bluuebunny/crossref_metadata_2025 huggingface dataset:
The Antileishmanial, Antioxidant and Cytotoxic Potential of Cecropia concolor Willd (Urticaceae), an Amazonian Species
Authors: Azevedo Sthéfanny Caroline Mendes , Amorim Bruno Sampaio , Zauli Rogéria Cristina , Mendonça Leilane de Souza , Marinho Lethicia do Nascimento , Vieira Marcela Martins , Carvalho Keyla Maciel , Façanha Geverson , Silva Weison Lima da , Falcão Lucas de Souza , de Vasconcellos Marne Carvalho , Xander Patrícia , Nunez Cecilia Veronica , Albuquerque Patrícia Melchionna
Published: October 2024

Cecropia sp. (Urticaceae) are commonly used in traditional medicine in South American countries for the treatment of different diseases. To date, the species Cecropia concolor Willd, of Amazonian occurrence, has not been investigated for its pharmacological potential. In this study, we described the chemical profile and the antileishmanial, antioxidant and cytotoxic activities of extracts of the leaves of C. concolor. The ethanolic extract and its partition phases (hexane, ethyl acetate and hydroethanolic) were analyzed for their chemical classes and phenolic content. Antileishmanial activity was assessed against Leishmania (L.) amazonensis. The antioxidant activity was evaluated using the DPPH method and in MRC-5 human fibroblast cells. Toxicity was tested against Artemia salina and in human cells (fibroblasts and cancer lines). The leaves of C. concolor have phenolic substances, such as flavonoids, as well as terpenes, steroids and alkaloids. Chlorogenic acid, caffeic acid, schaftoside and vicenin 2 were identified. The hydroethanolic phase showed a high concentration of phenolic compounds and pronounced antioxidant activity. The antileishmanial activity was observed in the ethanolic extract, with a promising effect of the hexane phase. The C. concolor ethanolic extract and its phases are non-toxic, which makes this species of interest in pharmaceutical and cosmetics applications.
The Final Pliocene and Early Pleistocene Faunal Dispersals from East to Europe and Correlation of the Villafranchian Biochronology between Eastern and Western Europe
Authors: Spassov Nikolai
Published: October 2024

The Villafranchian stage in the mammal fauna evolution in Eurasia (ca. 3.6/3.4 Ma—ca. 1.2 Ma) is associated with the beginning of the formation of the modern appearance of the mammal megafauna of today’s Palaearctic. The cooling and the aridification starting with the beginning of the Early Pleistocene gradually eliminated the quasi-tropical appearance of the Late Neogene landscapes and fauna of Europe. The time from the Mid-Piacenzian (ca. 3.3–3.0 Ma) to the end of the Early Pleistocene was a time of particularly intense dispersal of species, of faunal exchange between Eurasia and Africa, and of the entry of new mammals into Europe from the East. That is why the correlation of the biochronology of the Villafranchian fauna between Eastern and Western Europe is of particular interest. Accumulated data make possible a more precise correlation of these faunas today. A correlation of selected Eastern European localities with established faunal units and MNQ zones is made in the present work. Usually, the dispersal from Asia or from E. Europe to W. Europe is instantaneous from a geological point of view, but in a number of cases, reaching W. Europe happens later, or some species known to be from Eastern Europe do not reach Western Europe. The main driving forces of the faunal dispersals, which are the key bioevents in the faunal formation, are climate changes, which in turn, affect the environment. We can summarize the following more significant Villafranchian bioevents in Europe: the End Pliocene (Early Villafranchian: MNQ16) turnover related to the first appearance of a number of taxa, for example, felids, canids, proboscideans, and ungulates; the Quaternary beginning turnover. Correlated with this are the beginning of the Middle Villafranchian, which should be placed at about 2.6 Ma; the Coste San Giacomo faunal unit turnover (Senèze and Slivnitsa localities should be included here, and the FU itself, at the very beginning of the late Villafranchian (=MNQ18a)); the Pachycrocuta event at the very beginning of the Olivola FU; and the events related to the Late Villafranchian/Epivillafranchian bounfary.
The Catholic Church and Its Approach towards Refugees and Migrants: An Analysis of the Presence of Migration Issues in the Synod’s Syntheses on Synodality
Authors: Cekiera Rafał , Włosek Mateusz
Published: October 2024

The issues of migration and refugees are currently major global challenges. They are also important aspects of the teachings of the Catholic Church, as evidenced by the many recent Church documents. These issues also came up in discussions at the Synod on Synodality convened by Pope Francis. This article attempts to analyze 24 synodal syntheses, created by European episcopates, in terms of their approach to contemporary migration phenomena and further consequences, which allows for the identification of the main themes and indications of both the religious and social aspects of the encounter with newcomers. A common theme of the syntheses analyzed was the conviction of the need to sensitize societies to the specific plight of newcomers, threatening to marginalize them. Accompanying newcomers and caring for their integration with local communities resounded in the syntheses both as a task and also as opportunities for host communities to actualize solidarity, fraternity, and cultural exchange.
The Dynamics of Islam in Kazakhstan from an Educational Perspective
Authors: Beisenbayev Baktybay , Almukhametov Aliy , Mukhametshin Rafik
Published: October 2024

