bluuebunny/crossref_metadata_2025 huggingface dataset:
High-Precision Rayleigh Doppler Lidar with Fiber Solid-State Cascade Amplified High-Power Single-Frequency Laser for Wind Measurement
Authors: Yang Bin , Bu Lingbing , Huang Cong , Tan Zhiqiang , Hu Zhongyu , Shu Shijiang , Deng Chen , Li Binbin , Ding Jianyong , Yu Guangli , Wang Yungang , Wang Cong , Lin Weixia , Zong Weiguo
Published: February 2025

We introduce a novel Rayleigh Doppler lidar (RDLD) system that utilizes a high-power single-frequency laser with over 60 W average output power, achieved through fiber solid-state cascade amplification. This lidar represents a significant advancement by addressing common challenges such as mode hopping and multi-longitudinal mode issues. Designed for atmospheric wind and temperature profiling, the system operates effectively between altitudes of 30 km and 70 km. Key performance metrics include wind speed and temperature measurement errors below 7 m/s and 3 K, respectively, at 60 km, based on 30 min temporal and 1 km spatial resolutions. Observation data align closely with ECMWF reanalysis data, showing high correlation coefficients of 0.98, 0.91, and 0.94 for zonal wind, meridional wind, and temperature, respectively. Continuous observations also reveal detailed wind field variations caused by gravity waves, demonstrating the system’s high resolution and reliability. These results highlight the RDLD system’s potential for advancing meteorological monitoring, atmospheric dynamics studies, and environmental safety applications.
Perturbation Matters: A Novel Approach for Semi-Supervised Remote Sensing Imagery Change Detection
Authors: Peng Daifeng , Liu Min , Guan Haiyan
Published: February 2025

Due to the challenge of acquiring abundant labeled samples, semi-supervised change detection (SSCD) approaches are becoming increasingly popular in tackling CD tasks with limited labeled data. Despite their success, these methods tend to come with complex network architectures or cumbersome training procedures, which also ignore the domain gap between the labeled data and unlabeled data. Differently, we hypothesize that diverse perturbations are more favorable to exploit the potential of unlabeled data. In light of this spirit, we propose a novel SSCD approach based on Weak–strong Augmentation and Class-balanced Sampling (WACS-SemiCD). Specifically, we adopt a simple mean-teacher architecture to deal with labeled branch and unlabeled branch separately, where supervised learning is conducted on the labeled branch, while weak–strong consistency learning (e.g., sample perturbations’ consistency and feature perturbations’ consistency) is imposed for the unlabeled. To improve domain generalization capacity, an adaptive CutMix augmentation is proposed to inject the knowledge from the labeled data into the unlabeled data. A class-balanced sampling strategy is further introduced to mitigate class imbalance issues in CD. Particularly, our proposed WACS-SemiCD achieves competitive SSCD performance on three publicly available CD datasets under different labeled settings. Comprehensive experimental results and systematic analysis underscore the advantages and effectiveness of our proposed WACS-SemiCD.
Spatial Downscaling of Satellite Sea Surface Wind with Soft-Sharing Multi-Task Learning
Authors: Yue Yinlei , Liu Jia , Sun Yongjian , Ren Kaijun , Deng Kefeng , Deng Ke
Published: February 2025

Sea surface wind (SSW) plays a pivotal role in numerous research endeavors pertaining to meteorology and oceanography. SSW fields derived from remote sensing have been widely applied; however, regional and local studies require higher-spatial-resolution SSW fields to identify refined details. Most of the existing studies based on deep learning have constructed mappings from low-resolution inputs to high-resolution downscaled estimates. However, these methods have failed to capture the relationships between multiple variables as revealed by physical processes. Therefore, this paper proposes a spatial downscaling approach for satellite sea surface wind that employs soft-sharing multi-task learning. Sea surface temperature and water vapor are included as auxiliary variables for SSW, considering the close correlation revealed by physical principles and data availability. The spatial downscaling of auxiliary variables is designed as an auxiliary task and integrated into a multi-task learning network with generative adversarial network and dual regression structures. The proposed multi-task downscaling network achieves flexible parameter sharing and information exchange between tasks through a soft-sharing mechanism and bridge modules. Comprehensive experiments were conducted with WindSat SSW products at 0.25° from Remote Sensing Systems. The experimental results validate the outstanding downscaling capability of the proposed methodology with respect to precision in comparison with buoy measurements and reconstruction quality.
The Responses of Vegetation Production and Evapotranspiration to Inter-Annual Summer Drought in Northeast Asia Dryland Regions (NADRs)
Authors: Kang Wenping , Kang Sinkyu , Liu Shulin , Wang Tao
Published: February 2025

