bluuebunny/crossref_metadata_2025_split huggingface dataset:
Space invaders: dominant and emergent regulatory actors in the case of World Aquatics and the International Swimming League
Authors: Greenhow Annette , Adair Daryl , Kihl Lisa A. , Gowthorp Lisa 
Published: July 2024

AbstractThis article examines the regulatory space occupied by principal actors in elite sport, with a particular interest in how dominant actors in sports governance respond to the emergence of third-party competitions or ‘breakaway’ leagues. Applying a regulatory lens, the article identifies actors who, by virtue of their role and position, have long assumed or claimed legitimacy and authority in the running of a sport. In pursing that line of inquiry, the article focuses on the role of dominant actors assuming the constitutional right of prior approval in sanctioning and authorising qualifying events, along with penalties for athletes who participate in breakaway leagues. These controls in elite level swimming present a salient case where the sport has long been ruled by a singular actor, World Aquatics (WA), formerly known as Fédération Internationale De Natation. In recent years, WA’s dominant position has been interrupted by the rise of an emergent actor, the International Swimming League (ISL), which presented opportunities for either regulatory accommodation or disruption. In pursuing that scenario, the article draws on Hancher and Moran’s regulatory space metaphor (1989), which theorises the attributes of dominant actors occupying regulatory spaces. Concurrently, the article draws upon Arts’ Three Faces of Power concept (2003) to interpret the values, behaviours, and characteristics of various types of regulatory actors. By exploring the key characteristics of regulatory actors in the WA-ISL relational context, this article contributes to our understanding of organisational legitimacy and the regulatory power of dominant and emergent actors in global sport’s regulatory space.
Canonical metrics in complex geometry
Authors: Fino Anna 
Published: July 2024

AbstractA Hermitian metric on a complex manifold is said to be pluriclosed or SKT if the torsion of the associated Bismut connection is closed, and it is called balanced if its fundamental form is co-closed. In the paper we give an overview of recent results on pluriclosed and balanced metrics, provide new constructions of compact non-Kähler manifolds and also present a few open problems.
Profits, Innovation, Investment. Exploring the Virtuous Circle
Authors: Simone Giuseppe , Evangelista Rinaldo , Pianta Mario 
Published: July 2024

AbstractThe article explores the dynamic relationships between profits, product innovation and capital investments. A virtuous circle model is proposed where product innovation and investment are the key drivers of profits, which in turn support technological change and capital accumulation. In our model industries are characterised by two different trajectories for innovation and investments—either ‘embodied’ in machinery and equipment, aiming at cost competitiveness, or knowledge-related and aiming at technological competitiveness. The model is empirically tested on 40 manufacturing and service industries in six major European countries. The empirical analysis confirms that product innovations and capital investments are distinct drivers of profit growth. A virtuous circle between profit, innovation and investment is mainly found in the industries characterised by strategies of technological competitiveness.
Investigation on the adjusting compression ratio and injection timing for a DI diesel engine fueled with policy-recommended B20 fuel
Authors: Dash Santosh Kumar , Dash Dharmeswar , Das Pritam Kumar , Barik Debabrata , Dash Kshirod Kumar , Chandran Sreejesh S. R. , Dennison Milon Selvam 
Published: July 2024

AbstractIn this investigation, Jatropha methyl ester (JME) [JME 20% (volume) + diesel 80% (volume)] was used to adjust the engine’s compression ratio (CR 16, 17, 17.5, and 18) and fuel injection (IT) in the range of 21–25 deg. crank angle (CA) in steps of 2 deg. before top dead center (BTDC), to identify emission profiles of the engine, where the standard CR and IT were 17.5 and 23 deg. CA BTDC. The results reveal that the CO and UHC were obtained to be as low as 0.03% vol at 75% load, CR18, and IT25, and 5 ppm at full load, CR18, and IT25 respectively. The NOx emission rallied from as low as 47 ppm at no load to as high as 1179 ppm at full load, IT of 25, and CR of 18. Whereas the NOx for diesel was 1108 ppm at full load with standard engine operation. The smoke was about 22.1% with CR18 and IT25 for JME20. However, at standard CR and IT for JME20, the smoke was 34.6%. Elevated CR of 18 and advanced IT of 25 are superior to other conditions, hence it is recommended for JME20-powered engines.
Strain characteristics of reinforced soft clay around tunnel under metro loads
Authors: Lin Zhongcai , Yan Chunling , Sang Biaowei , Tang Yiqun 
Published: July 2024

