bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Authors: McMichael Lucas A. , Schmidt Michael J. , Wood Robert , Blossey Peter N. , Patel Lekha
Published: November 2024

Abstract. The rate at which aerosols spread from a point source injection, such as from a ship or other stationary pollution source, is critical for accurately representing subgrid plume spreading in a climate model. Such climate model results will guide future decisions regarding the feasibility and application of large-scale intentional marine cloud brightening (MCB). Prior modeling studies have shown that the rate at which ship plumes spread may be strongly dependent on meteorological conditions, such as precipitating versus non-precipitating boundary layers and shear. In this study, we apply a Lagrangian particle model (PM-ABL v1.0), governed by a Langevin stochastic differential equation, to create a simplified framework for predicting the rate of spreading from a ship-injected aerosol plume in sheared, precipitating, and non-precipitating boundary layers. The velocity and position of each stochastic particle is predicted with the acceleration of each particle being driven by the turbulent kinetic energy, dissipation rate, momentum variance, and mean wind. These inputs to the stochastic particle velocity equation are derived from high-fidelity large-eddy simulations (LES) equipped with a prognostic aerosol–cloud microphysics scheme (UW-SAM) to simulate an aerosol injection from a ship into a cloud-topped marine boundary layer. The resulting spreading rate from the reduced-order stochastic model is then compared to the spreading rate in the LES. The stochastic particle velocity representation is shown to reasonably reproduce spreading rates in sheared, precipitating, and non-precipitating cases using domain-averaged turbulent statistics from the LES.
Biological nitrogen fixation of natural and agricultural vegetation simulated with LPJmL 5.7.9
Authors: Wirth Stephen Björn , Braun Johanna , Heinke Jens , Ostberg Sebastian , Rolinski Susanne , Schaphoff Sibyll , Stenzel Fabian , von Bloh Werner , Taube Friedhelm , Müller Christoph
Published: November 2024

Abstract. Biological nitrogen fixation (BNF) by symbiotic and free-living bacteria is an important source of plant-available nitrogen (N) in terrestrial ecosystems supporting carbon (C) sequestration and food production worldwide. Dynamic global vegetation models (DGVMs) are frequently used to assess the N and C cycles under dynamic land use and climate. BNF plays an important role in the components of both these cycles, making a robust representation of the processes and variables that BNF depends on important to reduce uncertainty within the C and N cycles and improve the ability of DGVMs to project future ecosystem productivity, vegetation patterns or the land C sink. Still, BNF is often modelled as a function of net primary productivity or evapotranspiration, and the actual drivers are neglected. We implemented plant-functional-type-specific limitations for BNF dependent on soil temperature and soil water content, as well as a cost of BNF, in the Lund–Potsdam–Jena managed Land (LPJmL) DGVM and compared the new (“C-costly”) against the previous (“Original”) approach and data from the scientific literature. For our comparison, we simulated a potential natural vegetation scenario and one including anthropogenic land use for the period from 1901 to 2016 for which we evaluate BNF and legume crop yields. Our results show stronger agreement with BNF observations for the C-costly than the Original approach for natural vegetation and agricultural areas. The C-costly approach reduced the overestimation of BNF, especially in hot spots of legume crop production. Despite the reduced BNF in the C-costly approach, yields of legume crops were similar to the Original approach. While the net C and N balances were similar between the two approaches, the reduced BNF in the C-costly approach results in a slight underestimation of N losses from leaching, emissions and harvest compared to the values in the literature, supporting further investigation of the underlying reasons, such as processes represented in DGVMs and scenario assumptions. While we see the potential for further model development, for example, to separate symbiotic and free-living BNF, the C-costly approach is a major improvement over the simple Original approach because of the separate representation of important drivers and limiting factors of BNF, and the C-costly approach also improves the ability of LPJmL to project future C and N cycle dynamics.
High definition 3D models of small legume seed: a close up application to support ancient plant genomics
Authors: Balestra Mattia , Fattorini Federico , Angeloni Renato , Nanni Laura , Mancini Adriano , Papa Roberto , Pierdicca Roberto
Published: November 2024

Abstract. Legume seeds are essential for nutrition and play crucial roles in food security, climate change mitigation, biodiversity conservation, and sustainability. Among them, the common bean (Phaseolus vulgaris L.) is the most widely cultivated and vital to the food value chain. Originating in Mesoamerica and independently domesticated there and in the Andes about 8,000 years ago, common beans have adapted to diverse environments globally following the Columbian exchange. Ancient DNA (aDNA) sequencing offers insights into the bean’s adaptation and evolution, but traditional methods struggle with detailed 3D phenotypic analysis due to the beans’ small size and the destructive nature of aDNA extraction. Expensive high-detail optical instruments are not commonly available in genetic labs. This research proposes macro-photogrammetry as a low-cost technique for creating detailed 3D digital replicas of beans. By using samples from archaeological sites in northern Peru, this method preserves phenotypic information despite the destruction of physical samples during DNA extraction. The study details the process of capturing high-detail images with specialized equipment to build a digital phenotype library, preserving the morphological features of ancient beans for further study and future comparison with modern varieties.
Assessing the potential of polarimetric decomposition of Sentinel-1 SAR for the estimation of mangrove forest biomass
Authors: Ghivarry Giusti , Kutchartt Erico , Pirotti Francesco
Published: November 2024

