bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing accuracy and efficiency in real-time people counting with cascaded object detection
Authors: Holla M. Raviraja , Suma D. , Holla M. Darshan 
Published: August 2024

AbstractGrowing concerns about public safety have driven the demand for real-time surveillance, particularly in monitoring systems like people counters. Traditional methods heavily reliant on facial detection face challenges due to the complex nature of facial features. This paper presents an innovative people counting system known for its robustness, utilizing holistic bodily characteristics for improved detection and tallying. This system achieves exceptional performance through advanced computer vision techniques, with a flawless accuracy and precision rate of 100% under ideal conditions. Even in challenging visual conditions, it maintains an impressive overall accuracy of 98.42% and a precision of 97.51%. Comprehensive analyses, including violin plot and heatmaps, support this outstanding performance. Additionally, by assessing accuracy and execution time concerning the number of cascading stages, we highlight the significant advantages of our approach. Experimentation with the TUD-Pedestrian dataset demonstrates an accuracy of 94.2%. Evaluation using the UCFCC dataset further proves the effectiveness of our approach in handling diverse scenarios, showcasing its robustness in real-world crowd counting applications. Compared to benchmark approaches, our proposed system demonstrates real-time precision and efficiency.
A hybrid SARIMA-Prophet model for predicting historical streamflow time-series of the Sobat River in South Sudan
Authors: Kenyi Manzu Gerald Simon , Yamamoto Kayoko 
Published: August 2024

AbstractAccurate river streamflow forecasting is pivotal for effective water resource planning, infrastructure design, utilization, optimization, and flood planning and warning. Streamflow prediction remains a difficult task due to several factors such as climate change, topography, and lack of observed data in some cases. This paper investigates and evaluates the individual performances of the seasonal auto-regressive integrated moving average (SARIMA) and Prophet models in forecasting the streamflow of the Sobat River and proposes a hybrid SARIMA-Prophet model to leverage the strengths of both approaches. Using the augmented Dickey-Fuller (ADF) and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests, the flow of the Sobat River was found to be stationary. The performance of the models was then assessed based on their residual errors and predictive accuracy using the mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination (R2). Residual analysis and prediction capabilities revealed that Prophet slightly edged SARIMA in terms of prediction efficacy; however, both models struggled to effectively capture extreme values, resulting in significant overestimations and slight underestimations. The hybrid SARIMA-Prophet model significantly reduced residual variability, achieving a lower MAE of 4.047 m3/s, RMSE of 6.17 m3/s, and a higher R2 of 0.92 than did the SARIMA (MAE: 5.39 m3/s, RMSE: 8.70 m3/s, R2: 0.85) and Prophet (MAE: 5.35 m3/s, RMSE: 8.32 m3/s, and R2: 0.86) models. This indicates that the hybrid model handles both long-term patterns and short-term fluctuations more effectively than the individual models. The findings of the present study highlight the potential of hybrid SARIMA-Prophet models for streamflow forecasting in terms of accuracy and reliability, thus contributing to more effective water resource management and planning, particularly in the Sobat River.
The Value of Drilling—A Chance-Constrained Optimization Approach
Authors: Jeuken Rick , Forbes Michael 
Published: August 2024

AbstractManaging uncertainty is a core challenge in mine planning. Mine planners often represent various planning variables, such as equipment performance and geological parameters, as random variables due to inherent uncertainties. This paper looks at geological uncertainty and its impact on mine planning. Some traditional approaches to manage this uncertainty include using conditional simulations or mathematical programming in the planning process. Drilling additional holes, despite its cost, is a common method to reduce uncertainty using additional samples to reduce deposit variance. In this paper, we first outline an ore blending optimization model which uses chance-constrained programming to manage property limit risk when selecting the order of ore feed into a processing facility. In coal mining, in tactical planning horizons, the order of coal seam removal is usually predetermined, allowing a blending model to ensure optimal feed properties. Using chance-constrained programming allows us to blend the uncertainties from geological models to maximize plant output while adhering to property constraints. We use the chance-constrained blending model to determine the value of additional information from infill drilling. The model prioritizes drilling locations that reduce uncertainty and improve blending outcomes. A case study on a coking coal mine in Queensland, Australia, demonstrates the model’s application, highlighting significant improvements in blending by reducing the variance of high-quality blocks. The study concludes that targeting high-quality blocks for variance reduction can better accommodate lower-quality material, offering a more valuable approach than the traditional focus of reducing uncertainty in low-quality blocks. This approach provides insights for improving mine planning strategies and showcases the potential of chance constraints in optimizing ore blending under uncertainty.
Aggregate Stability and Aggregate-Associated Organic Matter along a Soil Chronosequence on the Galápagos Archipelago
Authors: Chittamart Natthapol , Mentler Axel , Rechberger Maria V. , Gerzabek Martin H. , Zehetner Franz 
Published: August 2024

