bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electromagnetic Model of K‐Changes
Authors: Kašpar Petr , Marshall Thomas , Stolzenburg Maribeth , Kolmašová Ivana , Santolík Ondřej 
Published: October 2024

AbstractK‐changes are observed as step‐like increases in the thundercloud electric fields. The K‐changes occur in the late part of intra‐cloud lightning or during negative cloud‐to‐ground lightning between return strokes. It has been shown that the processes leading to K‐changes initiate in the decayed part of a positive leader channel and propagate toward the flash origin. They are often accompanied by microsecond‐scale electric field pulses. We introduce a new model to simulate processes leading to the K‐changes in cloud‐to‐ground lightning. Our method is based on the full solution of Maxwell's equations coupled to Poisson's equation for the thundercloud charge structure. To model the K‐changes, we gradually increase the decayed channel conductivity. The modeled current wavefront propagates due to the K‐processes downward along a vertical channel and completely attenuates before reaching the ground. We derive the evolution of the linear charge densities and the scalar electric potential along the channel leading to K‐changes. We model electrostatic step‐like changes in the measured electric field together with the approximate rates and amplitudes of the microsecond scale pulses. Step‐like changes increase their amplitudes with the length of the simulated channel and with a higher conductivity of the channel. The microsecond‐scale pulse waveshapes depend mainly on the propagation velocity of the current wave, and the time scale of the conductivity increase. We show that our modeled waveforms are in a good agreement with observations conducted in Florida.
Inferring Surface NO2 Over Western Europe: A Machine Learning Approach With Uncertainty Quantification
Authors: Sun Wenfu , Tack Frederik , Clarisse Lieven , Schneider Rochelle , Stavrakou Trissevgeni , Van Roozendael Michel 
Published: October 2024

AbstractNitrogen oxides (NOx = NO + NO2) are of great concern due to their impact on human health and the environment. In recent years, machine learning (ML) techniques have been widely used for surface NO2 estimation with rapid developments in computational power and big data. However, the uncertainties inherent to such retrievals are rarely studied. In this study, a novel ML framework has been developed, enhanced with uncertainty quantification techniques, to estimate surface NO2 and provide corresponding data‐induced uncertainty. We apply the Boosting Ensemble Conformal Quantile Estimator (BEnCQE) model to infer surface NO2 concentrations over Western Europe at the daily scale and 1 km spatial resolution from May 2018 to December 2021. High NO2 mainly appears in urban areas, industrial areas, and roads. The space‐based cross‐validation shows that our model achieves accurate point estimates (r = 0.8, R2 = 0.64, root mean square error = 8.08 μg/m3) and reliable prediction intervals (coverage probability, PI‐50%: 51.0%, PI‐90%: 90.5%). Also, the model result agrees with the Copernicus Atmosphere Monitoring Service (CAMS) model. The quantile regression in our model enables us to understand the importance of predictors for different NO2 level estimations. Additionally, the uncertainty information reveals the extra potential exceedance of the World Health Organization (WHO) 2021 limit in some locations, which is undetectable by only point estimates. Meanwhile, the uncertainty quantification allows assessment of the model's robustness outside existing in‐situ station measurements. It reveals challenges of NO2 estimation over urban and mountainous areas where NO2 is highly variable and heterogeneously distributed.
Frequency and Spatial Variability of European Record Floods
Authors: Bertola M. , Castellarin A. , Viglione A. , Valtancoli E. , Blöschl G. 
Published: October 2024

AbstractRegional envelope curves (RECs) have been used to characterize the flooding potential of regions worldwide. However, a comprehensive assessment for Europe is still missing. In this study we use the largest European flood database to quantify the magnitude of record floods, their dependence on catchment size, and the amount of available independent information, which is needed for estimatinig the REC's exceedance probability. We propose a framework for estimating REC parameters across large areas, consisting in partitioning the domain according to the observation density and estimating the REC slope through quantile regression. The results show that the REC parameters vary substantially across Europe. The envelope unit flood associated with a catchment area of 1,000 km2 varies between 0.1 and 6 m3s−1 km−2 and is highest in Mediterranean and Alpine areas and lowest in central‐eastern Europe. The slope of the envelope varies between 0 and −1 and is larger in Southern Europe than in Northern Europe. These differences are explained by steeper landscape in mountaineous regions and localized short duration storms producing large floods in small catchments in the Mediterranean, whose intensities are larger than in other parts of Europe. Based on the framework of probabilistic envelope curves we show that, despite the uneven observation density, the obtained RECs are associated with comparable exceedance probabilities.
Earthquake Growth Inhibited at Higher Coulomb Stress Change Rate at Groningen
Authors: Tamama Y. , Acosta M. , Bourne S. J. , Avouac J. P. 
Published: October 2024