Abstract. Mangrove forests provide ecosystem services that can support the welfare of local communities. Therefore, promoting their conservation not only protects their environmental functions but also optimizes their economic potential. Remote sensing approaches, particularly active systems such as synthetic aperture radar (SAR), have emerged as a valuable tool for monitoring forest ecosystems. These systems can capture Earth's surface features regardless of atmospheric conditions. However, the backscatter approach becomes unreliable when the AGBD reaches a certain point. This leads to incomplete information being obtained as the reflected signal becomes too strong and overloads the receiver. Therefore, this study explores the potential of polarimetric decomposition as an option to traditional backscatter approaches. Decomposed polarimetric parameters from Sentinel-1 were used for biomass estimation in mangrove forests in West Kalimantan Province. Specifically, in Kubu Raya and North Kaong districts (Indonesia) for the year 2020. The decomposed polarimetric parameters of Entropy, Anisotropy, and Alpha Angle obtained from the H/A/α decomposition integrated with backscattering parameters were used as dependent variables, which were varied following the parameter usage scenarios (both individual and grouped). Meanwhile, GEDI data were used to train the prediction model instead of observational data. The predictive ability of the model using only SAR-derived explanatory variables resulted in an RMSE of about 45 Mg/ha and an R-squared of about 0.2.
Enhanced Forest Inventories: A QGIS Plugin to incorporate R processing tools in forest management
Authors: Granja Larissa Maria , Pirotti Francesco
Published: November 2024

Abstract. The complexity of remote sensing systems makes it possible to collect huge amounts of data that public administrations often do not use at their full potential. The traditional forest inventories (samples and field campaigns) used to identify tree species and measure morphological and physiological parameters are financially burdensome and time-demanding. Thus, remote sensing can be an alternative used by public administration to reduce the efforts in the field and improve the quality of forest inventories and land cover mapping at a sustainable price. In this scenario, this work aims to bridge the gap between common inventory practices and enhanced forest inventories (EFI), that used lidar point clouds and GIS environments together. To support EFIs we developed and present here a QGIS plugin for accessing and processing 3D point clouds to enable decision-makers in the forestry sector to have easier and more intuitive data processing pipelines. Lidar data provides accurate and detailed information on the vertical structure of canopies and can provide estimated volume and biomass, as well as other parameters that are key in forest management. This plugin differs from other approaches in that it initiates a stream with an active R session and sends commands from QGIS with several solutions that re-use all intermediate steps avoiding recalculating them. This saves time and allows multiple processing threads to run in parallel, and thus test different combinations of input parameters to the workflow. Examples and results of the processing are given over a specific study area.
Dam Breach Analysis and Damage Assessment of Nova Kakhovka Dam using Satellite data and 1D and 2D Hydrodynamic Modeling
Authors: Kadam Piyusha B. , Thakur Praveen K. , Dwivedi Sanjay K. , Garg Vaibhav , Dhote Pankja R.
Published: November 2024

Abstract. A dam is a man-made structure that crosses a river or other body of water intending to hold water and create a reservoir. When a dam fails, it results in the loss of lives and economic devastation, which directly depends on factors like water depth, velocity, warning time, and the presence of people in the affected area. Dam failure necessitates the use of dam-break modeling, which evaluates the flood characteristics such as the discharge and timing of flood waves resulting from the dam's breach. This study focuses on examining the two breach scenarios of the Kakhovka dam located in Ukraine. The analysis utilized the HEC-RAS software, a widely recognized tool for hydraulic modeling. Multiple breach parameters, including breach width, breach depth, and breach time, were considered to evaluate their impact on downstream flooding. The model is utilized to assess the potential outcomes of a dam break in downstream areas, including factors such as water level rise, travel time of flood waves, flow velocity, and other parameters. The resulting flood plain was also mapped using GIS tools to show the extent of flooding. Damage assessment for the downstream area was also done by using remote sensing based LULC. The study estimated 35962 m3/sec of peak discharge from the 300-meter dam breach scenario and the flood extent (823 km2) from this scenario also matched with the actual situation as observed by remote sensing data. These estimations help in understanding and managing the risks associated with structural failures.
Identification of asbestos-cement roofing with the use of remote sensing data in the capital city of Poland
Authors: Krówczyńska Małgorzata , Wilk Ewa
Published: November 2024

