40 Years
Authors: Li Shaopeng , Xiao Xiongxin , Neuhaus Christoph , Wunderle Stefan
Published: January 2025

In this study, the global land surface albedo namely GAC43 was retrieved for the years 1979 to 2020 using Advanced Very High Resolution Radiometer (AVHRR) global area coverage (GAC) data onboard National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational (MetOp) satellites. We provide a comprehensive retrieval process of the GAC43 albedo, followed by a comprehensive assessment against in situ measurements and three widely used satellite-based albedo products, the third edition of the CM SAF cLoud, Albedo and surface RAdiation (CLARA-A3), the Copernicus Climate Change Service (C3S) albedo product, and MODIS BRDF/albedo product (MCD43). Our quantitative evaluations indicate that GAC43 demonstrates the best stability, with a linear trend of ±0.002 per decade at nearly all pseudo invariant calibration sites (PICS) from 1982 to 2020. In contrast, CLARA-A3 exhibits significant noise before the 2000s due to the limited availability of observations, while C3S shows substantial biases during the same period due to imperfect sensors intercalibrations. Extensive validation at globally distributed homogeneous sites shows that GAC43 has comparable accuracy to C3S, with an overall RMSE of approximately 0.03, but a smaller positive bias of 0.012. Comparatively, MCD43C3 shows the lowest RMSE (~0.023) and minimal bias, while CLARA-A3 displays the highest RMSE (~0.042) and bias (0.02). Furthermore, GAC43, CLARA-A3, and C3S exhibit overestimation in forests, with positive biases exceeding 0.023 and RMSEs of at least 0.028. In contrast, MCD43C3 shows negligible bias and a smaller RMSE of 0.015. For grasslands and shrublands, GAC43 and MCD43C3 demonstrate comparable estimation uncertainties of approximately 0.023, with close positive biases near 0.09, whereas C3S and CLARA-A3 exhibit higher RMSEs and biases exceeding 0.032 and 0.022, respectively. All four albedo products show significant RMSEs around 0.035 over croplands but achieve the highest estimation accuracy better than 0.020 over deserts. It is worth noting that significant biases are typically attributed to insufficient spatial representativeness of the measurement sites. Globally, GAC43 and C3S exhibit similar spatial distribution patterns across most land surface conditions, including an overestimation compared to MCD43C3 and an underestimation compared to CLARA-A3 in forested areas. In addition, GAC43, C3S, and CLARA-A3 estimate higher albedo values than MCD43C3 in low-vegetation regions, such as croplands, grasslands, savannas, and woody savannas. Besides the fact that the new GAC43 product shows the best stability covering the last 40 years, one has to consider the higher proportion of backup inversions before 2000. Overall, GAC43 offers a promising long-term and consistent albedo with good accuracy for future studies such as global climate change, energy balance, and land management policy.
Hierarchical Optimization Segmentation and Parameter Extraction of Street Trees Based on Topology Checking and Boundary Analysis from LiDAR Point Clouds
Authors: Kou Yuan , Gao Xianjun , Zhang Yue , Liu Tianqing , An Guanxing , Ye Fen , Tian Yongyu , Chen Yuhan
Published: January 2025

Roadside tree segmentation and parameter extraction play an essential role in completing the virtual simulation of road scenes. Point cloud data of roadside trees collected by LiDAR provide important data support for achieving assisted autonomous driving. Due to the interference from trees and other ground objects in street scenes caused by mobile laser scanning, there may be a small number of missing points in the roadside tree point cloud, which makes it familiar for under-segmentation and over-segmentation phenomena to occur in the roadside tree segmentation process. In addition, existing methods have difficulties in meeting measurement requirements for segmentation accuracy in the individual tree segmentation process. In response to the above issues, this paper proposes a roadside tree segmentation algorithm, which first completes the scene pre-segmentation through unsupervised clustering. Then, the over-segmentation and under-segmentation situations that occur during the segmentation process are processed and optimized through projection topology checking and tree adaptive voxel bound analysis. Finally, the overall high-precision segmentation of roadside trees is completed, and relevant parameters such as tree height, diameter at breast height, and crown area are extracted. At the same time, the proposed method was tested using roadside tree scenes. The experimental results show that our methods can effectively recognize all trees in the scene, with an average individual tree segmentation accuracy of 99.07%, and parameter extraction accuracy greater than 90%.
Automatic Cleaning of Time Series Data in Rural Internet of Things Ecosystems That Use Nomadic Gateways
Authors: Dembski Jerzy , Kołakowska Agata , Wiszniewski Bogdan
Published: January 2025