AbstractThis study investigates the Strain characteristics of reinforced soft clay surrounding a tunnel subjected to cyclic loading, employing the Global Digital Systems cyclic triaxial test on the saturated reinforced clay near Shanghai Metro Line 4’s Hailun Road station. Initially, the study examines the impacts of frequency, dynamic stress amplitude (DSA), and loading cycles on cumulative plastic strain. Following this, the orthogonal design method was employed to organize tests, and an evaluation method for assessing soil strain was developed through mathematical statistical analysis. The results indicate at the constant vibration frequency, cumulative plastic strain increases with an increase in DSA and decreases with as load frequency increases. DSA is the primary factor influencing the axial deformation of subway tunnels, whereas the interaction between load frequency and vibration frequency is negligible. The findings suggest that measures to prevent and control subway tunnel settlement should concentrate on DSA during the early stages of subway operation.
Social Media Profiling for Political Affiliation Detection
Authors: Khan Ihsan Ullah , Khan Muhammad U. S. 
Published: July 2024

AbstractThe notion of discerning political affiliations from users’ social media behavior instills a sense of unease in many. Democracy necessitates that individuals’ political affiliations remain private, and social media challenges this foundational principle of democracy. This study uses BERT, a pre-trained language model to analyze X’s (formally Twitter) users and their political affiliations to understand that how much it is easy now to find the political affiliation of people. We collect posts in both English and Urdu languages from different political leaders and their followers, which are used to fine-tune the BERT model. The model classifies the users’ profiles into Pro, Neutral, or Anti-government classes. To assess the performance of the proposed method, experiments are conducted to evaluate its accuracy, efficiency, and effectiveness. The findings of this study confirm the hypothesis that it is easy to detect the political affiliation of individuals using social media with high accuracy (69% for English and 94% for Urdu language) and it can undermine democracy.
The implications of biomass and carbon sequestration of exclosure for climate change mitigation in arid areas, Sekota district, northern Ethiopia
Authors: Eshetie Mubarek , Gobezie Tsegaye , Muhie Seid , Abebe Getu 
Published: July 2024

AbstractClimate dynamics management plays a crucial role in safeguarding the environment from a global to local scale. Land degradation poses a significant threat to the livelihoods of millions of people living in drylands. Arid regions are particularly vulnerable when it comes to finding suitable habitats for ecological processes. Various global initiatives have been developed to restore degraded drylands. In addition, exclosures have important implications in arid areas for regulating environmental services. However, there is a lack of systematic studies on the biomass improvement and climate change mitigation effects of exclosures. A study was carried out in the Sekota district of northern Ethiopia to evaluate the impact of exclosures on biomass production and carbon stock. Three sites—Gateno, Jinqaba, and Mildam—were chosen for the pilot study. Data was collected from 27 quadrats, with different sizes used for sampling saplings, seedlings, litter, and soil. Soil samples were taken at depths of 0–20 cm and 0–40 cm. The data was analyzed using Excel and R Studio, and a linear mixed-effect model was used to determine the differences between land uses. The results indicated significant variations in above-ground biomass carbon, soil organic carbon, and total carbon stock between the two land uses. Furthermore, the observational perspective of exclosures in the Sekota district reveals a sustainable and suitable environment for interested parties. Exclosures prove to be effective in the restoration of degraded lands, as well as in enhancing biomass accumulation and carbon sequestration.
Impact of credit use on crop productivity and gross income of smallholder farmers: a propensity score matching approach
Authors: Lelisho Aregash Esayas , Lelisho Mesfin Esayas 
Published: July 2024

Abstract
Background
Agriculture is Ethiopia’s principal economic activity, employing the vast majority of the population, however, smallholder farmers in the country face long-standing challenges, including low levels of production, low income, and less credit use. This study aimed to analyze the impact of access to credit on crop productivity and income among small-scale farmers in the study area.