Abstract. Asbestos, a group of fibrous minerals prized for its strength, flexibility, and resistance to chemicals, heat, and electricity, was widely used in industrial applications, reaching its peak in the 1960s and 1970s with over 3,000 uses. Today, asbestos-cement roofs account for more than 80% of current asbestos-containing products. The International Agency for Research on Cancer has classified asbestos as a carcinogen, and the World Health Organization has called for global efforts to regulate and eliminate carcinogens, including asbestos, in both occupational and environmental exposure. Convolutional Neural Networks and high-resolution orthophotomaps were examined for the dense urban areas, i.e. the capital city of Poland, Warsaw. The area of Warsaw is divided into 18 districts. Two classes were distinguished: buildings with asbestos-cement roofs (“asbestos”) and buildings with other roof coverings (“non-asbestos”). Orthophotomaps, developed in 2021 based on aerial imagery with a spatial resolution of 5 cm and three spectral channels (RGB) were used. The overall accuracies (OA) over 90% were obtained. Differences in overall accuracy resulting from the size of the image signature were insignificant and amounted to up to 2 percentage points. The highest producer’s accuracies for the asbestos roofing class were obtained for a window of 128 by 128 pixels, while for the other roofing similar results were obtained for patterns with window sizes of 128 by 128 and 96 by 96 pixels. As a result of the research, the amount of asbestos-cement roofs was estimated, and their spatial location was determined in surveyed districts of the capital city of Warsaw. These results indicate that it is possible to train a neural network and, using available remote sensing data, estimate the scale of the phenomenon even in dense urban areas. Establishing a universally applicable technique would facilitate large-scale asbestos monitoring and management, thereby contributing to improved public health and safety across the EU.
Estimating canopy fuels across Europe with satellite data and allometric equations
Authors: Kutchartt Erico , González-Olabarria José Ramón , Aquilué Núria , Trasobares Antoni , Pirotti Francesco
Published: November 2024

Abstract. This study presents results regarding the estimation of two critical variables for modelling fire behaviour and fire danger: the canopy base height (CBH) and the canopy bulk density (CBD). Both variables have been mapped as raster datasets at a 100-meter spatial resolution across Europe, harmonizing data for all EU countries. Therefore, these canopy fuels are subsequently used for further processing regarding the identification of fire danger assessment, being a key input for forest fire prevention actions. A more in-depth analysis of these findings has been submitted to a journal and is currently in a revision phase. We present here a summary of the results and ideas for future developments. The overall study consists of estimating CBH and CBD using Earth observation products combined with artificial intelligence and species-specific allometric equations, applied geo-spatially using a tree species map of Europe encompassing the 16 most important tree species. Validation was carried out by comparing the results with higher-accuracy sampling methods, combining LiDAR data and field measurements in different European latitudes, typically applied on a smaller scale and with greater detail. Results show, as expected, a higher level of uncertainty than local methods, but they are still applicable to the European scale for which they were implemented. The accuracies reported in our study, when considering aggregated data on the 7 areas in Portugal were the following: R = 0.75, RMSE = 0.890 m, and MAPE = 54% for the mean CBH, and R = 0.93, RMSE = 0.020 kg m−3, and MAPE = 57% for the mean CBD.
Automatic Boundary Extraction from RADAR Images Using Artificial Intelligence Techniques
Authors: Leon Javier , Bedoya Diego , Valbuena Martha
Published: November 2024

Abstract. The extraction of land boundaries from SAR images plays a pivotal role in advancing peace processes and comprehensive rural reform in Colombia, this article explores the application of artificial intelligence (AI) techniques to automate boundary extraction, emphasising its significance in the context of Colombia’s ongoing efforts to resolve land disputes and promote rural development, Traditional methods of delimitation are often time – consuming and prone to human error, by leveraging AI, specifically machine learning algorithms, we can achieve precise and efficient boundary extraction, reducing the need for extensive manual intervention, this automatization facilities accurate land registry updates, which are essential for fair land distribution and the resolution of territorial conflicts.
Monitoring Activity of the Subglacial Lake Mercer Based on CryoSat-2 and ICESat-2 Altimetry Data from 2011 to 2023
Authors: Luo Penglan , Qiao Gang , Qu Zhi , Popov Sergey
Published: November 2024

Abstract. Active subglacial lakes are capable of exchanging and transporting water through water flow paths, thus having an important impact on ice sheet movement and even on the regional mass balance. The use of satellite altimetry can indirectly reveal internal subglacial hydrological activity through direct surface elevation observation, which plays an important role in the study of the evolution of active subglacial lakes. This paper monitors and analyzes the activity of the subglacial lake Mercer (SLM) in the Whillans and Mercer Ice Stream (WIS/MIS), using data from the CryoSat-2 satellite radar altimetry and ICESat-2 satellite laser altimetry. We adopt the differential DEM model and the repeat orbit model based on their respective data characteristics. Finally, we reveal the temporal and spatial evolution patterns of SLM during 2011-2023, and construct the elevation anomaly time series. The results show that the central and western parts of SLM were the areas with more significant elevation anomalies, and there were three significant fill-drain cycles during the time periods studied in this research, with the elevation anomaly range reaching about 8 m and 4 m for the first and second cycles, respectively, and the lake is currently in the third significant draining phase. Furthermore, the elevation anomalies obtained during the mission overlap time of CryoSat-2 and ICESat-2 data are in good agreement, which confirms the accuracy of our method.
Secondary growth deforestation leakage in the Pará beef cattle purchasing zone
Authors: Oliveira Junior Luis , de Souza Filho Jailson S. , Ferreira Bruno Gama , Souza Junior Carlos
Published: November 2024