This article provides a thorough examination of the past evolution and present conditions of Islamic education in Kazakhstan. It commences with an examination of the influence of the Hanafi school within Sunni Islam and traces the evolution of the Islamic educational system throughout various historical periods until the present day. Particular focus is given to blending Islamic teachings with contemporary educational structures. The researchers heuristically analyzed the current state of the field, identified the main problems, and suggested prospects for Islamic education for further development. In this study, the PRISMA methodology is adopted to systematize the literature, enabling a detailed examination of the characteristics and nuances of Islamic education within the historical and cultural traditions of Kazakhstan. The current study utilizes the historical method, which uses primary and secondary data sources. This method prioritizes historical analysis as a means to assess past occurrences. This paper examines the axiological importance of madrasas and Islamic universities, as well as the pedagogical approaches employed in these educational establishments. We have presented infographics that contribute to a detailed understanding of the field. From the heuristic analyses, we formulated practical recommendations for the government designed to enhance the quality and effectiveness of Islamic education. This paper highlights the importance of Islamic education as an important component of the cultural and scientific space of Kazakhstan, offering strategies for its sustainable development in the context of globalization and the transformation of educational systems. The results of this work are of significant interest to academics, madrasas, colleges, and higher education institutions specializing in Islamic education.
Thanks Be to God: Divine Gratitude and Its Relationship to Well-Being
Authors: Watkins Philip , Emmons Robert , Davis Don , Frederick Michael
Published: October 2024

Gratitude is a pivotal concept in the psychology of religion because it is one of the most frequently experienced emotions toward God. The authors developed a trait measure of Gratitude to God (GTG-T) and investigated the association between Gratitude to God and psychological and spiritual well-being in four studies. Study 1 provided evidence for the validity of the GTG-T as Gratitude to God was associated with overall well-being and predicted increases in spiritual well-being over time. Study 2 used a prospective design to show that Gratitude to God predicted increases in general gratitude. In a third study, results showed that Gratitude to God predicted increased grateful emotion and increased confidence in the existence of God over time. In Studies 2 and 3, mediation analyses supported the model that Gratitude to God enhances well-being by promoting generalized gratitude. Study 4 provided further valid evidence for the GTG-T and also showed that gratitude to God is much more strongly related to one’s heartfelt conception of God as loving than to their doctrinal conception of a loving God. Gratitude to God deserves additional scientific scrutiny in the psychology of religion and spirituality than it has received to date.
Application of Barycentric Coordinates and the Jacobian Matrix to the Analysis of a Closed Structure Robot
Authors: Chavdarov Ivan
Published: October 2024

A new approach is presented to study the kinematic properties of stationary robots with a closed structure. It combines the application of conventional methods from kinematics with geometric parameters represented in a barycentric coordinate system. This allows examining the influence of the proportions of the robot’s links on its basic mechanical characteristics. Each point from the newly introduced barycentric space corresponds to a set of robots with the same link proportions. The proposed approach is used to study three aspects: the link proportions for which the robot can exist; the shape of the robot’s workspace; and the possible singular configurations. This is valuable when evaluating the qualities of existing robots and could be applied to the design of new mechanical systems. An example of a 5-link robot with a closed structure is considered. The conditions for the existence of the mechanism and the conditions under which certain types of singular configurations can occur are defined. The example reveals the great potential of combining barycentric coordinates and Jacobian properties. The barycentric coordinates of 10 robots with a 5-link closed structure known from the literature are determined, and their properties are analyzed. The results are presented graphically. An extension of the application area of the approach is discussed.
Fast Hyperspectral Image Classification with Strong Noise Robustness Based on Minimum Noise Fraction
Authors: Wang Hongqiao , Yu Guoqing , Cheng Jinyu , Zhang Zhaoxiang , Wang Xuan , Xu Yuelei
Published: October 2024

A fast hyperspectral image classification algorithm with strong noise robustness is proposed in this paper, aiming at the hyperspectral image classification problems under noise interference. Based on the Fast 3D Convolutional Neural Network (Fast-3DCNN), this algorithm enables the classification model to have good tolerance for various types of noise by using a Minimum Noise Fraction (MNF) as dimensionality reduction module for hyperspectral image input data. In addition, by introducing lightweight hybrid attention modules with the spatial and the channel information, the deep features extracted by the Convolutional Neural Network are further refined, ensuring that the model has high classification accuracy. Public dataset experiments have shown that compared to traditional methods, the MNF in this algorithm reduces the dimensionality of input spectral data, preserves information with higher signal-to-noise ratio(SNR) in the spectral bands, and aggregates spectral features into class feature vectors, greatly improving the noise robustness of the model. At the same time, based on a lightweight spectral–spatial hybrid attention mechanism, combined with fewer spectral dimensions, the model effectively avoids overfitting. With less loss in model training speed, it achieved better classification accuracy in small-scale training sample experiments, fully demonstrating the good generalization ability of this algorithm.
Sky-GVIO: Enhanced GNSS/INS/Vision Navigation with FCN-Based Sky Segmentation in Urban Canyon
Authors: Wang Jingrong , Xu Bo , Liu Jingnan , Gao Kefu , Zhang Shoujian
Published: October 2024