The impacts of drought on Gross Primary Productivity (GPP) and Evapotranspiration (ET) play an important role in understanding the carbon–water process of dryland ecosystems. However, just via correlation analysis, the response mechanism of vegetation production and ET to droughts is not well understood. Based on a modified Vegetation Photosynthesis Model (VPM) and a revised Penman–Monteith (PM) model, GPP and ET were simulated to examine their sensitivity to drought and quantitative dynamics among biomes with the drought index in NADRs. The diverse response of GPP and ET to drought depending on biomes, grassland, barren/sparse vegetation and shrub showed a positive response to summer drought, while cropland and forest showed a negative response to summer drought. From the normal summers to extreme drought summers, GPP and ET reduced by 0.36 g C m−2 day−1 and 0.18 mm day−1, nearly 10.54% and 12.77%, respectively. Some compensation mechanisms (i.e., physiological changes of vegetation species to resistant drought) or drought timescale weaken the drought impacts in insignificant correlated regions (GPP or ET and SPEI) with lower reduction rates. Compared with persistent or multiple droughts, the impacts of abrupt wet–dry shifts on GPP and ET were weak with lower rates (4.44% for GPP, 0.92% for ET). Notably, the wet winter and warm spring weakens the summer drought impacts on GPP in some parts of grasslands. These observations would be useful to understand the ecosystem process and to account for the dynamics of ecosystem water use efficiency during drought disturbance in depth.
RSAM-Seg: A SAM-Based Model with Prior Knowledge Integration for Remote Sensing Image Semantic Segmentation
Authors: Zhang Jie , Li Yunxin , Yang Xubing , Jiang Rui , Zhang Li
Published: February 2025

High-resolution remote sensing satellites have revolutionized remote sensing research, yet accurately segmenting specific targets from complex satellite imagery remains challenging. While the Segment Anything Model (SAM) has emerged as a promising universal segmentation model, its direct application to remote sensing imagery yields suboptimal results. To address these limitations, we propose RSAM-Seg, a novel deep learning model adapted from SAM specifically designed for remote sensing applications. Our model incorporates two key components: Adapter-Scale and Adapter-Feature modules. The Adapter-Scale modules, integrated within Vision Transformer (ViT) blocks, enhance model adaptability through learnable transformations, while the Adapter-Feature modules, positioned between ViT blocks, generate image-informed prompts by incorporating task-specific information. Extensive experiments across four binary and two multi-class segmentation scenarios demonstrate the superior performance of RSAM-Seg, achieving an F1 score of 0.815 in cloud detection, 0.834 in building segmentation, and 0.755 in road extraction, consistently outperforming established architectures like U-Net, DeepLabV3+, and Segformer. Moreover, RSAM-Seg shows significant improvements of up to 56.5% in F1 score compared to the original SAM. In addition, RSAM-Seg maintains robust performance in few-shot learning scenarios, achieving an F1 score of 0.656 with only 1% of the training data and increasing to 0.815 with full data availability. Furthermore, RSAM-Seg exhibits the capability to detect missing areas within the ground truth of certain datasets, highlighting its capability for completion.
Re-Using Historical Aerial Imagery for Obtaining 3D Data of Beach-Dune Systems: A Novel Refinement Method for Producing Precise and Comparable DSMs
Authors: Almonacid-Caballer Jaime , Cabezas-Rabadán Carlos , Gorkovchuk Denys , Palomar-Vázquez Jesús , Pardo-Pascual Josep E.
Published: February 2025

This study explores the potential of repurposing historical aerial photographs to produce high-accuracy digital surface models (DSMs) at regional scales. A novel methodology is introduced, incorporating road points for quality control and refinement to enhance the precision and comparability of multitemporal DSMs. The method consists of two phases. The first is the photogrammetric phase, where DSMs are generated using photogrammetric and structure from motion (SfM) techniques. The second is the refinement phase, which uses a large number (millions) of points extracted from road centrelines to evaluate altimetric residuals—defined as the differences between photogrammetric DSMs and a reference DSM. These points are filtered to ensure that they represent stable positions. The analysis shows that the initial residuals exhibit geographical trends, rather than random behaviour, that are removed after the refinement. An application example covering the whole coast of the Valencian region (Eastern Spain, 518 km of coastline) shows the obtention of a series composed of six DSMs. The method achieves levels of accuracy (0.15–0.20 m) comparable to modern LiDAR techniques, offering a cost-effective alternative for three-dimensional characterisation. The application to the foredune and coastal environment demonstrated the method’s effectiveness in quantifying sand volumetric changes through comparison with a reference DSM. The achieved accuracy is crucial for establishing precise sedimentary balances, essential for coastal management. At the same time, this method shows significant potential for its application in other dynamic landscapes, as well as urban or agricultural monitoring.
Imaging Cultural Heritage at Different Scales: Part II, the Meso-Scale (Sites)
Authors: Piroddi Luca , Abu Zeid Nasser , Calcina Sergio Vincenzo , Capizzi Patrizia , Capozzoli Luigi , Catapano Ilaria , Cozzolino Marilena , D’Amico Sebastiano , Lasaponara Rosa , Tapete Deodato
Published: February 2025