Abstract. Deforestation is a major threat to forest conservation in the Amazon, affecting biodiversity, climate balance, and natural resources. The beef cattle market targets deforestation-free products. This study aims to assess the extension of Secondary Vegetation (SV) in the Pará State, quantify SV deforestation in rural properties, and measure potential deforestation leakage in SV. The study analyzed the SV dynamics at the property level by accessing the CAR database, selecting properties within the Pará State and filtering the database according to criteria. The dissolved CAR layer was used to remove overlapping properties and classify properties by class size. Properties with no deforestation from 2009 to 2022 were selected as potential purchasing zone. SV areas with regeneration ages greater than five years were considered. In 2022, the Pará State had 2.55 million hectares of SV areas over five years of age, with 136,831 properties in the potential purchasing zone of cattle beef. From 2009 to 2022, 45% of selected properties did not have PRODES alerts, however 82% had SV deforestation events between 2009 and 2022. If SV deforestation was a criterion, 51,065 properties would be out of business, and only 10,887 properties were free from SV deforestation. Deforestation analysis showed that not all forest resources are protected. To achieve a deforestation-free beef cattle market, the TAC must include an SV conservation strategy, to protect all forest resources.
Enhancing Disaster Response and Resilience Through Near-Time GIS for Flood Monitoring and Analysis in Niger River Basin, Nigeria
Authors: Onaopemipo Akintola Mercy
Published: November 2024

Abstract. This study develops an integrated framework leveraging Google Earth Engine for near real-time flood mapping and impact analysis in the flood-prone Niger River Basin of Nigeria. Multi-temporal optical, radar and terrain data quantified changing flood hazards and exposure across 150,000 km2 between peak floods in 2022. Results indicate over 50% rise in inundation, with 15,000 hectares of vegetation and 143,000 residents enduring impacts. Attributing factors include elevated antecedent rainfall versus historical medians coupled with accelerating catchment modifications expanding runoff. Floodplain zones face recurrent impacts, necessitating adaptation. Accurate flood delineation was achieved by applying water indices like NDWI on Landsat and Sentinel-2 data using land cover and land use. Exposure analytics overlay flood extents on land use, infrastructure and demographic layers to estimate affected populations and livelihoods. Google Earth Engine enabled rapid data processing using cloud parallelization, while random forest integration powered machine learning semantic segmentation for robust feature extraction. Going forward, assimilating real-time data from radar and hydrological sensors would enable predictive flood risk models using machine learning algorithms on this cloud GIS platform tailored for resilience applications globally. In a changing climate, such scalable geospatial technologies provide evidence-based decision support capabilities to emergency planners targeting proactive adaptation investments for vulnerable communities based on quantified flood risk analytics.
De Olho na Mata: monitoring Atlantic Forests with drones and few-shot learning
Authors: Pedro Alexandra Aguiar , Dadrass Javan Farzaneh , Georgievska Sonja , Barreto Eduardo Hortal Pereira , Ku Ou , de Oliveira Felipe , Oliveira Patricia do Prado , Gevaert Caroline
Published: November 2024

Abstract. The expansion of invasive species is a global challenge that leads to the loss of biodiversity habitat, and there are few tools to control it. In São Paulo, identification of invasive species is done through field inspections, in parts of Conservation Units and parks, making it difficult to map all tree individuals for adequate management and coping strategies. This manuscript presents a workflow that combines Unmanned Aerial Vehicles (UAVs), or drones, with Artificial Intelligence (AI) to accurately map invasive species in the Atlantic Forest. It describes best practices on how to conduct drone flights to map the forests, exponentially expanding the range of identification and efficiency in invasive tree species management. It also presents an AI workflow that uses few-shot learning and Explainable AI techniques (to guarantee transparency and understanding of the decisions made by the algorithms). Preliminary results indicate that the method obtains acceptable results in the range of 70 percent accuracy for Archontophoenix cunninghamiana (popular name: Seafórtia), an invasive Australian palm.
Trends of Remote Sensing applications for Amazon monitoring
Authors: Peña-Villacreses Gina , Ayala-Hidalgo Shantall , Braga Daniel , Guimarães Yasmim , Santos Marcos Ronielly da Silva , Pereira Marconi de Arruda , Velastegui-Montoya Andrés
Published: November 2024

Abstract. The Amazon is home to a vast biodiversity and plays a crucial role in the maintenance and conservation of the planet. The progress of anthropogenic activities in the region is one of the drivers of land cover change. Studying these changes through remote sensing enables the monitoring of degradation and deforestation in the Amazon rainforest. Using bibliometric tools this study analyses the different remote sensing approaches for land use and land cover monitoring in the Amazon. The methodology includes 1) data search and collection, 2) tool selection and data processing, and 3) data and trend analysis. The results indicate that studies on forest loss and biodiversity are trending in the field. Emerging topics focus on new tools for environmental impact assessment and evaluating new computational technologies for satellite data management.
Detection and correlation analysis of seasonal vertical ground movement measured from SAR and drought conditions
Authors: Pirotti Francesco , Toffah Felix Enyimah
Published: November 2024