Accurate, continuous, and reliable positioning is critical to achieving autonomous driving. However, in complex urban canyon environments, the vulnerability of stand-alone sensors and non-line-of-sight (NLOS) caused by high buildings, trees, and elevated structures seriously affect positioning results. To address these challenges, a sky-view image segmentation algorithm based on a fully convolutional network (FCN) is proposed for NLOS detection in global navigation satellite systems (GNSSs). Building upon this, a novel NLOS detection and mitigation algorithm (named S−NDM) uses a tightly coupled GNSS, inertial measurement units (IMUs), and a visual feature system called Sky−GVIO with the aim of achieving continuous and accurate positioning in urban canyon environments. Furthermore, the system combines single-point positioning (SPP) with real-time kinematic (RTK) methodologies to bolster its operational versatility and resilience. In urban canyon environments, the positioning performance of the S−NDM algorithm proposed in this paper is evaluated under different tightly coupled SPP−related and RTK−related models. The results exhibit that the Sky−GVIO system achieves meter-level accuracy under the SPP mode and sub-decimeter precision with RTK positioning, surpassing the performance of GNSS/INS/Vision frameworks devoid of S−NDM. Additionally, the sky-view image dataset, inclusive of training and evaluation subsets, has been made publicly accessible for scholarly exploration.
Characteristics of Rock Avalanche Deposit in Wangjiapo, Ludian Based on UAV Aerial Image Recognition
Authors: Han Zhenhua , Zhang Luqing , Zhou Jian , Wang Song , Sun Juanjuan , Li Ruirui , Huang Fuyou
Published: October 2024

Rock avalanche disasters in alpine and gorge regions are frequent and large in scale and cause severe damage. The movement of a rock avalanche is complex and has not been fully studied. The deposits of a rock avalanche can provide valuable insights into its movement process, which is crucial in understanding the rock fragmentation mechanism and predicting disaster-affected areas. Taking the Wangjiapo rock avalanche in Yunnan Province of China as an example, the size, shape and distribution characteristics of the deposit were analyzed based on field surveys, unmanned aerial vehicle (UAV) photography and image recognition technology. Initially, 3062 deposited rock blocks were manually measured in the field. Subsequently, the Particles/Pores and Cracks Analysis System (PCAS) was employed to identify 11,357 rock blocks with an area greater than 0.1 m2 from UAV orthophotos. By comparing the characteristics of the rock blocks obtained through image recognition and manual measurement, the statistical analysis of UAV aerial imagery combined with PACS proved feasible in studying the Wangjiapo rock avalanche. The results showed that the rock block movement was accompanied by fragmentation and sorting processes; furthermore, the roundness increased with the migration distance. Small blocks were more prevalent at the foot of the slope, while irregularly shaped, large blocks dominated in source areas. The movement of huge blocks was characterized by significant potential energy-driven features and inertia advantages, allowing them to travel farther than smaller blocks, and they tended to be concentrated in the central area of the deposit. Additionally, affected by the cementation degree of breccia and the topography, the blocks in the eastern and western deposit areas exhibited different fragmentation and deposition characteristics.
Estimating Grassland Carrying Capacity in the Source Area of Nujiang River and Selinco Lake, Tibetan Plateau (2001–2020) Based on Multisource Remote Sensing
Authors: Ji Fangkun , Xi Guilin , Xie Yaowen , Zhang Xueyuan , Huang Hongxin , Guo Zecheng , Zhang Haoyan , Ma Changhui
Published: October 2024

Estimating the spatiotemporal variations in natural grassland carrying capacity is crucial for maintaining the balance between grasslands and livestock. However, accurately assessing this capacity presents significant challenges due to the high costs of biomass measurement and the impact of human activities. In this study, we propose a novel method to estimate grassland carrying capacity based on potential net primary productivity (NPP), applied to the source area of the Nujiang River and Selinco Lake on the Tibetan Plateau. Initially, we utilize multisource remote sensing data—including soil, topography, and climate information—and employ the random forest regression algorithm to model potential NPP in areas where grazing is banned. The construction of the random forest model involves rigorous feature selection and hyperparameter optimization, enhancing the model’s accuracy. Next, we apply this trained model to areas with grazing, ensuring a more accurate estimation of grassland carrying capacity. Finally, we analyze the spatiotemporal variations in grassland carrying capacity. The main results showed that the model achieved a high level of precision, with a root mean square error (RMSE) of 4.89, indicating reliable predictions of grassland carrying capacity. From 2001 to 2020, the average carrying capacity was estimated at 9.44 SU/km2, demonstrating a spatial distribution that decreases from southeast to northwest. A slight overall increase in carrying capacity was observed, with 65.7% of the area exhibiting an increasing trend, suggesting that climate change has a modest positive effect on the recovery of grassland carrying capacity. Most of the grassland carrying capacity is found in areas below 5000 m in altitude, with alpine meadows and alpine meadow steppes below 4750 m being particularly suitable for grazing. Given that the overall grassland carrying capacity remains low, it is crucial to strictly control local grazing intensity to mitigate the adverse impacts of human activities. This study provides a solid scientific foundation for developing targeted grassland management and protection policies.
Detection of Floating Algae Blooms on Water Bodies Using PlanetScope Images and Shifted Windows Transformer Model
Authors: Ahn Jihye , Kim Kwangjin , Kim Yeji , Kim Hyunok , Lee Yangwon
Published: October 2024