AbstractGas extraction from the Groningen gas field resulted in significant induced seismicity. We analyze the magnitude‐frequency distribution of these earthquakes in space, time and in view of stress changes calculated based on gas production and reservoir properties. Previous studies suggested variations related to reservoir geometry and stress. While we confirm the spatial variations, we do not detect a clear sensitivity of b‐value to Coulomb stress changes. However, we find that b‐value correlates positively with the rate of Coulomb stress changes. This correlation is statistically significant and robust to uncertainties related to stress change calculation. This study thus points to a possible influence of stress change rate on the probability of the magnitude of induced earthquakes.
On the Stationarity of the Global Spatial Dependency of Heat Risk on Drought
Authors: Zampieri M. , Ashok K. , Toreti A. , Bavera D. , Hoteit I. 
Published: October 2024

AbstractLand surface processes such as the soil moisture—air temperature coupling influence compound climate anomalies like heatwaves and droughts, yet the spatial and temporal variability of the coupling strength is still understudied. We assess global land exposure to concurrent heat waves and drought since the 1980s. We found that drought significantly shapes the spatial distribution of the risk of heat waves. We show that the portion of global land experiencing drought‐conditioned heat anomalies more than tripled in less than 3 decades. However, using such traditional heat waves indicators, the level of spatial coupling between heat waves and drought seems to decline. Conversely, time‐dependent approaches accounting for the baseline climate change offer a more stable perspective. We conclude that tailoring hazard definitions to specific processes and impacts is crucial. Early warning systems can play a prominent role in mitigating the impacts of global warming to society.
On the Use of SMAP Soil Moisture for Forecasting NDVI Over CONUS Cropland Regions
Authors: Le Manh‐Hung , Bolten John D. , Whitney Kristen M. , Johnson David M. , Mueller Rick , Mladenova Iliana E. 
Published: October 2024

AbstractVegetation health forecasting (NDVI as a proxy) informs decision‐makers about the end of season crop yield productivity but is not well‐documented. This study tests improvements in vegetation health forecasting by developing a data‐driven Dynamic Agricultural Productivity Indicator (DAPI), which simultaneously incorporates satellite‐based root zone soil moisture (RZSM) and satellite‐based NDVI data. RZSM is estimated via data assimilation of satellite based SMAP SM dataset. We employ the proposed DAPI forecast across four cropland types in the CONUS, including corn, cotton, soybeans, and wheat. Results demonstrate superior performance of the DAPI forecasts compared to climatology‐based NDVI forecasts, with the largest improvements in water‐limited regions. DAPI shows particularly good performance during hydrologic disturbances such as floods and droughts. To this end, the DAPI approach is useful in estimating future vegetation health for identifying potential food‐insecure areas, predicting crop price changes, and projecting expected commodities market trends.
Electron Dissipation and Electromagnetic Work
Authors: Yang Yan , Adhikari Subash , Matthaeus William H. 
Published: October 2024

AbstractWith the increase in technical capabilities of computer simulation in recent years, it has become feasible to quantify the degradation of fluid scale plasma and electromagnetic energies in favor of increases of internal energies. While it is understood that electromagnetic energy can be exchanged with fluid scale velocities, it is the pressure strain interaction that exchanges energy between fluid motions and internal energy. Here using simulations of both turbulence and reconnection we show that for electrons, the pressure strain and electromagnetic work are closely related and are frequently comparable when appropriate time and spatial averaging is applied. Otherwise, the instantaneous spatial averaged pressure strain and electromagnetic work are nearly equal for slowly evolving systems, like the reconnection case, while they differ significantly in rapidly evolving systems, like the turbulence case. This clarifies the relationship between these two quantities, which are each frequently used as measures of dissipation.
AKR1B1-dependent fructose metabolism enhances malignancy of cancer cells
Authors: Zhao Qing , Han Bing , Wang Lu , Wu Jia , Wang Siliang , Ren Zhenxing , Wang Shouli , Yang Haining , Carbone Michele , Dong Changsheng , Melino Gerry , Chen Wen-Lian , Jia Wei 
Published: October 2024