Abstract. In this work the relationship between climatic indices and seasonal vertical ground motion (SVGM) from earth observation data is investigated. The European Ground Motion Service (EGMS) vertical ground movement measurements provided from 2018 to 2022 are used together with temperature and precipitation data from MODIS and CHIRP datasets respectively. Precipitation and temperature are further processed to provide Drought Code (DC) maps calculated ad hoc for this study at 1 km spatial resolution and daily temporal resolution. Measurement Points (MP) from EGMS over Italy provide a value of ground vertical movement approximately every 6 days. Seasonality is analysed to assess correlation between SVGM and DC from Copernicus CEMS (DC1) and from MODIS+CHIRP (DC2) and from temperature using Spearman's rank correlation coefficient (ρ). Initial results over Italy show that DC2 is significantly better correlated to SVGM than DC1 and temperature, with a stronger median absolute value of ρ of 0.025 and 0.042 respectively for negative and positive correlation scenarios. A total of 1275 MPs have correlation coefficients between DC2 map and EGMS measurements above 0.8 (positive correlation) and 2594 ρ < −0.8 (negative correlation). Correlations lagged in time are also analysed, resulting in most being inside a window of ± 6 days. Because DC and temperature are strongly collinear, further analysis to assess which is better at explaining the seasonality of GM was carried out, resulting in DC2 significantly explaining more variance of the SVGM than temperature for the inversely correlated points more than the directly correlated points. These points are unevenly distributed in the Italian territory, with clusters in some areas that appear to show reliable SVGM-DC correlations. We conclude that further investigation is necessary at a local scale. An interactive web-gis open to the public is available for data consultation and all data are shared in a public repository for full replicability of the method.
Variability of Hydro-Meteorological Fluxes in North West Himalayan Basins for Hydrological and Sustainability Studies
Authors:   Rachit, Masiwal Abhay , Singla Sanyam , Singhal Gaurish , Thakur Praveen K. , Garg Vaibhav , Romshoo Shakil
Published: November 2024

Abstract. The Himalayas are a crucial source of food, water, and habitat for a wide range of ecosystems in the northern Indian subcontinent. This research focuses on utilizing remote sensing data to analyze hydrological and meteorological factors—such as precipitation, temperature, runoff, evapotranspiration (ET), soil moisture and snow depth—for nine watersheds in the North West Himalayas (NWH): Jhelum, Tawi, Beas, Parbati, Suketi, Gangotri, Aglar, Asan, and Henval. The study employs near real-time (~1-day latency) hydrological flux data from the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) at a spatial resolution of 0.01°. To gain further insights, the trend in snow cover area (SCA) for the NWH region is analyzed using Interactive Multisensor Snow and Ice Mapping System (IMS) data from the United States National Ice Center (USNIC), disseminated by the National Oceanic and Atmospheric Administration (NOAA) via the National Snow and Ice Data Center (NSIDC). The analysis covers water balance components for these basins from 2001 to 2023. Monthly and annual averages are computed to reveal overall watershed behavior and distribution, which is closely linked to the land use and land cover (LULC) in the area. For instance, the Gangotri basin, with over 50% snow coverage, shows low ET throughout the year, a trend reflected in the long-term annual average ET values. Similarly, basins with higher SCA exhibit lower ET percentages, resulting in increased runoff and a strong correlation between rainfall and runoff patterns. A regional analysis of snow cover from 2014 to 2024, encompassing the union territories of Jammu and Kashmir, Ladakh, and the states of Himachal Pradesh and Uttarakhand, indicates a significant decrease in relative SCA. For the peak winter months of December and January, SCA dropped by about 50% from January 2023 (~2,94,635 km2) to January 2024 (~1,48,225 km2). Additionally, the Indian Meteorological Department's (IMD) daily rainfall data for Jammu and Kashmir from December 1, 2023, to January 31, 2024, shows lower rainfall compared to the previous year, likely due to reduced north-west disturbances. This prolonged snow drought poses challenges to water security and increases the risk of wildfire disasters in these regions.
The immediate ex vivo covering and filling characteristics of antibiotic-loaded resorbable calcium sulfate paste around intramedullary nails
Authors: Hamilton Amber A. , Wongcharoenwatana Jidapa , Hoellwarth Jason S. , Fragomen Austin T. , Rozbruch S. Robert , Reif Taylor J.
Published: November 2024

Abstract. Background: Antibiotic-laden polymethyl methacrylate (PMMA)-coated intramedullary nails (IMNs) are an effective treatment for osteomyelitis, but they pose multiple disadvantages. Antibiotic-loaded resorbable calcium sulfate (ARCS) paste is an alternative option to deliver a local antibiotic depot around IMNs, but such use has been minimally investigated. This study aimed to define the immediate covering and filling characteristics of ARCS around IMNs by using anatomic bone models. Method: Five tibia models (foam with cortical shell) were prepared by reaming a uniform 13 mm cylindrical path. Three 40 cc kits of ARCS (STIMULAN, Biocomposites Ltd, Keele, UK) were mixed with 3 g vancomycin and 1.2 g tobramycin powder and injected into the intramedullary canal while wet, completely filling the canal. A 10 mm × 345 mm tibial IMN was immediately inserted without interlocking screws and allowed to completely cure for 2 h. The models were then longitudinally cut without disrupting the dry ARCS covering on the nail. The ARCS was removed from the nail at five equidistant locations along the nail. The thickness of the ARCS was measured with a caliper. A repeated-measures ANOVA test was used to compare the mean width of each segment for each model. Results: In all five trials, the tibial canal volume surrounding the nail remained completely filled. The ARCS paste was confluent along the length of the IMN. There were no gaps or air pockets between the paste and reamed model bone. There was no statistically significant difference among the five samples at each location (p=0.913) or among the five locations along the bone (p=0.210). Conclusion: In a model setting, ARCS fully fills the intramedullary canal of a tibia and covers an IMN uniformly. Study of the in vivo material properties of ARCS may further elucidate the bone penetration as well as the clinical utility of this antibiotic depot technique.
Mutu Pendidikan Tinggi Islam: Pengembangan Etika Islam dan Peningkatan Kompetensi Akademik dalam Pengembangan Profesional dan Keterlibatan Dosen Perguruan Tinggi Islam Indonesia
Authors: Alfarizi Muhammad , Megawati Suci
Published: November 2024