AbstractPurpose: Soil aggregate stability is a crucial property affecting soil erodibility, water infiltration and carbon sequestration. This study aimed to determine ultrasonic aggregate stability (USAS) as well as solid and dissolved organic carbon (OC and DOC) associated with aggregate fractions of different aggregation strength and size in volcanic soils along an Andosol-Luvisol-Cambisol chronosequence on the Galápagos Islands. Methods: Aggregate stability was determined by ultrasonication at different energy levels, i.e. 20, 100, and 500 J mL− 1. OC was measured in different aggregate size fractions, i.e. macroaggregates (250–2000 μm), microaggregates (63–250 μm), and the fraction < 63 μm, and released DOC was determined. Results: Aggregate breakdown increased with ultrasonic energy input. The Andosol (short-range order minerals, high OC) had the highest aggregate stability among the studied soils. The OC contents in the stable macro- and microaggregates (at 20 J mL− 1) were highest in the Andosol (20.4 and 20.1%, respectively), followed by the Luvisol (11.6 and 10.8%, respectively) and the Cambisol (6.5 and 6.7%, respectively). The decreasing aggregate-associated OC stabilization with increasing soil age coincided with mineralogical changes from short-range order phases to high-activity clays to low-activity clays. The release of DOC during sonication was highest for the intermediate-aged soil (Luvisol) and mainly occurred at low and intermediate energy levels, while for the young soil (Andosol), released DOC steadily increased until the highest energy level. Conclusions: Our results imply that mineralogical/pedogenic changes over millennial time scales can make volcanic soils more susceptible to losses of OC by leaching and water erosion.
A Novel Stem Cell Model to Study Preeclampsia Endothelial Dysfunction
Authors: Wu Yanming , Sun Tianyanxin , Medina Pedro , Narasimhan Purnima , Stevenson David K. , Von Versen-Höynck Frauke , Armstrong Jennifer , Wu Joseph C. , Sayed Nazish , Winn Virginia D. 
Published: August 2024

AbstractPreeclampsia is a common pregnancy complication affecting 5% to 7% of all pregnancies worldwide annually. While the pathogenesis is not fully understood, maternal endothelium dysfunction is thought to be a central component to preeclampsia development. Studies to dissect maternal endothelial dysfunction, particularly on a patient-specific basis, are hampered by limited access to systemic primary endothelial cells (ECs). The objective of this study was to establish a replenishable, patient-specific in vitro EC model to allow robust mechanistic studies to dissect endothelial dysfunction in preeclampsia. Induced pluripotent stem cells (iPSCs) from three women with a history of normotensive pregnancies were differentiated into ECs. The established ECs were exposed to pooled sera from normotensive pregnancies, preeclamptic pregnancies, normotensive postpartum for non-pregnant comparison and controls. Endothelial functions including nitric oxide (NO) release, cell migration, tube formation and viability were evaluated. Levels of NO release were significantly lower after incubation with preeclamptic sera compared to the fetal bovine serum (FBS) control, and normotensive and non-pregnant (postpartum) sera treatments were also lower than FBS but higher than preeclamptic sera treatments. Tube formation and cell migration were also impaired with preeclamptic sera compared to FBS controls. Cell viabilities remained unaffected by any sera treatment. Consistent outcomes were obtained across all three patient-specific lines treated with the same pooled sera. Establishment of patient-derived iPSC-ECs treated with pregnancy sera serves as a novel model to explore the interplay between individual maternal endothelial health and circulating factors that lead to endothelial dysfunction in preeclampsia.
Multiple sclerosis: a narrative overview of current pharmacotherapies and emerging treatment prospects
Authors: Olejnik Piotr , Roszkowska Zuzanna , Adamus Sylwia , Kasarełło Kaja 
Published: August 2024