The increasing water temperature due to climate change has led to more frequent algae blooms and deteriorating water quality in coastal areas and rivers worldwide. To address this, we developed a deep learning-based model for identifying floating algae blooms using PlanetScope optical images and the Shifted Windows (Swin) Transformer architecture. We created 1,998 datasets from 105 scenes of PlanetScope imagery collected between 2018 and 2023, covering 14 water bodies known for frequent algae blooms. The methodology included data pre-processing, dataset generation, deep learning modeling, and inference result generation. The input images contained six bands, including vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), enhancing the model’s responsiveness to algae blooms. Evaluations were conducted using both single-period and multi-period datasets. The single-period model achieved a mean Intersection over Union (mIoU) between 72.18% and 76.47%, while the multi-period model significantly improved performance, with an mIoU of 91.72%. This demonstrates the potential of our model and highlights the importance of change detection in multi-temporal images for algae bloom monitoring. Additionally, the padding technique proposed in this study resolved the border issue that arises when mosaicking inference results from individual patches, providing a seamless view of the satellite scene.
A Disparate Disaster: Spatial Patterns of Building Damage Caused by Hurricane Ian and Associated Socio-Economic Factors
Authors: Salim Md Zakaria , Qiang Yi , Dixon Barnali , Collins Jennifer
Published: October 2024

The literature shows that communities under different socio-economic conditions suffer different levels of damage in disasters. In addition to the physical intensity of hazards, such differences are also related to the varying abilities of communities to prepare for and respond to disasters. This study analyzes the spatial patterns of building damage in Hurricane Ian in 2022 and investigates the socio-economic disparities related to the damage. Specifically, this study employs NASA’s Damage Proxy Map (DPM2) to analyze spatial patterns of building damage caused by the hurricane. Then, it uses statistical analysis to assess the relationships between building damage and hurricane intensity, building conditions, and socio-economic variables at the building and census tract levels. Furthermore, the study applies geographically weighted regression (GWR) to examine the spatial variation of the damage factors. The results provide valuable insights into the potential factors related to building damage and the spatial variation in the factors. The results also reveal the uneven distribution of building damage among different population groups, implying socio-economic inequalities in disaster adaptation and resilience. Moreover, the study provides actionable information for policymakers, emergency responders, and community leaders in formulating strategies to mitigate the impact of future hurricanes by identifying vulnerable communities and population groups.
Enhancing the Precision of Forest Growing Stock Volume in the Estonian National Forest Inventory with Different Predictive Techniques and Remote Sensing Data
Authors: Omoniyi Temitope Olaoluwa , Sims Allan
Published: October 2024

Estimating forest growing stock volume (GSV) is crucial for forest growth and resource management, as it reflects forest productivity. National measurements are laborious and costly; however, integrating satellite data such as optical, Synthetic Aperture Radar (SAR), and airborne laser scanning (ALS) with National Forest Inventory (NFI) data and machine learning (ML) methods has transformed forest management. In this study, random forest (RF), support vector regression (SVR), and Extreme Gradient Boosting (XGBoost) were used to predict GSV using Estonian NFI data, Sentinel-2 imagery, and ALS point cloud data. Four variable combinations were tested: CO1 (vegetation indices and LiDAR), CO2 (vegetation indices and individual band reflectance), CO3 (LiDAR and individual band reflectance), and CO4 (a combination of vegetation indices, individual band reflectance, and LiDAR). Across Estonia’s geographical regions, RF consistently delivered the best performance. In the northwest (NW), the RF model achieved the best performance with the CO3 combination, having an R2 of 0.63 and an RMSE of 125.39 m3/plot. In the southwest (SW), the RF model also performed exceptionally well, achieving an R2 of 0.73 and an RMSE of 128.86 m3/plot with the CO4 variable combination. In the northeast (NE), the RF model outperformed other ML models, achieving an R2 of 0.64 and an RMSE of 133.77 m3/plot under the CO4 combination. Finally, in the southeast (SE) region, the best performance was achieved with the CO4 combination, yielding an R2 of 0.70 and an RMSE of 21,120.72 m3/plot. These results underscore RF’s precision in predicting GSV across diverse environments, though refining variable selection and improving tree species data could further enhance accuracy.
Analysis of Lofoten Vortex Merging Based on Altimeter Data
Authors: Meng Jing , Liu Yu , Han Guoqing , Lin Xiayan , Xie Juncheng
Published: October 2024