Non-invasive sensing techniques have become a cornerstone in the study and preservation of Cultural Heritage. These techniques offer a means to investigate the internal structure and surface properties of precious and delicate objects without causing damage. This article is the second of three review articles exploring contact and non-contact imaging methods applied to Cultural Heritage at various scales encompassing micro- (i.e., manufacts), meso- (sites), and macro-scales (landscapes). The unifying factor of these techniques is their ability to infer variations in geometrical and physical properties across inspected surfaces or volumes. This allows researchers to discover new historical sites, map their spatial extent, and characterize their material features at different scales, from landscapes to artifacts. This second part focuses on the meso-scale, encompassing the inspection, documentation, study, and characterization of historical and archeological sites, monuments, and submerged sites, using both contact and remote sensing techniques.
SBAS-InSAR Monitoring of Landslides and Glaciers Along the Karakoram Highway Between China and Pakistan
Authors: Khan Basit Ali , Zhao Chaoying , Kakar Najeebullah , Chen Xuerong
Published: February 2025

Global assessments of landslide impact on critical communication infrastructure have become urgent because of rising occurrences related to human activities and climate change. The landslide and glacial slide susceptibility along the Karakoram Highway poses a significant threat to the infrastructure ecosystem, local communities, and the critical China–Pakistan Economic Corridor. This research paper utilized the Small Baseline Subset InSAR technique to monitor the deformation patterns over the past 5 years, yielding high-resolution insights into the terrain instability in this geologically active region. The SBAS time series results reveal that the substantial cumulative deformation in our study area ranges from 203 mm to −486 mm, with annual deformation rates spanning from 62 mm/year to −104 mm/year. Notably, the deformation that occurred is mainly concentrated in the northern section of our study area. The slope’s aspect is responsible for the maximum deformed material flow towards the Karakoram Highway via steep slopes, lost glacial formations, and the climate variations that cause the instability of the terrain. The given pattern suggests that the northern area of the Karakoram Highway is exposed to a greater risk from the combined influence of glacial slides, landslides, and climatic shifts, which call for the increased monitoring of the Karakoram Highway. The SBAS-InSAR method is first-rate in deformation monitoring, and it provides a scientific basis for developing real-time landslide monitoring systems. The line of sight limitations and the complexity and imprecision of weather-induced signal degradation should be balanced through additional data sources, such as field surveys to conduct large slide and glacial slide susceptibility evaluations. These research results support proactive hazard mitigation and infrastructure planning along the China–Pakistan Economic Corridor by incorporating SBAS-InSAR monitoring into the original planning. The country’s trade policymakers and national level engineers can enhance transport resilience, efficiently manage the landslide and glacial slide risks, and guarantee safer infrastructure along this strategic trade route.
A Multiple-Input Multiple-Output Synthetic Aperture Radar Echo Separation and Range Ambiguity Suppression Processing Framework for High-Resolution Wide-Swath Imaging
Authors: Zhao Haonan , Zhang Zhimin , Chen Zhen , Fan Huaitao , Lv Zongsen , Bi Jianzhong
Published: February 2025

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) is a promising scheme for high-resolution wide-swath (HRWS) imaging. After echo separation processing, a MIMO-SAR system can provide many equivalent phase centers (EPCs) in azimuth. However, EPC duplication occurs for traditional monostatic systems with uniform antenna arrays, leading to system resource waste. Moreover, range ambiguity suppression is a necessary process for wide-swath SAR systems. In this paper, a novel MIMO-SAR echo separation and range ambiguity suppression processing framework is proposed for HRWS imaging. A set of transmission delays is introduced to the transmit channels to displace the repetitive EPCs. The transmission delays can also be used to flexibly control the performance of echo separation. A wide-null beamformer is employed to accomplish echo separation and ambiguity suppression simultaneously. The proposed framework is designed for real-time processing and therefore does not require frequency-domain operations. Finally, the proposed framework is verified through point target and distributed scene simulation experiments.
Multi-Temporal Remote Sensing Satellite Data Analysis for the 2023 Devastating Flood in Derna, Northern Libya
Authors: Shults Roman , Farahat Ashraf , Usman Muhammad , Rahman Md Masudur
Published: February 2025

Floods are considered to be among the most dangerous and destructive geohazards, leading to human victims and severe economic outcomes. Yearly, many regions around the world suffer from devasting floods. The estimation of flood aftermaths is one of the high priorities for the global community. One such flood took place in northern Libya in September 2023. The presented study is aimed at evaluating the flood aftermath for Derna city, Libya, using high resolution GEOEYE-1 and Sentinel-2 satellite imagery in Google Earth Engine environment. The primary task is obtaining and analyzing data that provide high accuracy and detail for the study region. The main objective of study is to explore the capabilities of different algorithms and remote sensing datasets for quantitative change estimation after the flood. Different supervised classification methods were examined, including random forest, support vector machine, naïve-Bayes, and classification and regression tree (CART). The various sets of hyperparameters for classification were considered. The high-resolution GEOEYE-1 images were used for precise change detection using image differencing (pixel-to-pixel comparison and geographic object-based image analysis (GEOBIA) for extracting building), whereas Sentinel-2 data were employed for the classification and further change detection by classified images. Object based image analysis (OBIA) was also performed for the extraction of building footprints using very high resolution GEOEYE images for the quantification of buildings that collapsed due to the flood. The first stage of the study was the development of a workflow for data analysis. This workflow includes three parallel processes of data analysis. High-resolution GEOEYE-1 images of Derna city were investigated for change detection algorithms. In addition, different indices (normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), transformed NDVI (TNDVI), and normalized difference moisture index (NDMI)) were calculated to facilitate the recognition of damaged regions. In the final stage, the analysis results were fused to obtain the damage estimation for the studied region. As the main output, the area changes for the primary classes and the maps that portray these changes were obtained. The recommendations for data usage and further processing in Google Earth Engine were developed.
Correcting Forecast Time Biases in CMA-MESO Using Himawari-9 and Time-Shift Method
Authors: Song Xingtao , Han Wei , Sun Haofei , Wang Hao , Xu Xiaofeng
Published: February 2025