AbstractMultiple sclerosis (MS) is a chronic autoimmune disease characterized by pathological processes of demyelination, subsequent axonal loss, and neurodegeneration within the central nervous system. Despite the availability of numerous disease-modifying therapies that effectively manage this condition, there is an emerging need to identify novel therapeutic targets, particularly for progressive forms of MS. Based on contemporary insights into disease pathophysiology, ongoing efforts are directed toward developing innovative treatment modalities. Primarily, monoclonal antibodies have been extensively investigated for their efficacy in influencing specific pathological pathways not yet targeted. Emerging approaches emphasizing cellular mechanisms, such as chimeric antigen receptor T cell therapy targeting immunological cells, are attracting increasing interest. The evolving understanding of microglia and the involvement of ferroptotic mechanisms in MS pathogenesis presents further avenues for targeted therapies. Moreover, innovative treatment strategies extend beyond conventional approaches to encompass interventions that target alterations in microbiota composition and dietary modifications. These adjunctive therapies hold promise as complementary methods for the holistic management of MS. This narrative review aims to summarize current therapies and outline potential treatment methods for individuals with MS.
Escalating Wildfires in Siberia Driven by Climate Feedbacks Under a Warming Arctic in the 21st Century
Authors: Huang Xin , Xue Lian , Wang Zilin , Liu Yawen , Ding Ke , Ding Aijun 
Published: August 2024

AbstractSiberian wildfire is of paramount importance in the carbon cycle and climate change as it is a major disturbance in the pan‐Arctic ecosystems. In recent decades, the Siberian wildfire regime has been shifting; however, less is known about its process‐based feedback mechanisms. By integrating in‐situ and satellite observational data sets as well as chemistry‐climate coupled modeling, we find that central Siberia has featured the most prominent wildfire escalation during the past two decades, which is closely related to hydrological drought with decreasing rainfall and drying soil under a fast‐warming Arctic. Furthermore, fire‐emitted aerosols compound the increasing wildfires via serving as cloud condensation nuclei and suppressing precipitation, forming self‐amplifying feedback. As the Arctic warming is projected to continue, wildfires are estimated to more than double by the end of this century. This work highlights the great importance of fire risk management based on a fundamental scientific understanding of the complex climate system.
Integrated Spectral and Compositional Analysis for the Lunar Tsiolkovskiy Crater
Authors: Tognon Gloria , Zambon Francesca , Carli Cristian , Massironi Matteo , Giacomini Lorenza , Pozzobon Riccardo , Salari Giulia , Tosi Federico , Combe Jean‐Philippe , Fonte Sergio 
Published: August 2024

AbstractRemote sensing observations represent the primary means in the production of geologic maps of planetary surfaces. However, they do not provide the same level of detail as Earth's geologic maps, which rely also on field observations and laboratory analyses. Color‐derived basemaps can help to bridge this gap by highlighting peculiar surface and compositional properties. Here, we analyzed the spectral properties of the lunar Tsiolkovskiy crater through the definition of spectral units summarizing the information enclosed by a set of selected spectral parameters. We then performed a compositional analysis of the newly derived spectral units that helped us in discriminating the presence and relative abundance of the main mineralogical phases on the Moon. As a final step, we produced a geo‐stratigraphic map of the Tsiolkovskiy crater integrating in a single mapping product both morphologic, stratigraphic and compositional information. The basaltic infilling of the crater is distinguished by three spectral units associated with distinct effusive events presenting a different composition. On the central peak, plagioclase and olivine suggest the presence of Mg‐suite rocks from the lower crust. The continuous ejecta deposits are mostly characterized by impact melts and shocked materials rich in glass or agglutinates related to more mature terrains from which occasionally appear fresher anorthositic and gabbroic outcrops exposed by the inward sliding of the crater walls. Overall, the geo‐stratigraphic map allows inferring compositional variations associated with the different morpho‐stratigraphic units, which clarify and elaborate on the compositional heterogeneities within the lunar crust and the Tsiolkovskiy crater, and its geologic evolutionary history.
The Effect of Drying Boreal Lakes on Plants, Soils, and Microbial Communities in Lake Margin Habitats
Authors: Patil Vijay P. , McFarland Jack W. , Wickland Kimberly P. , Manies Kristen , Winterstein Mark , Hollingsworth Teresa N. , Euskirchen Eugénie S. , Waldrop Mark P. 
Published: August 2024