AbstractFructose metabolism has emerged as a significant contributor to cancer cell proliferation, yet the underlying mechanisms and sources of fructose for cancer cells remain incompletely understood. In this study, we demonstrate that cancer cells can convert glucose into fructose through a process called the AKR1B1-mediated polyol pathway. Inhibiting the endogenous production of fructose through AKR1B1 deletion dramatically suppressed glycolysis, resulting in reduced cancer cell migration, inhibited growth, and the induction of apoptosis and cell cycle arrest. Conversely, the acceleration of endogenous fructose through AKR1B1 overexpression has been shown to significantly enhance cancer cell proliferation and migration with increased S cell cycle progression. Our findings highlight the crucial role of endogenous fructose in cancer cell malignancy and support the need for further investigation into AKR1B1 as a potential cancer therapeutic target.
Mediator MED23 controls oligodendrogenesis and myelination by modulating Sp1/P300-directed gene programs
Authors: Zhang Shuai , Feng Xue , Li Chong-Hui , Zheng Yuan-Ming , Wang Meng-Ya , Li Jun-Jie , Dai Yun-Peng , Jing Naihe , Zhou Jia-Wei , Wang Gang 
Published: October 2024

AbstractGaining the molecular understanding for myelination development and regeneration has been a long-standing goal in neurological research. Mutations in the transcription cofactor Mediator Med23 subunit are often associated with intellectual disability and white matter defects, although the precise functions and mechanisms of Mediator in myelination remain unclear. In this study, we generated a mouse model carrying an Med23Q649R mutation that has been identified in a patient with hypomyelination features. The MED23Q649R mouse model develops white matter thinning and cognitive decline, mimicking common clinical phenotypes. Further, oligodendrocyte-lineage specific Med23 knockout mice verified the important function of MED23 in regulating central nervous system myelination and postinjury remyelination. Utilizing the in vitro cellular differentiation assay, we found that the oligodendrocyte progenitor cells, either carrying the Q649R mutation or lacking Med23, exhibit significant deficits in their capacity to differentiate into mature oligodendrocytes. Gene profiling combined with reporter assays demonstrated that Mediator Med23 controls Sp1-directed gene programs related to oligodendrocyte differentiation and cholesterol metabolism. Integrative analysis demonstrated that Med23 modulates the P300 binding to Sp1-targeted genes, thus orchestrating the H3K27 acetylation and enhancer activation for the oligodendrocyte lineage progression. Collectively, our findings identified the critical role for the Mediator Med23 in oligodendrocyte fate determination and provide mechanistic insights into the myelination pathogenesis associated with MED23 mutations.
Artificial intelligence-based analysis of retinal fluid volume dynamics in neovascular age-related macular degeneration and association with vision and atrophy
Authors: Yu Siqing , Jones Ian Lloyd , Maunz Andreas , Bachmeier Isabel , Albrecht Thomas , Ebneter Andreas , Gliem Martin , Staurenghi Giovanni , Sadda SriniVas R. , Chakravarty Usha , Fauser Sascha 
Published: October 2024

Abstract

Background/objectives
To characterise morphological changes in neovascular age-related macular degeneration (nAMD) during anti-angiogenic therapy and explore relationships with best-corrected visual acuity (BCVA) and development of macular atrophy (MA).

Subjects/methods
Post-hoc analysis of the phase III HARBOR trial. SD-OCT scans from 1097 treatment-naïve nAMD eyes were analysed. Volumes of intraretinal cystoid fluid (ICF), subretinal hyperreflective material (SHRM), subretinal fluid (SRF), pigment epithelial detachment (PED) and cyst-free retinal volume (CFRV) were measured by deep-learning model. Volumes were analysed by treatment regimen, macular neovascularisation (MNV) subtypes and topographic location. Associations of volumetric features with BCVA and MA development were quantified at month 12/24.