The Lofoten Vortex (LV), which is identified as a quasi-permanent anticyclonic eddy, strengthens through continuous merging with external anticyclonic eddies. Our investigation used the Lagrangian method to monitor the LV on a daily basis. Utilizing satellite altimeter data, we conducted multi-year tracking and statistical analysis of merging events involving the LV. The results indicate a characteristic radius of approximately 42.72 km and a mean vorticity at the eddy center of approximately −2.23 × 10−5 s−1. The eddy exhibits oscillatory motion within the sea basin depression, centered at 70°N, 3°E, characterized by counterclockwise trajectories between 0.5°E and 6°E and between 69°N and 70.5°N. There are two types of merging events: fusion events (55%), in which eddies of similar strengths interact within a closed flow line and then merge to form a new eddy; and absorption events (45%), in which the stronger LV absorbs the weaker anticyclonic eddies without destroying the structure of the LV itself. The nodes where strong vorticity advection occurs correspond to the nodes where merging occurs, suggesting that their effect on merging can be well characterized by the vorticity advection time series. We also observe occasional fluctuations and substitution events involving the LV and external anticyclonic eddies, suggesting a dynamic succession rather than a single vortex entity.
An Innovative Tool for Monitoring Mangrove Forest Dynamics in Cuba Using Remote Sensing and WebGIS Technologies: SIGMEM
Authors: Valero-Jorge Alexey , González-Lozano Raúl , González-De Zayas Roberto , Matos-Pupo Felipe , Sorí Rogert , Stojanovic Milica
Published: October 2024

The main objective of this work was to develop a viewer with web output, through which the changes experienced by the mangroves of the Gran Humedal del Norte de Ciego de Avila (GHNCA) can be evaluated from remote sensors, contributing to the understanding of the spatiotemporal variability of their vegetative dynamics. The achievement of this objective is supported by the use of open-source technologies such as MapStore, GeoServer and Django, as well as Google Earth Engine, which combine to offer a robust and technologically independent solution to the problem. In this context, it was decided to adopt an action model aimed at automating the workflow steps related to data preprocessing, downloading, and publishing. A visualizer with web output (Geospatial System for Monitoring Mangrove Ecosystems or SIGMEM) is developed for the first time, evaluating changes in an area of central Cuba from different vegetation indices. The evaluation of the machine learning classifiers Random Forest and Naive Bayes for the automated mapping of mangroves highlighted the ability of Random Forest to discriminate between areas occupied by mangroves and other coverages with an Overall Accuracy (OA) of 94.11%, surpassing the 89.85% of Naive Bayes. The estimated net change based on the year 2020 of the areas determined during the classification process showed a decrease of 5138.17 ha in the year 2023 and 2831.76 ha in the year 2022. This tool will be fundamental for researchers, decision makers, and students, contributing to new research proposals and sustainable management of mangroves in Cuba and the Caribbean.
InSAR Analysis of Partially Coherent Targets in a Subsidence Deformation: A Case Study of Maceió
Authors: Teixeira Ana Cláudia , Bakon Matus , Perissin Daniele , Sousa Joaquim J.
Published: October 2024

Since the 1970s, extensive halite extraction in Maceió, Brazil, has resulted in significant geological risks, including ground collapses, sinkholes, and infrastructure damage. These risks became particularly evident in 2018, following an earthquake, which prompted the cessation of mining activities in 2019. This study investigates subsidence deformation resulting from these mining operations, focusing on the collapse of Mine 18 on 10 December 2023. We utilized the Quasi-Persistent Scatterer Interferometric Synthetic Aperture Radar (QPS-InSAR) technique to analyze a dataset of 145 Sentinel-1A images acquired between June 2019 and April 2024. Our approach enabled the analysis of cumulative displacement, the loss of amplitude stability, the evolution of amplitude time series, and the amplitude change matrix of targets near Mine 18. The study introduces an innovative QPS-InSAR approach that integrates phase and amplitude information using amplitude time series to assess the lifecycle of radar scattering targets throughout the monitoring period. This method allows for effective change detection following sudden events, enabling the identification of affected areas. Our findings indicate a maximum cumulative displacement of −1750 mm, with significant amplitude changes detected between late November and early December 2023, coinciding with the mine collapse. This research provides a comprehensive assessment of deformation trends and ground stability in the affected mining areas, providing valuable insights for future monitoring and risk mitigation efforts.
Surface Ages in the Vicinity of the Chang’e-6 Landing Site
Authors: Zhang Li , Liu Jianzhong , Michael Gregory , Ge Ping , Di Kaichang , Wu Congzhe , Zhu Kai , Kang Xiaoxi
Published: October 2024

The samples from lunar farside have great significance for the study of the Moon, and even the solar system. Chang’e-6 landed successfully on the southern mare of the Apollo basin and returned ~2 kg of samples from lunar farside. To provide a better understanding for the background of the returned samples, we conducted detailed crater size-frequency distribution (CSFD) measurements in the Chang’e-6 landing region, the southern mare of the Apollo basin. The southern mare is divided into the western mare (W region) and the eastern mare (E region), and then subdivided into five subunits (W1, W2, W3, W4, W5) and three units (E1, E2, E3), respectively, according to the elevation, TiO2, and FeO abundances. Within the W2 and W5 region, more detailed subunits were separated out. The results show that the southern mare surface was active during two epochs, the Imbrian period and the Eratosthenian period. The basalt eruption lasted for ~1.7 Ga, from 3.28 Ga of the eastern mare to 1.54 Ga of the western mare. The W region is younger than the E region, while the three units of the E region have an age of ~3.2 Ga. The ages of the western mare basalts range from 2.98 Ga to 1.54 Ga, lasting for 1.4 Ga. It is worth noting that the age of the basalt at the Chang’e-6 sampling site is ~1.68 Ga, indicating the samples returned may include components with this very young age.
Quantifying the Contributions of Vegetation Dynamics and Climate Factors to the Enhancement of Vegetation Productivity in Northern China (2001–2020)
Authors: Liu Kaixuan , Wang Xufeng , Wang Haibo
Published: October 2024