AbstractDecadal scale lake drying in interior Alaska results in lake margin colonization by willow shrub and graminoid vegetation, but the effects of these changes on plant production, biodiversity, soil properties, and soil microbial communities are not well known. We studied changes in soil organic carbon (SOC) and nitrogen (N) storage, plant and microbial community composition, and soil microbial activities in drying and non‐drying lakes in the Yukon Flats National Wildlife Refuge. Historic changes in lake area were determined using Landsat imagery. Results showed that SOC storage in drying lake margins declined by 0.13 kg C m−2 yr−1 over 30 years of exposure of lake sediments, with no significant change in soil N. Lake drying resulted in an increase in graminoid and shrub aboveground net primary production (ANPP, +3% yr−1) with little change in plant functional composition. Increases in ANPP were similar in magnitude (but opposite in sign) to losses in SOC over a 30‐year drying trend. Potential decomposition rates and soil enzyme activities were lower in drying lake margins compared to stable lake margins, possibly due to high salinities in drying lake margin soils. Microbial communities shifted in response to changing plant communities, although they still retained a legacy of the previous plant community. Understanding how changing lake hydrology impacts the ecology and biogeochemistry of lake margin terrestrial ecosystems is an underexamined phenomenon with large impacts to landscape processes.
A Real‐Time Prediction System of the Intensity of Solar Energetic Proton Events Based on a Solution of the Diffusion Equation
Authors: Zhang Y. , Wang Y. , Li X. , Zuo P. B. 
Published: August 2024

AbstractIn this study, based on solar energetic particle (SEP) events classification and a solution of the diffusion equation, we present an efficient system, HITSEP, to predict the intensities in different energy channels (P4 15.0–44.0 MeV, P5 40.0–80.0 MeV, and P6 80.0–165.0 MeV) of energetic proton events observed by GOES spacecraft. The system can predict the rising phase (especially the peak time and peak intensity) of the energetic proton events using only a small amount of data at the beginning of the solar energetic proton events. Among the events that meet the conditions for the use of our prediction system from 2003 to 2017, for P4, P5, and P6 channels, the median Warning Times are 3.70, 2.52, and 1.69 hr; the median Error of the Intensity for events are 0.43, 0.23, 0.34 orders of magnitude; the median Error of the Peak Time for events are 2.53, 0.55, 0.43 hr, respectively. Our system is based on physical mechanisms and has a high accuracy in forecasting the peak intensity with a strict definition of the error. The HITSEP system has huge potential to apply in the space weather forecast. The application of the HITSEP system in space weather forecasting is very promising.
Tracer Velocity Versus Bedload Velocity: Derivation of the Unsteady Virtual Bedload Velocity From Decelerating Tracers
Authors: Klösch M. , Pessenlehner S. , Gmeiner P. , Habersack H. 
Published: August 2024