The accurate forecasting of time, intensity, and spatial distribution is fundamental to weather prediction. However, the limitations of numerical weather prediction (NWP) models, as well as uncertainties in inital conditions, often lead to temporal biases in forecasts. This study addresses these biases by employing visible reflectance data from the Himawari-9/AHI satellite and RTTOV (TOVS radiation transfer) simulations derived from CMA-MESO model outputs. The time-shift method was applied to analyze two precipitation events—20 October 2023 and 30 April 2024—in order to assess its impact on precipitation forecasts. The results indicate the following: (1) the time-shift method improved cloud simulations, necessitating a 30 min advance for Case 1 and a 3.5 h delay for Case 2; (2) time-shifting reduced the standard deviation of observation-minus-background (OMB) bias in certain regions and enhanced spatial uniformity; (3) the threat score (TS) demonstrated an improvement in forecast accuracy, particularly in cases exhibiting significant movement patterns. The comparative analysis demonstrates that the time-shift method effectively corrects temporal biases in NWP models, providing forecasters with a valuable tool to optimize predictions through the integration of high-temporal- and spatial-resolution visible light data, thereby leading to more accurate and reliable weather forecasts.
Remote Sensing Tool for Reservoir Volume Estimation
Authors: Pimenta João , Fernandes João Nuno , Azevedo Alberto
Published: February 2025

Efficient reservoir management is essential for ensuring water security and flood control, as well as hydroelectric power generation. Accurate volume measurements are key to optimizing these functions, but traditional methods—such as in situ measurements and physical surveys—are often time-consuming, costly, and unfeasible in many regions due to financial or geographical limitations. This study introduces a novel globally accessible remote sensing tool designed to overcome these challenges by providing a more effective approach to reservoir volume estimation. The tool leverages high-resolution satellite imagery from Sentinel-2 and integrates it with official storage capacity data and the GLOBAthy dataset to calculate surface area and reservoir volume across varying water levels over user-defined timeframes. Users can select reservoirs, date ranges, and cloud cover thresholds via an intuitive interface, which then generates time-series data of reservoir volumes. The tool employs machine learning algorithms to improve the precision of water surface delineation and volume calculations, accounting for complex environmental factors like cloud cover and built structures such as bridges. This remote sensing tool was tested on reservoirs of varying sizes and topographies in Portugal and California, USA, demonstrating a high accuracy with a Mean Absolute Percentage Error (MAPE) of 5.35% and a correlation coefficient (R2) of 0.90 when compared to official records. By offering a cost-effective, scalable, totally remote, and timely solution, the tool enables improved reservoir monitoring, particularly in remote or otherwise inaccessible areas. Ultimately, this research contributes to global water resources management, enhancing the sustainability and resilience of reservoir operations around the world.
A New Method for Determining the Wave Turbopause Based on SABER/TIMED Data
Authors: Wang Zewei , Xiao Cunying , Hu Xiong , Yang Junfeng , Cheng Xuan , Li Kuan , Xiao Luo , Wu Xiaoqi , Yu Yang , Li Hao
Published: February 2025

The determination of the wave turbopause is vital for understanding the dynamics of atmospheric processes in the Mesosphere and Lower Thermosphere (MLT). In this study, we introduce a novel approach for identifying the wave turbopause, using SABER/TIMED temperature data and number density data, addressing the limitations associated with traditional linear fitting methods that can lead to ambiguities in results. Our approach is grounded in the conservation-of-energy principle, which facilitates the introduction of an energy index to effectively delineate the boundaries of the turbopause layer. This method allows us to define several key parameters: the lower boundary height, upper boundary height, turbopause height, and turbopause layer thickness. Analyzing long-term SABER data specifically over Beijing, we observed that the turbopause layer exhibited significant seasonal and inter-annual variations. Our findings indicated that the average height of the lower boundary was approximately 69.17 km, while the average height of the upper boundary was around 93.85 km. The energy index provided a comprehensive assessment of atmospheric wave activity, revealing periodic variations at different altitudes within the turbopause layer. The proposed method not only offers a more precise and applicable characterization of the turbopause but also enhances our capacity for atmospheric modeling and empirical investigations. Future work will focus on extending this methodology, to analyze the comprehensive SABER data collected globally. We aim to uncover insights into the seasonal characteristics of the turbopause across various geographic regions, allowing for a more detailed understanding of its behavior under different climatic conditions, ultimately contributing to a deeper understanding of MLT dynamics.
Impacts of Reference Precipitation on the Assessment of Global Precipitation Measurement Precipitation Products
Authors: Zhang Ye , Wang Leizhi , Li Yilan , Wang Yintang , Yao Fei , Chen Yiceng
Published: February 2025