Vegetation dynamics are critical to the terrestrial carbon and water cycle, with China recognized as one of the largest contributors to global greening due to significant variations in forest coverage. However, distinguishing the effects of vegetation changes from those of climate factors on vegetation productivity remains challenging. This study conducted a comprehensive analysis of vegetation productivity in Northwest China over the past two decades, focusing on the spatiotemporal patterns and drivers of gross primary production (GPP) within ecological restoration areas. Using trend analysis and ridge regression models, we assessed the relative contributions of climate factors and vegetation coverage changes to GPP dynamics. The results revealed a significant increase in both the GPP and vegetation coverage in Northern China from 2001 to 2020, with GPP rising by 6.7 g C m−2 yr−1 and forest coverage increasing by 0.08% per year. A strong positive correlation (r = 0.9) was observed between vegetation coverage changes and GPP. The increase in GPP was driven by both climate factors and changes in forest coverage, with climate factors contributing 61.0% and vegetation coverage changes contributing 39.0%. Among the climate factors, radiation, temperature, and precipitation contributed 15.4%, 6.4%, and 39.2%, respectively. The study highlights the critical role of ecological restoration efforts, particular in regions like the Less Plateau and Inner Mongolian Plateau, in enhancing vegetation productivity. These findings provide valuable insights for addressing desertification and inform strategies for ecological restoration and sustainable development in Northern China.
Ghost Removal from Forward-Scan Sonar Views near the Sea Surface for Image Enhancement and 3-D Object Modeling
Authors: Liu Yuhan , Negahdaripour Shahriar
Published: October 2024

Underwater sonar is the primary remote sensing and imaging modality within turbid environments with poor visibility. The two-dimensional (2-D) images of a target near the air–sea interface (or resting on a hard seabed), acquired by forward-scan sonar (FSS), are generally corrupted by the ghost and sometimes mirror components, formed by the multipath propagation of transmitted acoustic beams. In the processing of the 2-D FSS views to generate an accurate three-dimensional (3-D) object model, the corrupted regions have to be discarded. The sonar tilt angle and distance from the sea surface are two important parameters for the accurate localization of the ghost and mirror components. We propose a unified optimization technique for improving both the measurements of these two parameters from inexpensive sensors and the accuracy of a 3-D object model using 2-D FSS images at known poses. The solution is obtained by the recursive updating of sonar parameters and 3-D object model. Utilizing the 3-D object model, we can enhance the original images and generate synthetic views for arbitrary sonar poses. We demonstrate the performance of our method in experiments with the synthetic and real images of three targets: two dominantly convex coral rocks and a highly concave toy wood table.
Retrieval of Solar Shortwave Irradiance from All-Sky Camera Images
Authors: González-Fernández Daniel , Román Roberto , Mateos David , Herrero del Barrio Celia , Cachorro Victoria E. , Copes Gustavo , Sánchez Ricardo , García Rosa Delia , Doppler Lionel , Herrero-Anta Sara , Antuña-Sánchez Juan Carlos , Barreto África , González Ramiro , Gatón Javier , Calle Abel , Toledano Carlos , de Frutos Ángel
Published: October 2024

The present work proposes a new model based on a convolutional neural network (CNN) to retrieve solar shortwave (SW) irradiance via the estimation of the cloud modification factor (CMF) from daytime sky images captured by all-sky cameras; this model is named CNN-CMF. To this end, a total of 237,669 sky images paired with SW irradiance measurements obtained by using pyranometers were selected at the following three sites: Valladolid and Izaña, Spain, and Lindenberg, Germany. This dataset was randomly split into training and testing sets, with the latter excluded from the training model in order to validate it using the same locations. Subsequently, the test dataset was compared with the corresponding SW irradiance measurements obtained by the pyranometers in scatter density plots. The linear fit shows a high determination coefficient (R2) of 0.99. Statistical analyses based on the mean bias error (MBE) values and the standard deviation (SD) of the SW irradiance differences yield results close to −2% and 9%, respectively. The MBE indicates a slight underestimation of the CNN-CMF model compared to the measurement values. After its validation, model performance was evaluated at the Antarctic station of Marambio (Argentina), a location not used in the training process. A similar comparison between the model-predicted SW irradiance and pyranometer measurements yielded R2=0.95, with an MBE of around 2% and an SD of approximately 26%. Although the precision provided by the SD at the Marambio station is lower, the MBE shows that the model’s accuracy is similar to previous results but with a slight overestimation of the SW irradiance. Finally, the determination coefficient improved to 0.99, and the MBE and SD are about 3% and 11%, respectively, when the CNN-CMF model is used to estimate daily SW irradiation values.
Standards for Data Space Building Blocks
Authors: Noardo Francesca , Atkinson Rob , Bastin Lucy , Maso Joan , Simonis Ingo , Villar Alejandro , Voidrot Marie-Françoise , Zaborowski Piotr
Published: October 2024