Perkembangan pendidikan tinggi, terutama PTKI, fokus pada inovasi pengajaran, pembelajaran, dan etika dosen sebagai teladan. PTKI berperan penting dalam mencetak generasi unggul melalui integrasi ilmu dan nilai Islam. Studi ini bertujuan untuk mengeksplorasi kontribusi program peningkatan kompetensi akademik dan pengembangan etika pendidik Islam terhadap pengembangan profesional dosen PTKI serta dampak keterlibatan dalam pekerjaan akademik. Penelitian ini menggunakan pendekatan kuantitatif eksploratif dengan desain cross-sectional untuk mengkaji pengembangan profesional dosen PTKI. Data dikumpulkan melalui survei kuisioner terbuka pada 150 responden yang dipilih secara purposive sampling. Analisis data dilakukan menggunakan teknik PLS-SEM untuk mengevaluasi validitas model struktural serta hubungan variabel laten dan indikatornya. Hasil penelitian menunjukkan program peningkatan kompetensi akademik dan pengembangan etika pendidik Islam berpengaruh signifikan positif terhadap pengembangan profesional dosen. Pengembangan profesional berpengaruh langsung sekaligus mediator dalam keterlibatan pekerjaan akademik dosen. Dosen yang mengembangkan kompetensi dan etika secara berkelanjutan cenderung lebih terlibat dalam tugas akademik, berkomitmen tinggi, dan mampu menciptakan lingkungan belajar yang dinamis dan kolaboratif. Studi ini mendorong PTKI untuk merancang program pelatihan berkelanjutan yang berbasis kebutuhan dosen, serta mendorong sinergi antar-kampus melalui kolaborasi riset.
Technologies émergentes en éducation : Potentiel et défis de la personnalisation via l'IA et la Chaîne de Blocs
Authors: El Bahlouli Yassine
Published: November 2024

Cet article examine comment l'analytique de l'apprentissage, l'intelligence artificielle (IA), et la chaîne de blocs transforment la personnalisation de l'éducation. En explorant la littérature récente, il identifie les contributions et les défis de ces technologies dans l'amélioration des parcours éducatifs. L'analyse suggère que l'intégration de ces technologies offre des opportunités uniques pour la personnalisation de l'apprentissage, tout en soulevant des questions importantes sur la sécurité, la confidentialité, et l'équité. La convergence de l'IA, de l'analytique de l'apprentissage, et de la technologie de la chaîne de blocs promet une révolution dans la manière dont l'éducation est délivrée et reçue, permettant une adaptation précise au profil de chaque apprenant. Cette intégration technologique, cependant, exige une réflexion approfondie sur les cadres éthiques et réglementaires pour garantir que la personnalisation de l'éducation bénéficie à tous, sans compromettre la sécurité des données ni accentuer les inégalités. L'article plaide pour une collaboration étroite entre développeurs technologiques, éducateurs, et décideurs politiques pour relever ces défis et exploiter pleinement le potentiel de ces technologies émergentes dans l'éducation.
Employee Wellbeing and Job Engagement of Academics in Universities
Authors: T. O. Court, , K. B. Ogbolo,
Published: November 2024

The study explored the nexus between employee well-being and job engagement of academics in universities. The study adopted analytic descriptive strategy and the target population of the study was 980 lecturers; a sample of 284 was selected through stratified sampling procedure. The data collection instrument was a structured questionnaire; the instrument was validated through content approach while the reliability of the measurement instrument was determined via Cronbach alpha internal consistency. The data were collected through online platforms and offline means. The data collected were analyzed by Process Based approach using Partial Least Square Regression with the Smart PLS software version 4. The results indicated that there was a significant positive relationship between psychological well-being and job engagement; there was a significant positive relationship between social well-being and job engagement; but there was a non-significant negative relationship between subjective well-being and job engagement and there was a significant positive relationship between workplace well-being and job engagement. In view of the findings, we concluded that employee well-being is critical to the job engagement of academics in universities and recommended that university authorities should fashion out programmes aimed at fostering the holistic well-being of staff members and performance on the job.
Analysis of Published Manuscripts on Napoleon Bonaparte
Authors: Önder Oğuz Kağan
Published: November 2024