Reference precipitation (RP) serves as a benchmark for evaluating the accuracy of precipitation products; thus, the selection of RP considerably affects the evaluation. In order to quantify this impact and provide guidance for RP selection, three interpolation methods, namely inverse distance weighting (IDW), ordinary kriging (OK), and geographical weighted regression (GWR), along with six groups of station densities, were adopted to generate different RPs, based on the super-high-density rainfall observations as true values, and we analyzed the errors of different RPs and the impacts of RP selection on the assessment of GPM precipitation products. Results indicate that the RPs from IDW and GWR both approached the true values as the station density increased (CC > 0.90); while the RP from OK showed some differences (CC < 0.80), it was similar to GWR when the station density was low, but the accuracy improved at first and then worsened as the station density continued to increase; the evaluation results based on different RPs showed remarkable differences even under the same conditions; when the average distance between rainfall gauges that were utilized to generate RPs was below the medium value (i.e., d < 20 km), the evaluation based on RP derived from IDW and GWR was close enough to that based on the true precipitation, which indicates its feasibility in evaluating satellite precipitation products.
Empowering African American Tourism Entrepreneurs with Generative AI: Bridging Innovation and Cultural Heritage
Authors: George Babu , Mattathil Anupama Peter
Published: February 2025

Generative artificial intelligence (AI) present opportunities and challenges for African American tourism entrepreneurs. This paper conceptually explores how tools like language models, image generators, and creative assistants can be used for content creation, personalized marketing, and deeper customer connections. Drawing on relevant innovation- and resource-related theories, this paper examines factors influencing the adoption of generative AI among African American tourism entrepreneurs. The analysis highlights the potential to address tourism-specific needs like virtual tours, multilingual content, and conversational AI assistants. The paper recognizes challenges faced by African American entrepreneurs, including the digital divide, and suggests solutions such as partnerships and training programs aimed at responsible AI adoption. This work aims to provide a foundation for understanding how generative AI can drive innovation and cultural preservation within the African American tourism sector.
A Two-Part Harmony: Changes in Peat Molecular Composition in Two Cores from an Ombrotrophic Peatland (Tremoal do Pedrido, Xistral Mountains, NW Spain)
Authors: Martínez Cortizas Antonio , Francos Golán Ainé , Traoré Mohamed , López-Costas Olalla
Published: February 2025

In peat research, the question often arises as to how similar/different the records of cores collected in the same mire are. This has been addressed for some metals (e.g., Pb and Hg), but the question remains open for the molecular composition of organic matter (pOM). Here, we explore this issue by analysing two cores from a raised bog, combining FTIR-ATR, mid-infrared (MIR) indices, and principal component analysis (PCA), and support the interpretation with multilinear regression (MLR) modelling of peat physical (colour) and elemental (C, N, and C/N) properties. The MIR indices and principal components showed depth patterns mainly related to long- and short-term peat decomposition, as well as other secondary changes involving some compounds (e.g., lignin). The depth records of the two cores are remarkably similar, indicating they were synchronously affected by the same processes and to almost the same degree. Cellulose crystallinity was the only property that showed differences in intensity. The good-to-excellent fitting of the MLR models supports the usefulness of FTIR-ATR in peat research. Further studies in a larger number of cores, from the same peatland and from different types of peatlands, are needed to better understand the spatio-temporal responses of the pOM and the factors involved.
[MxLy]n[MwXz]m Non-Perovskite Hybrid Halides of Coinage Metals Templated by Metal–Organic Cations: Structures and Photocatalytic Properties
Authors: Zabierowski Piotr W.
Published: February 2025

This review provides an analysis of non-perovskite hybrid halides of coinage metals templated by metal–organic cations (CCDC November 2023). These materials display remarkable structural diversity, from zero-dimensional molecular complexes to intricate three-dimensional frameworks, allowing fine-tuning of their properties. A total of 208 crystal structures, comprising haloargentates, mixed-metal haloargentates, and halocuprates, are categorized and examined. Their potential in photocatalysis is discussed. Special attention is given to the structural adaptability of these materials for the generation of functional interfaces. This review highlights key compounds and aims to inspire further research into optimizing hybrid halides for advanced technological applications.
Experimental Evaluation of Temperature and Strain-Rate-Dependent Mechanical Properties of Austenitic Stainless Steel SS316LN and a New Methodology to Evaluate Parameters of Johnson–Cook and Ramberg–Osgood Material Models
Authors: Pandey Sanjay Kumar , Samal Mahendra Kumar
Published: February 2025