Data spaces are conceptualised as a trusted and secure distributed data ecosystem through which to exchange resources in the Web. Several efforts define guidance toward data space implementation, such as reference architectures and frameworks. As yet, the proposed data space solutions do not provide common and mature implementation options yet, and this gap between concept and implementation risks confusing users and developers. However, well-recognised organisations have been developing solutions and standards that address interoperability and good data exchange practices for decades, especially in the domain of geospatial information and remote sensing. Therefore, this paper compares the available solutions, providing the mapping and integration of the proposed blueprints to available interoperable standards. This concrete mapping, followed by a discussion with experts, results in a proposal of integrated reference data space building blocks, and an overview of the related standards and solutions. It is designed to support the effective practical implementation of data spaces and to guide future solution developments. This work can form the base for effective collaboration among different organisations, clearly identifying their scopes. A key role is apparent for standards and use cases from the remote sensing and geospatial domains, which have achieved wide adoption and maturity over the past years.
Development, Validation, and Greenness Assessment of Eco-Friendly Analytical Methods for the Determination of Abiraterone Acetate in Pure Form and Pharmaceutical Formulations
Authors: Akbel Erten
Published: October 2024

This study presents the development and validation of environmentally friendly analytical methods for quantifying Abiraterone Acetate (AA) in both its pure form and commercial pharmaceutical formulations. An optimized High-Performance Liquid Chromatography (HPLC) method was developed using an Agilent Extend C18 column (250 mm × 4.6 mm, 5 μm) at 25 °C. The mobile phase consisted of formic acid and ethanol in isocratic mode, with a flow rate of 1.0 mL min−1, and detection was performed at 253 nm. The spectrophotometric method involved a comprehensive evaluation of AA’s spectral properties in various solvents, with ultrapure water providing the most suitable spectra for analysis at 253 nm. Both methods were validated according to ICH guidelines, demonstrating selectivity, linearity, accuracy, precision, detection and quantification limits, and robustness, with correlation coefficients exceeding 0.999 across the 5–30 μg mL−1 concentration range. Comparative statistical analysis using Student’s t-test and Fisher’s F-test showed no significant differences between the two methods. The environmental impact of both methods was assessed using AGREE and GAPI software, confirming their sustainability. These validated methods offer reliable and eco-friendly approaches for the quantitative analysis of AA in tablet formulations, promoting safer and greener laboratory practices in pharmaceutical analysis.
Comparison and Optimization of Three Extraction Methods for Epimedium polysaccharides
Authors: Liu Cheng , Gong Fangyuan , Chen Yijia , Xiong Zhengwei , Wang Cun , Li Jiepei , Guo Jin
Published: October 2024

Epimedium is used in traditional Chinese medicine. Epimedium polysaccharides have a variety of physiological properties. This study compared three different processes for the extraction of polysaccharides from Epimedium spp., including ultrasonic, aqueous enzymatic, and microwave extraction, to optimize the extraction conditions and determine the optimal extraction method. The optimal parameters for each method were analyzed. The results showed that the optimal process for ultrasonic extraction was an ultrasonic power of 250 W, an extraction time of 60 min, a temperature of 50 °C, and a solid–liquid ratio of 1:35. The optimal conditions for the aqueous enzymatic method were a papain concentration of 70 U/mL, extraction time of 70 min, a temperature of 50 °C, and a material-to-liquid ratio of 1:30, while those for microwave extraction were a microwave power of 650 W, an extraction time of 50 min, a temperature of 40 °C, and a material-to-liquid ratio of 1:25. The polysaccharide yields were 4.85%, 4.72%, and 3.98% for the three methods, respectively, indicating that ultrasonic extraction resulted in the highest yield of polysaccharides from Epimedium brevicornum. After purification with DEAE-cellulose, the polysaccharide yields were 4.13%, 3.67%, and 3.12%, respectively. A comprehensive comparison demonstrated the superiority of the ultrasonic extraction method in terms of both extraction yield and purification efficiency. Characterization of the extracted Epimedium polysaccharides showed the presence of five monosaccharides, i.e., glucose, galactose, mannose, galacturonic acid, and rhamnose, and a number average molecular weight Mn of 1.65 × 105 Da and weight average molecular weight Mw of 6.61 × 105 Da. These results provide a scientific basis for the in-depth study and application of Epimedium polysaccharides.
Perspectives on Necessity-Driven Immigrant Entrepreneurship: Interactions with Entrepreneurial Ecosystems through the Lens of Dynamic Capabilities
Authors: Chen Yu-Heng , Chen Han-Shen
Published: October 2024