Napoleon Bonaparte stands out as one of the most important characters of the 19th century. This study was conducted to evaluate the manuscripts written for Napoleon Bonaparte. The number of publications, document types, the most attractive journals, the most chosen keywords, the most productive authors, the most cited articles, collaborative information about the studies, co-citation report, and the conceptual structure map for keywords used together were examined in this study. As a conclusion of this bibliometric study, it can be understood that the number of studies about Napoleon Bonaparte will increase. The results showed that overwhelming majority of the works on Bonaparte are single country publications. It can be suggested that multiple country publications can bring new scientific interpretations and reveal historical findings with the help of cooperation among researchers with different perspectives on the Napoleon Bonaparte who is one of the most influential character of the 19th century.
Unveiling Deception: A GAN-Based Unsupervised Learning Approach for Real-Time Generation and Detection of Text-Based Fake News
Authors: Vivek Joshi
Published: November 2024

Generative artificial intelligence technology advancements have made it easy to generate fake news. Online community platforms like social media have made propagation of such fake news faster and more convenient. We have witnessed the social impact of such fake news in the past few years. In the literature, a Generative Adversarial Network (GAN) is used to detect text-based fake news based on structured data with the supervised learning approaches. However, we have observed that most large-scale online data are unstructured and can not be used with the supervised learning approaches. In this paper, we have used an auto-encoder to select the features from the unstructured data and feed them to GAN.
"Exploring the Dynamics: Unraveling the Impact of Facets Model on Social Media Advertising among College Students"
Authors: S.Ramesh Babu, S.Ajith Kumar T.Manoj Kumar,
Published: November 2024

This research embarks on a profound exploration of the Facets Model, inspired by the foundational principles elucidated in "Advertising & IMC Practices and Principles" by Sandra Moriarty, Nancy Mitchell, Charles Wood, and William Wells. The study aims to unravel the intricate relationships between Perception, Emotion, Cognitive processes, and the Persuasive factor within the context of social media advertising. With the college student demographic as the focal point, we delve into the profound insights provided by the renowned authors, seeking to augment their theoretical framework with empirical evidence.
¿Podríamos hablar de una odontología narrativa?
Authors: Godoy Olave Jorge , Guerra Parker Catalina , Fuentes Díaz Pablo , Jofré Pávez Pamela
Published: November 2024

Aunque el modelo de atención en salud ha evolucionado, aún suele desplazar la importancia de incluir la narrativa del paciente e intenta uniformar las necesidades de las personas enfermas. La medicina narrativa nos da la capacidad de interpretar y comunicar los relatos de nuestros pacientes, a través de la escucha activa, así como de valorar la complejidad del ser humano, a diferencia de la salud basada en la evidencia, donde las experiencias de un individuo son extrapolables a otros pacientes sin importar su historia, con lo que se reduce gran parte de la narración a una clasificación objetiva en la ficha clínica, cuando lo correcto sería integrar el paradigma narrativo en la atención de personas enfermas. Creemos que enseñar competencias narrativas y saber científico a profesionales de odontología permitirá estrechar la relación clínica con los pacientes a partir de valores como la empatía y la compasión, mermando el sufrimiento ligado a lo objetivo de sus enfermedades.
To Infinity and Beyond-The Impact of Knowledge Upload on People and Society
Authors: Fisher Eddie John Paul , Fisher Eddie
Published: November 2024

The continuously improving advances in artificial intelligence (AI) technology have been the driving force behind innovative approaches to develop the field of direct knowledge upload between human brains. The results from this research confirm that there is a widening gap between knowledge transfer solutions and associated ethical and social concerns. Implications to the individual and society include technological abuse, data privacy, human intellect intellectual property (IP), prejudice and discrimination. Associated costs suggest that knowledge upload can make the benefits of it upload exclusively available to affluent people. The primary focus of scientists and researchers must place more emphasis on knowledge transfer solutions that are in the best interests of people and society. The current widening collaboration and partnership gaps between developers and scientists must be closed through the sharing of relevant knowledge and insights, setting aside cultural and geographical differences. New legislation is needed to protect people and society in ethics and social concerns. Knowledge upload reversal requires further investigation to prove its impacts/side-effects and to generate acceptable proven solutions to resolve these.
Bovine colostrum in human health promotion: determinants and moderators of purchase intention and consumption in Brazil
Authors: GALDINO Alyne Batista da Silva , ARAÚJO Emmanuella de Oliveira Moura , RIBEIRO Cláudio Vaz Di Mambro , CORDEIRO Clarice Gebara Muraro Serrate , SANTOS Geraldo Tadeu dos , SALES Danielle Cavalcanti , MARQUES JÚNIOR Sérgio , RANGEL Adriano Henrique do Nascimento
Published: November 2024

This study aimed to investigate the perception of the Brazilian population about bovine colostrum and the perspectives of consumption and purchase of its derived foods. A questionnaire was made available on the Google Forms® platform and disseminated through social networks. A total of 1,179 people from 19 Brazilian states responded. Spearman’s test was used to identify correlations between variables, and the Kruskal–Wallis test was used to compare means. Correlation and difference of means were considered significant when p < 0.05. Most respondents (45.0%) reported having no knowledge about bovine colostrum and never having had contact with it (67.8%). However, they believe that consumption can benefit human health (61.6%). They also reported their intention to consume and purchase food and derived supplements in the form of dairy products, powdered supplements, and flavored liquid supplements. Sensory aspects can contribute to the non-consumption of bovine colostrum. However, a lack of knowledge about the products and their benefits, availability, and price can further influence the intention not to consume derivatives. Thus, it is likely that foods derived from bovine colostrum will be well accepted if commercialized in the Brazilian market.
La adecuación de los procesos académicos-administrativos a la virtualidad. Caso: La juramentación virtual de los graduandos en la Universidad de Los Andes
Authors: Pacheco Juan
Published: November 2024