Results
Differences in feature volume changes by treatment regimens and MNV subtypes were observed. Each additional 100 nanolitre unit (AHNU) of residual ICF, SHRM and CFRV at month 1 in the fovea was associated with deficits of 10.3, 7.3 and 12.2 letters at month 12. Baseline AHNUs of ICF, CFRV and PED were associated with increased odds of MA development at month 12 by 10%, 4% and 3%. While that of SRF was associated with a decrease in odds of 5%. Associations at month 24 were similar to those at month 12.

Conclusion
Eyes with different MNV subtypes showed distinct trajectories of feature volume response to treatment. Higher baseline volumes of ICF or PED and lower baseline volume of SRF were associated with higher likelihoods of MA development over 24 months. Residual intraretinal fluid, including ICF and CFRV, along with SHRM were predictors of poor visual outcomes.
Visualising the strength development of FICP-treated sand using impedance spectroscopy
Authors: Ahmad Jamal , Khan Mohammad Arsalan , Ahmad Shakeel , Alkahtani Meshel Q. , Mursaleen Mohammad , Islam Saiful 
Published: October 2024

AbstractFungal Induced Calcium Carbonate Precipitation (FICP) is a novel method used in geotechnical engineering that enhances the engineering properties of sand by using the potential of fungal activity. This research is the first attempt to monitor the strength of FICP treated sand using embedded Piezoelectric (PZT) patch based Electromechanical Impedance (EMI) spectroscopy. In the past, the strength of such treated sand has been determined through the destructive methods like Unconfined Compressive Strength (UCS) test. In this study, the sand is mixed with the filamentous fungus Aspergillus Niger and the cementation solution (urea and $$\:{\text{C}\text{a}\text{C}\text{l}}_{2}$$ in the ratio of 1:1) is injected after every 24 h. Results recorded from the cost-effective EVAL AD5933 chip indicate that the shifting of frequency impedance signals in each phase is in good alignment with UCS and calcium carbonate content (CCC). Following the 28-day treatment period, the treated sand achieves a maximum UCS of 3.93 MPa, accompanied by a CCC of 15.19%. In order to correlate EMI signals with treatment cycles, UCS, and CCC, various multi linear regression (MLR) equations for statistical metrics like root mean square deviation (RMSD), mean absolute percentage deviation (MAPD), and correlation coefficient deviation (CCD) are developed. Additionally, Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray (EDX) analyses have been conducted to observe the success of the FICP process in the sand.
Current-controlled periodic double-polarity reversals in a spin-torque vortex oscillator
Authors: Chopin Chloé , de Wergifosse Simon , Moureaux Anatole , Abreu Araujo Flavio 
Published: October 2024

AbstractMicromagnetic simulations are used to study a spin-torque vortex oscillator excited by an out-of-plane dc current. The vortex core gyration amplitude is confined between two orbits due to periodical vortex core polarity reversals. The upper limit corresponds to the orbit where the vortex core reaches its critical velocity triggering the first polarity reversal which is immediately followed by a second one. After this double polarity reversal, the vortex core is on a smaller orbit that defines the lower limit of the vortex core gyration amplitude. This double reversal process is a periodic phenomenon and its frequency, as well as the upper and lower limit of the vortex core gyration, is controlled by the input current density while the vortex chirality determines the apparition of this confinement regime. In this non-linear regime, the vortex core never reaches a stable orbit and thus, it can be of interest for neuromorphic application as a leaky integrate-and-fire neuron for example.
High order Fano resonance in the time domain for a freezing water microdroplet
Authors: Minin Igor V. , Minin Oleg V. , Zhou Song , Luk’yanchuk Boris S. 
Published: October 2024

AbstractFog is a collection of micro drops of water suspended in the air, formed as a result of cooling of moist air. In supercooled air, water droplets freeze, forming ice fog at air temperatures below − 10–15° C. As the ice drop freezes, it forms a core-shell structure. In such a particle, a high-Q Fano resonance is possible, which entails the formation of a magnetic pulse. Our theoretical calculations have predicted the time-dependent formation of Fano resonances in a freezing the outside in water droplet. Time-varying unconventional Fano resonance with magnetic field enhancement yield new method to manipulate light–matter interactions in a freezing water droplet. To the best of our knowledge this mechanism was not discussed previously.
Exploring online public survey lifestyle datasets with statistical analysis, machine learning and semantic ontology
Authors: Chatterjee Ayan , Riegler Michael A. , Johnson Miriam Sinkerud , Das Jishnu , Pahari Nibedita , Ramachandra Raghavendra , Ghosh Bikramaditya , Saha Arpan , Bajpai Ram 
Published: October 2024