This paper explores the interaction between immigrant small and medium-sized enterprises (SMEs) and the entrepreneurial ecosystems of their home and host countries. These SMEs, often established out of necessity due to economic hardship or unemployment, contrast with opportunity-driven ventures that seek to exploit new market prospects. Employing a dynamic capabilities framework, the study investigates how immigrant SMEs identify and mobilize critical resources in unstable environments, and how these resources are dynamically adapted and transformed to meet organizational objectives while responding to ecosystem changes, ultimately cultivating competitive advantages. Interviews were conducted with 25 immigrant entrepreneurs from eight countries, and the interviews took place within their business environments, with native speakers of the interviewees′ home countries present to ensure accuracy and authenticity. The findings highlight that immigrant entrepreneurs effectively leverage resources from both home and host country ecosystems, with human capital being the most essential asset. Additionally, the role of immigrants′ social networks is emphasized as a crucial mechanism for resource acquisition. This study further illustrates the positive contributions of immigrant enterprises to entrepreneurial ecosystems, revealing a co-evolutionary relationship whereby the businesses and ecosystems both mutually evolve. This co-evolution strengthens the resilience and sustainability of immigrant ventures, significantly enhancing their long-term success.
“Someone Who Is Going to Preserve Your Surname and Clan Name”: A Sesotho Cultural Perspective on Male Partner Involvement in Maternal and Newborn Care in the Free State, South Africa
Authors: Mulu Ngwi N. T. , Engelbrecht Michelle
Published: October 2024

In the global public health discourse, involving men in maternal and neonatal health is regarded as crucial for positive outcomes in both health and development. In South Africa, health interventions designed to promote male partner involvement among low-income indigenous populations have been framed within social constructivist notions of masculinities and have produced mixed outcomes. This has necessitated calls to explore alternative approaches, including the need to decolonise men and masculinities studies in Africa. As part of one phase of formative research for a mixed-method project aimed at adapting a male involvement intervention for the context of Sesotho-speaking men and women in the Free State, we applied a multi-site case study research design and collected qualitative data using focus group discussions and key informant interviews. Verbatim-recorded transcripts were translated, transcribed, and thematically analysed with NVIVO 14. The results indicate that customary practices in pregnancy, delivery, and newborn care are not static and vary between families based on belief systems, socioeconomic status, geographical setting (peri-urban/rural), and kinship networks of care. Therefore, these practices and beliefs should be understood, affirmed, and contested within the complex African-centred material and immaterial worldviews on personhood in which they were generated, transmitted, rejected, or adopted. It is recommended that a decolonised approach to male partner involvement in this context must be cognisant of the intersections of racial and gendered power relations, contestations in beliefs and practices, the resilient effect of colonialism on indigenous gender systems, as well as contemporary global entanglements that inform North–South power relations on the best practices in maternal and newborn health in the public health sector in South Africa.
Validity and Reliability of a New Wearable Chest Strap to Estimate Respiratory Frequency in Elite Soccer Athletes
Authors: Di Paco Adriano , Bonilla Diego A. , Perrotta Rocco , Canonico Raffaele , Cione Erika , Cannataro Roberto
Published: October 2024

Assessing respiratory frequency (fR) is practical in monitoring training progress in competitive athletes, especially during exercise. This study aimed to validate a new wearable chest strap (wCS) to estimate fR against ergospirometry as a criterion device in soccer players. A total of 26 elite professional soccer players (mean [standard deviation]: 23.6 [4.8] years; 180.6 [5.7] cm; 77.2 [5.4] kg) from three Italian Serie A League teams participated in this cross-sectional study. The sample included attackers, midfielders, and defenders. fR was assessed during a maximal cardiopulmonary exercise test (CPET) on a treadmill using (i) a breath-by-breath gas exchange analyzer (Vyntus® CPX, Vyaire Medical) and (ii) a novel wCS with sensors designed to assess breath frequency following chest expansions. Pearson’s correlation coefficient (r), adjusted coefficient of determination (aR2), Bland–Altman plot analysis, and Lin’s concordance correlation coefficient (ρc) were used for comparative analysis (correlation and concordance) among the methods. The repeated measures correlation coefficient (rrm) was used to assess the strength of the linear association between the methods. The intraclass correlation coefficient (ICC) and the Finn coefficient (rF) were used for inter-rater reliability. All statistical analyses were performed within the R statistical computing environment, with 95% confidence intervals (95% CIs) reported and statistical significance set at p < 0.05. A total of 16529 comparisons were performed after collecting the CPET data. The robust time series analysis with Hodges–Lehmann estimation showed no significant differences between both methods (p > 0.05). Correlation among devices was statistically significant and very large (r [95% CI]: 0.970 [0.970, 0.971], p < 0.01; aR2 [95% CI]: 0.942 [0.942, 0.943], p < 0.01) with strong evidence supporting consistency of the new wCS (BF10 > 100). In addition, a high concordance was found (ρc [95% CI]: 0.970 [0.969, 0.971], bias correction factor: 0.999). VyntusTM CPX, as a standard criterion, showed moderate agreement with wCS after Bland–Altman analysis (bias [95% lower to the upper limit of agreement]; % agree: 0.170 [−4.582 to 4.923] breaths·min−1; 69.9%). A strong association between measurements (rrm [95% CI]: 0.960 [0.959, 0.961]), a high absolute agreement between methods (ICC [95% CI]: 0.970 [0.970, 0.971]), and high inter-rater reliability (rF: 0.947) were found. With an RMSE = 2.42 breaths·min−1, the new wCS seems to be an valid and reliable in-field method to evaluate fR compared to a breath-by-breath gas exchange analyzer. Notwithstanding, caution is advised if methods are used interchangeably while further external validation occurs.