Methods
We conducted a cross-sectional study from January 1st to 30th, 2022. Primary data were collected from purposely selected seven (7) kebele of the district based on potential users of agricultural credit. Then the impact was investigated by applying the propensity score matching technique. A Probit regression model was used to determine factors associated with credit use. The significance of the variables was decided at a 5% level of significance.

Results
In our study, a total sample of 347 smallholder farmers were randomly selected, out of which 42.9% were credit-users while 59.1% were non-users. Regarding sources of credit use, Vision Fund was the most commonly used source of credit with 67.8% of users, followed by the Omo Microfinance institution with 22.1%. Sex of the farmer, age of the farmer, existence collateral, farm size, attitude towards risk, extension service, membership in credit institutions, road access, and number of total livestock units in tropical livestock units (TLU) had significant effects on credit use at a 5% level of significance. Moreover, the estimates showed that utilizing credit resulted in a rise in crop productivity in current market value and total yearly income by 19,302.44 and 18,009.63 respectively.

Conclusion
Our study suggested that credit use had a considerable impact on crop productivity and total annual income. As a result, the study recommended that the government’s rural finance policy agenda should prioritize opening different branches near farmers, improving credit usability, and providing more training programs to smallholder farmers to improve their skills and help reduce the problems that impede their use of agricultural credit.
Potentially Toxic Elements (PTEs) Distribution in Drainage Canal Sediments of a Low‐Lying Coastal Area
Authors: Giambastiani B. M. S. , Greggio N. , Carloni G. , Molducci M. , Antonellini M. 
Published: July 2024

AbstractThis study examines the accumulation, distribution, and mobility of Potentially Toxic Elements (PTEs) in the sediments of a low‐lying coastal drainage network (Ravenna, Italy). The aim is to understand the geochemical processes occurring between drainage water and canal bed sediments and assess factors affecting and driving PTE distribution and enrichment in these environments. A geochemical database resulting from the analysis of 203 drainage sediment samples was analyzed using Principal Component Analysis and compared to undisturbed near‐surface sediment samples from the same depth and depositional environment. The results reveal PTEs exceeding national regulation limits. Distance from the sea, electrical conductivity of drainage water, and fertilizer use were identified as the main driving factors. The primary mechanisms for PTE precipitation (As, Co, Mo) and subsequent enrichment in the sediments is attributed to the absorption on Fe‐ and Mn‐oxyhydroxides (HFO and HMO), particularly in high salinity areas near the coast. While Cu, Zn, Pb, Cr, and V also have affinity for HFO and HMO, their adsorption efficiency decreases due to the competition with salt‐derived cations during ongoing salinization processes. Anthropogenic sources, including agriculture, hunting activities, traffic dust, and railways, contribute to the local abundance of other elements (Cr, Ni, Cu, Zn, Pb, and Sn). This paper's significant progress lies in assessing the concurrent interactions of chemical and physical processes that drive PTE distribution and accumulation in reclaimed low‐lying coastal plains. The findings are significant for assessing PTE accumulation risks and sediment toxicity in coastal areas affected by water salinization, drainage, and subsidence, providing valuable information to water management institutions globally.
A Machine Learning Framework to Evaluate Vegetation Modeling in Earth System Models
Authors: Swaminathan Ranjini , Quaife Tristan , Allan Richard 
Published: July 2024