La Universidad de Los Andes ha ido adaptando sus procesos académicos administrativos a la virtualidad. Uno de estos procesos es la juramentación virtual para los estudiantes de pregrado y postgrado que, cumpliendo los requisitos legales y académicos para obtener su grado, no pueden hacer acto de presencia física en el acto protocolar de grado programado por la Universidad. La juramentación es un acto personal y obligatorio y, desde abril 2022 se realiza también de forma virtual, a través de plataformas de videoconferencias. El interés de este artículo es caracterizar el proceso de juramentación virtual de los graduandos de la Universidad de Los Andes en el período 2022-2023. Se realizó un análisis de documentos históricos, normativos y estadísticas disponibles. La juramentación virtual de abril y diciembre de 2022 presentó el mayor número de graduandos y las carreras que más optan a la juramentación virtual son Enfermería y Educación. La juramentación virtual es una muestra de la adecuación de los procesos administrativos académicos en los que puede avanzarse a pesar de los problemas de entorno de baja conectividad, pero, también, permite a los graduandos que no pueden asistir al acto protocolar, vivir con sus familiares y amigos, la experiencia de parte del acto de grado tradicional.
La construcción del sujeto: mediante la pedagogía del cuerpo y los vínculos afectivos
Authors: Rodríguez Annyulie
Published: November 2024

El pretender analizar la construcción del sujeto, en medio de una sociedad de constantes cambios es una tarea ardua, y si a esto le sumamos cómo se encuentran las escuelas en la actualidad, se hace necesario reflexionar sobre la des-proporcionalidad que existe entre la realidad y el currículo, este trabajo pretende analizar, proponer y aportar desde la Pedagogía del cuerpo y los vínculos afectivos que deben existir entre la/el docente y el niño, una nueva forma de llevar el proceso de enseñanza y aprendizaje . Por lo tanto, adquirir un compromiso desde la educación, el estado es una pieza importante para este progreso, la creación de políticas públicas que incluyan el cambio metodológico, didáctico, pedagógico, para así adecuar las circunstancias propuestas con la intención que puedan modificar el andar pedagógico en el aula, dándole respuesta a la demanda de la sociedad. Para alcanzarlo, es importante la formación del docente con respecto a las metodologías afectivas y las herramientas a adquirir para transformar la realidad, en la construcción de conceptos más abstractos asociados al desarrollo cognitivo, socio-emocional del individuo. En tal sentido, a continuación, se presenta el enfoque de varios autores, teorías y conocimientos fundamentales que permiten determinar el marco de referencia que se quiere estudiar, en el contexto educativo.
Peningkatan Pengetahuan Guru SD dalam Mendesain Perangkat Pembelajaran Berbasis TPACK
Authors: Mardhatillah Mardhatillah , Arifin Slamet , Anggraini Ade Eka , Rahayuningsih Sri , Faizah Siti , Filina Nurul Zikri
Published: November 2024

Kegiatan ini bertujuan untuk meningkatkan pengetahuan dan keterampilan guru SD dalam mendesain perangkat pembelajaran berbasis TPACK di SD N 3 Bareng. Kegiatan pengabdian masyarakat dilaksanakan melalui beberapa tahapan: perencanaan, tindakan, observasi dan evaluasi, serta refleksi. Metode yang digunakan adalah action research yang terdiri dari pelatihan, simulasi, dan praktek langsung. Hasil penelitian menunjukkan adanya peningkatan signifikan dalam pengetahuan dan keterampilan guru dalam mendesain perangkat pembelajaran berbasis TPACK, yang dibuktikan dengan hasil pre-test dan post-test. Penggunaan TPACK membantu guru dalam menciptakan pembelajaran yang lebih interaktif, efektif, dan menyenangkan, serta memberikan dampak positif terhadap kualitas pembelajaran di kelas.
Analysis of the Influence of Host Characteristics on Consumer Purchase Intention in E-commerce Livestreaming
Authors: Xie Ling , Nallaluthan Kesavan
Published: November 2024

In the current e-commerce livestreaming environment, the host serves as a crucial bridge between products and consumers. The characteristics of these hosts significantly influence consumer purchase intentions. With the booming growth of the e-commerce livestreaming industry, an increasing number of consumers are turning to livestreams to learn about and purchase products. Factors such as the hosts' demeanor, professional competence, and interactive abilities have become significant in influencing consumer decisions. The livestreaming environment offers a more intuitive, clear, and convenient shopping experience, encouraging consumers to explore products through livestreams and fostering a desire to purchase. Given the relatively recent development of e-commerce livestreaming, the mechanisms by which various factors influence consumer purchase intentions are not yet fully understood. Therefore, it is necessary to adopt scientific measures based on actual conditions to enhance the professionalism and visibility of e-commerce hosts during broadcasts, improve the quality of product information disclosure, and strengthen consumers' perceived value and trust in livestreaming, thereby enhancing their purchase intentions.