AbstractDuring rest periods, bedload tracers can be buried, while transport can move them to locations with different bed shear stresses or a different riverbed composition. This affects the mobility of the tracers compared to that of the bedload at the location where the tracers were seeded and has so far limited the explanatory power of field tracer studies on the virtual bedload velocity. This paper proposes a method to assess both the unsteady virtual tracer velocity and the unsteady virtual bedload velocity from field tracer studies. First, the virtual bedload velocity was conceptualized as the velocity of a relay run and contrasted with the velocity of the decelerating runs of bedload tracers. Then, a regression method for deriving the unsteady virtual velocity of bedload tracers was extended to account for tracer slowdown by including a corresponding function of the distance traveled. Finally, data from 65 bedload tracers in the Upper Drava River with very‐high‐frequency (VHF) transmitters were used for method testing. By linking the measured tracer mobility to the hydraulics and bed surface grain size near the seeding location, it was possible to determine the unsteady bedload velocity function as the unsteady tracer velocity function at a travel distance of zero. The tracer travels exhibited increasing slowdown effects with increasing tracer grain size, probably due to the dominant role of advection effects at the study site. The derivation of the bedload velocity ensures comparability to laboratory results and between tracer studies.
Effect of Tropical Cyclone Intensity on the Relationship Between Hydrometeor Distribution and Rapid Intensification by GPM GMI
Authors: Leng Yuankang , Liu Rui , Zhu Peijun , Zhang Honglei 
Published: August 2024

AbstractThis study analyzes hydrometeor evolution during rapid intensification (RI) and tropical cyclone (TC) intensity dependence using satellite data. Previous studies have suggested ice cloud water or non‐convective precipitation as a predictor of RI from different perspectives. However, few studies have focused on the impact of TC intensity or comprehensive comparisons to identify better indicators. During RI, hydrometeor contents in weak TCs increase over the entire region, whereas they increase mainly in the inner‐core region and decrease in advance in the outer‐core region for strong TCs. Hydrometeor contents in the inner‐core are higher in RI than in slow intensification, and their maxima location is related to TC intensity and intensification rate. Cloud water path (CWP) in the inner‐core region is most correlated with the intensification rate, especially in weak TCs. Therefore, the CWP can serve as a predictor of RI and can be applied to all TC intensities.
Dust Source Areas and Their Plume Extent Derived From Satellite Data Fields
Authors: AlNasser Faisal , Chehbouni Abdelghani , Entekhabi Dara 
Published: August 2024

AbstractIn this study, prominent dust source areas are identified along with their plume extent using high temporal frequency satellite observations. Hourly dust plume observations of the Dust Belt from geostationary‐orbit satellites are analyzed for the 2017‐12–2022‐11 period. To identify dust source areas and their extents, we back‐track plumes to their source, assessing source areas in terms of emission frequency, contribution, and plume extent patterns. This method advances over traditional source allocation techniques that rely on polar‐orbiting satellites based on a few daily passes and meteorological wind fields for backtracking. Our findings indicate that Boreal summer is the most intense season for most sources, except in the Southern Sahara, which experiences winterly winds. Our analysis also reveals significant contributions from regions within the Sahara that experience expansive but infrequent dust storms, highlighting the importance of considering both frequency and magnitude in understanding dust emissions.
Analysis of the Antarctic Marginal Ice Zone Based on Unsupervised Classification of Standalone Sea Ice Model Data
Authors: Day Noah S. , Bennetts Luke G. , O’Farrell Siobhan P. , Alberello Alberto , Montiel Fabien 
Published: August 2024

AbstractThe Antarctic marginal ice zone, the regularly wave‐affected outer band of the sea ice covered Southern Ocean, typically contains an unconsolidated ice cover comprised of smaller, thinner floes than the inner ice pack. Thus, it is a highly dynamic region and susceptible to rapid expansion and contraction, making it a focal area for understanding and predicting the response of Antarctic sea ice to a changing climate. This novel study uses unsupervised statistical clustering of sea ice data simulated by a global sea ice model (standalone CICE6 combined with a wave propagation module and prescribed ocean) to address the outstanding challenge of separating the marginal ice zone from the inner ice pack in sea ice data sets. The method identifies a marginal ice zone with the desired characteristics and floe size is shown to be the key variable in the classification. Simulated marginal ice zone widths are similar to those derived from satellite observations of wave penetration distances, but contrast with those using the standard 15%–80% areal sea ice concentration proxy, particularly during austral winter. The simulated marginal ice zone is found to undergo a seasonal transition due to new ice formation in winter, increased drift in spring, and increased rates of wave‐induced breakup and melting in summer. The understanding gained from the study motivates incorporation of wave and floe‐scale processes in sea ice models, and the methods are available for application to outputs from high‐resolution and coupled sea ice–ocean–wave models for more detailed studies of the marginal ice zone (in both hemispheres).