AbstractVegetation gross primary productivity (GPP) is the single largest carbon flux of the terrestrial biosphere which, in turn, is responsible for sequestering 25%–30% of anthropogenic carbon dioxide emissions. The ability to model GPP is therefore critical for calculating carbon budgets as well as understanding climate feedbacks. Earth system models (ESMs) have the capability to simulate GPP but vary greatly in their individual estimates, resulting in large uncertainties. We describe a machine learning (ML) approach to investigate two key factors responsible for differences in simulated GPP quantities from ESMs: the relative importance of different atmospheric drivers and differences in the representation of land surface processes. We describe the different steps in the development of our interpretable ML framework including the choice of algorithms, parameter tuning, training and evaluation. Our results show that ESMs largely agree on the physical climate drivers responsible for GPP as seen in the literature, for instance drought variables in the Mediterranean region or radiation and temperature in the Arctic region. However differences do exist since models don't necessarily agree on which individual variable is most relevant for GPP. We also explore a distance measure to attribute GPP differences to climate influences versus process differences and provide examples for where our methods work (South Asia, Mediterranean) and where they are inconclusive (Eastern North America).
A Numerical Consideration on the Correlation Between Magnitude of Earthquakes and Current Intensity Causing ULF Electromagnetic Wave Emission
Authors: Kimura Ryota , Ando Yoshiaki , Kukiyama Leo , Masuzawa Tomoya , Hattori Katsumi , Hayakawa Masashi 
Published: July 2024

AbstractNumerous studies have reported anomalous ultralow frequency (ULF) electromagnetic fields preceding earthquakes. In this paper, we estimate the current intensity responsible for generating the earthquake‐related ULF fields under the assumption that the origin is a current flowing at the hypocenter and that it has the same frequency dependence for all cases. To estimate current intensity, we perform ULF electromagnetic field simulations with an absorbing boundary condition developed in this study, taking into account the conductivity distribution of the Earth's crust. We analyze 11 earthquakes, including those that occurred in Loma Prieta, Spitak, Guam, Biak, Kagoshima, Iwateken Nairiku Hokubu, Izu swarm, Jammu and Kashmir, Alum Rock, Wenchuan, and L’Aquila. Our results show that, for nine out of the 11 events, there is a positive correlation between current intensity and earthquake magnitude, suggesting that the measured ULF fields originate from seismic activity and supporting our assumptions.
Bank Retreat Mechanisms Driven by Debris Flow Surges: A Parameterized Model Based on the Results of Physical Experiments
Authors: Wang Xi'an , Chen Jiangang , Chen Xiaoqing , Chen Huayong , Zhao Wanyu , Ruan Hechun , Wang Jinshui 
Published: July 2024

AbstractLateral erosion is a critical factor that influences the formation and amplification of debris flows. However, our understanding of the bank retreat process in debris flow channels is limited, which limits the evaluation of debris flow magnitudes and the prediction of their activity trends. Herein, we conduct physical experiments to investigate bank retreat mechanisms using five types of bank soil and multiple debris flow surges. The bank retreat process is categorized into two stages: toe cutting and bank collapse. Toe cutting is mainly caused by hydraulic erosion, bank collapse includes gravity erosion in the form of toppling failure. Notably, the bank retreat process exhibits a significant negative feedback loop. Bank erosion widens the channel bed, subsequently decreasing the flow depth. In turn, this reduction in flow depth mitigates bank erosion. Moreover, we discover a concise pattern in the complex coupling of hydraulic erosion and toppling failure: erosion efficiency is linearly and negatively correlated with the bed widening width. We develop a new parameterized model for describing the bank retreat process and provided empirical values for the model parameters. Furthermore, we observe that the initial erosion efficiency first increases and then decreases with an increase in the fine particle content of the bank soil. Additionally, we report a negative correlation between the maximum bed widening width and the fine particle content in the bank soil that follows a power function relationship.
Quantifying Earth's Topography: Steeper and Larger Than Projected in Digital Terrain Models
Authors: Voigtländer Anne , Rheinwalt Aljoscha , Tofelde Stefanie 
Published: July 2024