Austenitic stainless steel SS316LN is used as the material of construction of the vessel and core components of fast breeder reactors, which operate at an elevated temperature of 550 °C. For design and integrity analysis using the finite element method, material models, such as Johnson–Cook and Ramberg–Osgood, are widely used. However, the temperature- and strain-rate-dependent plasticity and damage parameters of these models for this material are not available in the literature. Moreover, the method of evaluation of temperature and strain-rate-dependent plasticity parameters, in literature, has some major shortcomings, which have been addressed in this work. In addition, a new optimization-based procedure has been developed to evaluate all nine plasticity and damage parameters, which uses results of combined finite element analysis and experimental data. The procedure has been validated extensively by testing tensile specimens at different temperatures, by testing notched tensile specimens of different notch radii, and by carrying out high strain-rate tests using a split Hopkinson pressure bar test setup. The parameters of the Johnson–Cook material model, evaluated in this work, have been used in finite element analysis to simulate load-displacement behavior and fracture strains of various types of specimens, and the results have been compared with experimental data in order to check the accuracy of the parameters. The procedure developed in this work shall help the researchers to adopt such a technique for accurate estimation of both plasticity and damage parameters of different types of material models.
Exploring the Potential of Licuri (Syagrus coronata) Using Sustainable Techniques and Solvents for Extracting Bioactive Compounds
Authors: Inocêncio Emília Silva , Buarque Filipe Smith , Ferreira Luiz F. R. , Soares Cleide M. F. , Lima Álvaro S. , Souza Ranyere Lucena de
Published: February 2025

Bioactive compounds are important for promoting human health, either by developing functional products that offer complementary health benefits or by incorporating them into nutritional supplements, beverages, fortified foods, and pharmaceutical products. In this context, this work focuses on extracting phenolic compounds from the mesocarp of licuri (Syagrus coronata), with the aim of evaluating different emerging solvents and extraction techniques. Solvents with different polarities, such as acetonitrile, ethanol, dimethyl isosorbide (DMI), and CyreneTM, were used in the extraction process (by maceration, ultrasound, and microwaves). A response surface methodology (RSM) with 11 tests was applied, through which it was possible to determine the best extraction condition and method for extracting bioactive compounds, such as total phenolic content (TPC) and total flavonoid content (TFC). The results of licuri mesocarp characterization demonstrated the presence of functional groups associated with the presence of bioactive compounds. RSM analysis showed that the extraction process using acetonitrile at 30 wt%, 60 °C, and in a 1:20 (w/v) ratio had better TPC (35.8 mg GAE·g−1) and TFC (331.1 mg Erutin·g−1) values compared to ethanol. A comparative study between solvents was also conducted, in which CyreneTM (100 wt%) showed the better TPC extraction capacity (75.1 mg GAE·g−1) and acetonitrile as the best TFC extracting solvent (331.1 mg Erutin.g−1). Regarding the extraction method, when analyzing the optimized conditions found by RSM, ultrasound-assisted extraction showed the highest extraction values for TPC (42.8 mg GAE·g−1) and TFC (347.9 mg Erutin·g−1).
Land Consolidation and Its Effects on Afforested Agricultural Land: A Case Study of Ukraine
Authors: Malashevskyi Mykola , Kishchak Olena , Malashevska Olena , Kishchak Yuriy
Published: February 2025

The study is dedicated to the optimization of the naturally afforested land plots. The purpose of this paper was to substantiate land consolidation in the environment of natural afforestation in Ukraine. The look-back analysis of afforestation in the timespan of 20 years was carried out, and the need for the sustainable land use and keeping the tree cover on the afforested land plots was substantiated. Land consolidation, aimed at the optimization of use of agricultural, forest, and naturally afforested land of a territorial community is suggested. The availability of reserve land and the possibility of its involvement in the process of reallotment was substantiated. The development of multifunctional land consolidation was suggested; the reallotment was carried out based on the principles of rural land consolidation and forestry land consolidation. Two land consolidation options were suggested: land plot buying out and swapping the boundaries of the initial land plots as much as possible and land plot reallotment. The algorithms and practical implementation of these approaches in the Kipti territorial community of the Chernihiv Region of Ukraine were presented. As the result of land consolidation, the consolidated land plots, bordering on forest land, were created; the configuration and placement of agricultural land plots were improved. The prospects, limitations, and solutions to the issue of natural afforestation by means of land consolidation by the presented method were singled out.
Effect of High Temperature on CO2 Gasification Kinetics of Sub-Bituminous Coal Fly Ash
Authors: Kang Tae-Jin , Lee Jin-Hee , Lee Da-Hye , Kim Hyo-Sik , Kang Suk-Hwan
Published: February 2025

Gasification is an eco-friendly thermochemical conversion process that can use various raw materials to generate high value-added products. Coal fly ash residue from coal-based thermal power plants must be effectively managed and utilized. Therefore, this study investigates the effects of high temperatures (1100–1300 °C) on the gasification kinetics of two types of coal fly ash (KPU and LG) under isothermal CO2 balance using a thermo-balance reactor. Three models were applied to study the reactivity of the coal fly ashes: the shrinking core model (SCM), the volume reaction model (VRM), and the random pore model (RPM). The results showed that among the three models, the SCM-based simulation was the most similar to the experimental data. We determined that low activation energy and a high pre-exponential factor achieve high gasification reactivity. With the SCM, the activation energy values for the CO2 gasification of the KPU and LG coal fly ashes were 52.7 and 59.6 kJ/mol, respectively, and their pre-exponential factors were 1.90 × 102 and 6.51 × 102, respectively. Moreover, the high reactivity of the two fly ashes was attributed to the high reaction temperature and presence of moisture and volatile matter.
Symmetric Circle Configurations from Regular Skeletal Polyhedra
Authors: Jin Jieying , Schulte Egon
Published: February 2025