Abstract
Lifestyle diseases significantly contribute to the global health burden, with lifestyle factors playing a crucial role in the development of depression. The COVID-19 pandemic has intensified many determinants of depression. This study aimed to identify lifestyle and demographic factors associated with depression symptoms among Indians during the pandemic, focusing on a sample from Kolkata, India. An online public survey was conducted, gathering data from 1,834 participants (with 1,767 retained post-cleaning) over three months via social media and email. The survey consisted of 44 questions and was distributed anonymously to ensure privacy. Data were analyzed using statistical methods and machine learning, with principal component analysis (PCA) and analysis of variance (ANOVA) employed for feature selection. K-means clustering divided the pre-processed dataset into five clusters, and a support vector machine (SVM) with a linear kernel achieved 96% accuracy in a multi-class classification problem. The Local Interpretable Model-agnostic Explanations (LIME) algorithm provided local explanations for the SVM model predictions. Additionally, an OWL (web ontology language) ontology facilitated the semantic representation and reasoning of the survey data. The study highlighted a pipeline for collecting, analyzing, and representing data from online public surveys during the pandemic. The identified factors were correlated with depressive symptoms, illustrating the significant influence of lifestyle and demographic variables on mental health. The online survey method proved advantageous for data collection, visualization, and cost-effectiveness while maintaining anonymity and reducing bias. Challenges included reaching the target population, addressing language barriers, ensuring digital literacy, and mitigating dishonest responses and sampling errors. In conclusion, lifestyle and demographic factors significantly impact depression during the COVID-19 pandemic. The study’s methodology offers valuable insights into addressing mental health challenges through scalable online surveys, aiding in the understanding and mitigation of depression risk factors.
The risk of energy hardship increases with extreme heat and cold in Australia
Authors: Li Ang , Toll Mathew , Bentley Rebecca 
Published: October 2024

AbstractClimate change is shifting the experience of energy hardship. Here we examine the effect of the intensity, frequency, and duration of temperature extremes on energy hardship, and how this risk is shaped by individual, housing and neighbourhood resiliencies across Australia, using nationally representative data (269,500 observations) on energy hardship linked to temperature records between 2005 and 2021. Findings suggest that the risk of energy hardship increases with more intense extreme heat and cold, with greater risks for older individuals, lone-person or single-parent households, and rental tenants. These vulnerabilities can be offset by quality housing and renewable energy installations. Energy hardship risks under moderate and high emissions global warming scenarios are projected to increase by 0.1%−2.6% and 0.6%−3.3% respectively in the long run. Energy hardship will remain a concern despite raising temperatures, especially for colder regions less prepared for heat and populations with individual vulnerabilities and lacking housing and neighbourhood adaptations.
Enhanced stochastic coding framework for discriminating faults and cyber incidents in hybrid systems
Authors: Badr Mustafa , Talebi Heidar Ali , Khosravi Mohammad A. 
Published: October 2024

AbstractThis article presents an innovative approach for distinguishing replay attacks from faults in hybrid systems. To develop the idea at first, a novel technique for replay attack detection, which differentiates it from typical system faults, is introduced. This is achieved through a tactical combination of stochastic coding and a window‐based comparison mechanism, setting a new standard in hybrid system security. In the realm of fault detection, robust L2‐L∞ adaptive observers are employed for precise mode detection, allowing for an accurate assessment of the system's operational state. Additionally, robust H∞ Sliding Mode Observers are utilized to identify abnormal behaviours in the system's output, further solidifying the fault detection capabilities. A significant enhancement in the proposed approach is the integration of a Luenberger observer with the Butterworth low‐pass filter. This novel addition not only refines the filtering process but also contributes to the overall reliability and accuracy of the system. The efficiency and versatility of these methods are demonstrated through their application to a four‐tank hybrid system. This practical simulation showcases the adaptability of the approach to real‐world scenarios, highlighting its potential in diverse applications within the field of hybrid systems.