AbstractGrid‐ or pixel‐based models, used across various scientific disciplines from microscopic to planetary scales, contain an unquantified error that bias our interpretation of the data. The error is produced by projecting 3D data onto a 2D grid. For Digital Terrain Models (DTMs) the projection error affects all slope‐dependent topographic metrics, like surface area or slope angle. Due to the proportionality of the error to the cosine of the slope, we can correct for it. We quantify the error and test the correction using synthetic landscapes for which we have analytical solutions of their metrics. Application to real‐world landscapes in California, reveal the systematic underestimation of surface area by up to a third, and mean slope angles by up to 10° in steep topography in current DTMs. Correcting projection errors allow for true estimates of surface areas and slope distributions enabling physics‐based models of surface processes at any spatial scale.
Observational Limitations to the Emergence of Climate Signals
Authors: Rivoire Louis , Linz Marianna , Li Jingyuan 
Published: July 2024

AbstractUsing model projections to study the emergence of observable climate signals presumes omniscient knowledge about the climate system. In reality, observational knowledge suffers from data quality and availability issues, for instance data gaps, changes in instrumentation, issues due to gridding and retrieval algorithms. Overlooking such deficiencies leads to misrepresentations of the time of emergence (ToE). We introduce a new definition of ToE that accounts for observational limitations, and show that significant corrections to the ToE may be necessary to achieve the same statistical confidence as would be afforded by omniscient knowledge. We also show how our method can inform future observational needs and observing systems design.
Flow‐Dependence of Ensemble Spread of Subseasonal Forecasts Explored via North Atlantic‐European Weather Regimes
Authors: Spaeth J. , Rupp P. , Osman M. , Grams C. M. , Birner T. 
Published: July 2024

AbstractAtmospheric prediction at 2–6 weeks lead time (so‐called subseasonal‐to‐seasonal timescales) entails large forecast uncertainty. Here we investigate the flow‐dependence of this uncertainty during Boreal winter. We categorize the large‐scale flow using North Atlantic‐European weather regimes. First, we show that forecast uncertainty of near‐surface geopotential height (Z1000) and temperature (T2m) are strongly sensitive to the prevailing regime. Specifically, forecast uncertainty of Z1000 reduces over northern Europe following Greenland Blocking (enhanced predictability) due to a southward shifting eddy‐driven jet. However, due to strong temperature gradients and variable flow patterns, Greenland blocking is linked to increased forecast uncertainty of T2m over Europe (reduced predictability). Second, we show that forecast uncertainty of weather regimes is modulated via the stratospheric polar vortex. Weak polar vortex states tend to reduce regime‐uncertainty, for example, due to more frequent predicted occurrence of Greenland blocking. These regime changes are associated with increased T2m uncertainty over Europe.
Computationally Efficient Emulation of Spheroidal Elastic Deformation Sources Using Machine Learning Models: A Gaussian‐Process‐Based Approach
Authors: Anderson Kyle R. , Gu Mengyang 
Published: July 2024

AbstractElastic continuum mechanical models are widely used to compute deformations due to pressure changes in buried cavities, such as magma reservoirs. In general, analytical models are fast but can be inaccurate as they do not correctly satisfy boundary conditions for many geometries, while numerical models are slow and may require specialized expertise and software. To overcome these limitations, we trained supervised machine learning emulators (model surrogates) based on parallel partial Gaussian processes which predict the output of a finite element numerical model with high fidelity but >1,000× greater computational efficiency. The emulators are based on generalized nondimensional forms of governing equations for finite non‐dipping spheroidal cavities in elastic halfspaces. Either cavity volume change or uniform pressure change boundary conditions can be specified, and the models predict both surface displacements and cavity (pore) compressibility. Because of their computational efficiency, using the emulators as numerical model surrogates can greatly accelerate data inversion algorithms such as those employing Bayesian Markov chain Monte Carlo sampling. The emulators also permit a comprehensive evaluation of how displacements and cavity compressibility vary with geometry and material properties, revealing the limitations of analytical models. Our open‐source emulator code can be utilized without finite element software, is suitable for a wide range of cavity geometries and depths, includes an estimate of uncertainties associated with emulation, and can be used to train new emulators for different source geometries.