The paper studies finite and infinite periodic point-circle configurations in ordinary Euclidean 3-space associated with regular skeletal polyhedra or related structures. The configurations preserve all the symmetries of the underlying polyhedron and, in most cases, are point-circle transitive. Illustrations of many highly symmetric point-circle configurations are provided.
Exploring the Combination of Serious Games, Social Interactions, and Virtual Reality in Adolescents with ASD: A Scoping Review
Authors: Stasolla Fabrizio , Curcio Enza , Passaro Anna , Di Gioia Mariacarla , Zullo Antonio , Martini Elvira
Published: February 2025

Autism spectrum disorder (ASD) often presents significant challenges for adolescents in developing social interaction skills. Emerging technologies such as Serious Games (SGs) and Virtual Reality (VR) offer promising solutions by providing immersive, interactive learning environments. This scoping review evaluates the potential of VR-based SGs to enhance social skills in adolescents with ASD by identifying current applications, benefits, limitations, and research gaps. A systematic search of the literature was conducted on Scopus, focusing on empirical studies published between 2013 and 2024. Studies were included based on their relevance to the use of SGs and VR in promoting social interactions in children and adolescents with ASD. The review highlights that VR-based SGs can effectively support the development of social skills, such as communication and collaboration, by providing structured, safe environments for children and adolescents to practice and refine their abilities. However, challenges remain, including the high cost of VR equipment, the need for greater customization, and the limited scope of long-term efficacy studies. While VR-based SGs show considerable promise, further research is needed to explore their long-term impacts and improve accessibility. Addressing these challenges could solidify VR’s role in ASD interventions, enhancing social skill development and improving the quality of life for children and adolescents with ASD.
An Effective Description of the Instability of Coherent States of Gravitons in String Theory
Authors: Damian Cesar , Loaiza-Brito Oscar
Published: February 2025

We study the dynamics of a coherent state of closed type II string gravitons within the framework of the Steepest Entropy Ascent Quantum Thermodynamics, an effective model where the quantum evolution is driven by a maximal increase of entropy. We find that by perturbing the pure coherent state of gravitons by the presence of other states in the string spectrum, there exist conditions upon which the system undergoes decoherence by reaching thermodynamical equilibrium. This suggests the instability of the coherent state of gravitons. We identify the time scale it takes the system to reach equilibrium consisting of a mixed state of fields in the string spectrum and compare it with the quantum-break time. Also we find that in such final state the quantum-break time seems to be larger than the classical break-time.
Consistency of Histories of Neutrino Oscillation in the Presence of Normal Matter and Continuous Non-Selective Measurement
Authors: Khan Fazeel Ahmed , Dajka Jerzy
Published: February 2025

Two-flavor neutrino oscillation is analyzed using the consistent histories approach. We identify the properties of neutrinos and the oscillation conditions, such as the presence of matter or the impact of measurement, that ensure the consistency of three-time neutrino histories. The connection between the consistency of these histories and the well-known CP violation explored in this study serves as a specific example.
Targeting Herpes Simplex Virus Glycoprotein D with Bispecific Antibodies: Expanding Therapeutic Horizons by Searching for Synergy
Authors: Atanasiu Doina , Saw Wan Ting , Friedman Harvey M. , Cohen Gary H.
Published: February 2025

Herpes simplex viruses (HSV-1 and HSV-2), which can be transmitted both orally and sexually, cause lifelong morbidity and in some cases, meningitis and encephalitis. While both the passive transfer of neutralizing antibodies and placental transfer of anti-HSV monoclonal antibodies (Mabs) have shown therapeutic promise in animal models, clinical trials have yet to identify approved immunotherapeutics for herpes infection. Here, we present strategies for the generation of recombinant bispecific antibodies (BsAbs) that target different domains of glycoprotein D (gD), crucial for HSV entry, that have the potential to outperform the effect of individual Mabs to curb herpes infection. Specifically, we selected three pairs of Mabs from our extensive panel for BsAb design and production based on their binding site and ability to block virus entry. Actual binding of BsAbs to gD and epitope availability on gD after BsAb binding were characterized using surface plasmon resonance (SPR) and inhibition by IgG Fab fragments generated from selected Mabs. While one BsAb exhibited an additive effect similar to that observed using a combination of the Mabs utilized for its generation, two showed antagonistic effects, suggesting that the simultaneous engagement of two epitopes or selective binding to one affected their activity against HSV. One BsAb (DL11/1D3) targeting the binding site for both nectin-1 and HVEM receptors demonstrated synergistic inhibitory activity against HSV, outperforming the effect of the individual antibodies. Recombinant DL11/1D3 antibody variants, in which the size of one or both paratopes was decreased to single chains (scFv-Fc), highlighted differences in potency depending on antibody size and format. We propose that BsAbs to individual glycoproteins offer a potential avenue for herpes therapeutics, but their design, mechanism of action, antibody format, and epitope engagement require careful consideration of structure for optimal efficacy.
Effect of Selection for Litter Size Variability on Growth, Carcass and Meat Quality in Rabbits
Authors: Zawiślak Ireneusz , Argente Maria-Jose , Leicht Katarzyna , Agea Iván , García Maria de la Luz , Belabbas Rafik , Korzeniowska Małgorzata
Published: February 2025