A serious limitation to the deployment of IoT solutions in rural areas may be the lack of available telecommunications infrastructure enabling the continuous collection of measurement data. A nomadic computing system, using a UAV carrying an on-board gateway, can handle this; it leads, however, to a number of technical challenges. One is the intermittent collection of data from ground sensors governed by weather conditions for the UAV measurement missions. Therefore, each sensor should be equipped with software that allows for the cleaning of collected data before transmission to the fly-over nomadic gateway from erroneous, misleading, or otherwise redundant data—to minimize their volume and fit them in the limited transmission window. This task, however, may be a barrier for end devices constrained in several ways, such as limited energy reserve, insufficient computational capability of their MCUs, and short transmission range of their RAT modules. In this paper, a comprehensive approach to these problems is proposed, which enables the implementation of an anomaly detector in time series data with low computational demand. The proposed solution uses the analysis of the physics of the measured signals and is based on a simple anomaly model whose parameters can be optimized using popular AI techniques. It was validated during a full 10-month vegetation period in a real Rural IoT system deployed by Gdańsk Tech.
The Realization of a Three-Dimensional Temperature Measurement System with a Two-Dimensional Sensor Array and the Demonstration of the Deformation Effect of Gravity on the Heating Patterns
Authors: Samuk Dogan Can , Cakir Oguzhan
Published: January 2025

Electric heaters are widely used owing to their portability, fast heating, single-focus heating, and energy efficiency advantages. Manufacturers provide customers with information on the power consumption and energy efficiency classes of heaters but do not provide any information on heating patterns. Knowing the heating pattern enables users to select the correct heater, which has a significant effect on comfort, health, energy efficiency, industrial process performance, plant growth, and climate change. In previous studies, two-dimensional temperature measurements were performed using sensor arrays. However, the three-dimensional heating patterns of the heaters have not been extracted, and the deformation effect of gravity on the heating patterns has not been demonstrated. In this study, a temperature measurement system with 64 temperature sensors placed at equal intervals in the xz-plane was designed and implemented. Then, the fan heater was moved along the y-axis at intervals of 10 cm from 0 to 100 cm, and three-dimensional heating patterns were obtained for different fan voltages. As part of the research objectives, the deformation effect of gravity on the heating pattern was revealed, and the shift in the maximum temperature point on the +z-axis was measured. The mathematical formula for the maximum temperature value was derived based on the fan voltage and the distance between the heater and the sensor array. The goodness-of-fit statistical values for the derived mathematical formula for the 55 temperature measurements were calculated as the root mean square error of 1.9543 and R-squared of 99.43%, demonstrating the accuracy of the presented model.
Table Extraction with Table Data Using VGG-19 Deep Learning Model
Authors: Iqbal Muhammad Zahid , Garg Nitish , Ahmed Saad Bin
Published: January 2025

In recent years, significant progress has been achieved in understanding and processing tabular data. However, existing approaches often rely on task-specific features and model architectures, posing challenges in accurately extracting table structures amidst diverse layouts, styles, and noise contamination. This study introduces a comprehensive deep learning methodology that is tailored for the precise identification and extraction of rows and columns from document images that contain tables. The proposed model employs table detection and structure recognition to delineate table and column areas, followed by semantic rule-based approaches for row extraction within tabular sub-regions. The evaluation was performed on the publicly available Marmot data table datasets and demonstrates state-of-the-art performance. Additionally, transfer learning using VGG-19 is employed for fine-tuning the model, enhancing its capability further. Furthermore, this project fills a void in the Marmot dataset by providing it with extra annotations for table structure, expanding its scope to encompass column detection in addition to table identification.
Pedagogical Documentation as a “Bridge” Between Parents and the Early Childhood Curriculum
Authors: Kakana Domna (Mika) , Gkloumpou Alexandra
Published: January 2025

Parents’ involvement in early childhood education is of great importance. In Greece, many educators still hesitate to involve parents in their school’s daily program. They also do not use pedagogical documentation in the educational process as it is not included in the official curriculum. Our main goal was to bring parents closer to the early childhood curriculum, in an active and participatory way, through the documentation process. The main research question referred to the way in which the systematic use of pedagogical documentation can help parents understand the kindergarten’s daily curriculum and participate in it in a new way, in a country where pedagogical documentation is not mandatory. We used collaborative action research between ten kindergarten educators from five schools and two researchers from the same university department. The methodological tools were a researchers’ diary, two digital questionnaires for the educators (pre-/post-implementation) and a post-implementation digital questionnaire for the parents. The results showed that the documentation helped the educators to bring the parents closer to the kindergarten’s daily program and made them feel as if they could participate in it creatively. Also, the documentation derived from the children, educators and parents constructed a community of relations, participation, shared values and learning among them.