This study aimed to analyze the effect of reducing litter size variability on growth rate, carcass traits, and meat quality in rabbits. Two divergent lines selected by litter size variability were compared: a line selected to reduce litter size variability (HO) and one selected to increase litter size variability (HE). All animals were fed the same commercial diet and kept under identical rearing conditions. The HO line had lower live weight at weaning compared to the HE line (p ≤ 0.05), but the growth rate was higher in the HO line than in the HE line (p ≤ 0.05). Carcass weight and composition were similar between the lines. No differences in meat pH at 45 min and 24 h post-mortem were found between lines. However, the HO line had a higher lightness (L*) value at 45 min post-mortem than the HE line (p ≤ 0.05). The HO line showed higher Ca concentrations than the HE line (p ≤ 0.05). The HO line also had higher protein content and lower saturated fatty acid content than the HE line (p ≤ 0.05). No differences in fat oxidation were observed among the lines. In conclusion, the selection to reduce litter size variability did not negatively impact growth rate and had a favorable effect on protein content, as well as a reduction in saturated fatty acid content in carcass.
A Comparison of Three Methodologies for Determining Soil Infiltration Capacity in Thicketized Oak Woodlands and Adjacent Grasslands
Authors: Atalar Furkan , Leite Pedro A. M. , Wilcox Bradford P.
Published: February 2025

This study had two primary objectives: (1) to determine relative differences in soil infiltration capacity between native grasslands and thicketized oak woodlands and (2) to compare the effectiveness of three infiltration measurement techniques—rainfall simulation, an automated Simplified Steady Beerkan Infiltration (SSBI) method, and the Saturo dual-head infiltrometer. The study was conducted at three sites with clay, loamy sand, and sandy soils. Rainfall simulation captured significant infiltration differences between vegetation covers at all three sites, while SSBI did so at two sites, and Saturo failed to detect significant differences. Consistent with past studies, rainfall simulation results showed significantly higher infiltration capacity in thicketized woodlands compared to adjacent grasslands, with mean infiltration capacity an order of magnitude greater in clay soils (67 mm h−1 vs. 7.5 mm h−1) and more than twice as high in sandy (144.5 mm h−1 vs. 69 mm h−1) and loamy sand (106 mm h−1 vs. 49 mm h−1) soils. Across sites, rainfall simulation and SSBI showed strong positive correlations between infiltration capacity and dead biomass (R2 = 0.74 and 0.46, respectively; p < 0.001 for both), as well as significant negative correlations with live biomass and bulk density. In contrast, the Saturo method exhibited higher variability, overestimating infiltration capacity by an average of 34.3 mm h−1 compared to rainfall simulation, and did not capture significant relationships with biomass or bulk density. Our findings have twofold importance: first, they demonstrate that thicketization of oak savannahs results in higher soil infiltration capacity; and second, they show that for determining soil infiltration capacity, the SSBI methodology is an accurate and practical alternative to the labor-intensive rainfall simulation.
Spatial and Temporal Variations in Rainfall Seasonality and Underlying Climatic Causes in the Eastern China Monsoon Region
Authors: Lu Menglan , Song Xuanhua , Yang Ni , Wu Wenjing , Deng Shulin
Published: February 2025

The regularity of rainfall seasonality is very important for vegetation growth, the livelihood of the population, agricultural production, and ecosystem sustainability. Changes in precipitation and its extremes have been widely reported; however, the spatial and temporal variations in rainfall seasonality and their underlying mechanisms are less understood. Here, we analyzed the changes in rainfall seasonality and possible teleconnection mechanisms in the eastern China monsoon region during 1981–2022, with a special focus on the El Niño-Southern Oscillation (ENSO), El Niño Modoki (ENSO_M), and Indian Ocean Dipole (IOD). Our results show that due to the changes in rainfall concentration, rainfall magnitude, or both, rainfall seasonality has developed in the northern China (NC, 0.15 × 10−3 yr−1) and central China (CC, 0.07 × 10−3 yr−1) monsoon regions, and weakened in the northeastern China (NEC, −0.08 × 10−3 yr−1) and southern China (SC, −0.15 × 10−3 yr−1) monsoon regions during the recent decades. The large-scale circulation and SST anomalies induced by cold or warm phases of the IOD, ENSO_M, and (or) ENSO can explain the enhanced seasonality in the NC and CC monsoon regions and weakened seasonality in the NEC and SC monsoon regions. The wavelet coherence analysis further shows that the dominated climatic factors for rainfall seasonality changes are different in the CC, NC, SC, and NEC monsoon regions, and that rainfall seasonality is also affected by the coupling of the IOD, ENSO_M, and ENSO. Our results highlight that the IOD, ENSO_M, and ENSO are important climatic causes for rainfall seasonality changes in the eastern China monsoon region.