Source Distribution Research Articles

Distribution characteristics, sources and risk assessment of heavy metal(oid)s in road dust from a typical lead-zinc mining area in South China.

Although the construction of green mines has effectively reduced soil pollution issues, dust contaminants continue to pose potential risks to human health and environment. This study investigated the concentrations, sources, and human health risks of metal(oid)s present in road dust across different functional zones of the largest lead-zinc mine in Guangdong Province, China, namely the Fankou lead-zinc mine. First, a systematic collection of 45 dust samples from six functional zones was conducted, focusing on the concentrations of ten heavy metal(oid)s (HMs), including As, Cd, Pb, and Zn etc. The results indicate that mining and smelting activities at the Fankou lead-zinc mine dictate the accumulation and distribution of HMs in the dust across the various functional zones. Except for Mn, Cr, and Thallium (Tl), the concentrations of other HMs significantly exceed the soil background values. These HMs primarily originate from mixed sources, including natural, traffic, and industrial activities. In particular, the presence of As, Cd, Pb, and Zn in the dust resulted in moderate to severe pollution, posing extremely high potential ecological risks. Furthermore, the bioavailable concentrations of HMs in the dust were analyzed using two in vitro gastrointestinal simulation methods: Physiologically Based Extraction Test (PBET) and Simplified Bioaccessibility Extraction Test (SBET), allowing for a further assessment of metal bioavailability and estimation of (non)carcinogenic risk probabilities for humans. The bioaccessible heavy metal contents extracted through SBET and PBET were relatively low, with most samples exhibiting bioaccessibility below 40%. In comparison to the total concentrations of HMs in the dust, the estimated non-carcinogenic risks (HQ and HI) and carcinogenic risks (CR) associated with bioavailability (PBET and SBET) for As, Cd, Cu, Sb, Pb, and Zn were significantly reduced, falling within safe values for both adults and children. However, the carcinogenic risk posed by total As remains a concern for local adults and children, indicating that the potential carcinogenic risk of As should not be overlooked. Therefore, additional protective measures should be considered to reduce resident exposure to dust, particularly in the core production areas of the mining district.

Hydrogeochemical characteristics, source distribution, and health risk of high-fluoride groundwater in Swabi, Pakistan.

This paper evaluated fluoride (F-) pollution in drinking groundwater sources, which causes severe fluorosis and other human health concerns in Swabi, Pakistan. We determined F- concentration, prevalence, enrichment, distribution, and health hazards from water ingestion in Swabi, Pakistan. Therefore, 126 groundwater and 18 surface water samples were collected to analyze F- and other geochemical tracers to understand groundwater enrichment and F- mobilization in aquatic systems. The range and mean values of F- in groundwater were 0.02 to 14.2 and 4.0mg/L, and those in surface water were 1.12-0.8 and 1.4mg/L. Most residents used groundwater for drinking purposes. Thus, groundwater results showed that 72.2% of samples had surpassed the WHO guidelines of F- 1.5mg/L. The fluoride pollution index (FPI) declared that 48.73% of samples showed a higher risk, 41.95% medium risk, and 9.32% lower risk. Mineral phases using PHREEQC interactive software determined mineral saturation revealing the dissolution of host rock minerals and unsaturation showed precipitation of minerals within the aquifer. The principal component analysis multilinear regression (PCA-MLR) model showed a five-factor solution: (a) geogenic processes, (b) mixed geogenic and anthropogenic inputs, (c) geochemical processes, (d) agriculture pollution, and (e) industrial effluents which would release F- in the aquifer. The health hazard due to higher F- revealed that children showed high-risk levels compared to adults in endemic areas. The spatial distribution of F- in drinking groundwater increases towards the northern side and decreases in the south to the southeastern side. Therefore, effective water management techniques would be required to safeguard groundwater resources and secure human health from dental and skeletal fluorosis and other associated problems caused by high F- groundwater with varying fluoride concentrations. This study will help the water management authority to safeguard depleted groundwater for drinking demands.

Application of Graph Theory in the Assessment of the Threat of Illegal Distribution of Nuclear Materials and Radioactive Sources

Utilizing nuclear and other radioactive sources poses a risk of misuse that may impact public safety, security, and safeguards. An architecture for detecting illicit trafficking of radioactive materials needs to be implemented. Threat assessment is part of the development of such architecture. A systematic approach to threat assessment on the illegal trafficking of nuclear and other radioactive materials has been proposed. However, the approach only considers the possibility of illicit trafficking of radioactive materials directly from the utilization sites and not the possibility that the radioactive materials come from another port without getting detected in the ports they transited through. In Indonesia, the utilization of radioactive materials on one island may pose a threat of illicit trafficking through ports in other islands. Because ports, utilization of radioactive materials, and transport of radioactive materials can be modelled using graphs, this study proposes an implementation of graph theory to develop the threat assessment further. This paper presents a model framework that can be developed into an analysis model by adding factors that affect the parameters depending on the needs and the available data. The proposed model framework is expected to be integrable to the existing threat assessment so that it also takes into account the possibility of detection failure during transit in ports, and further threat assessment that is more suitable for Indonesia as an archipelagic state may be conducted. Keywords: nuclear security, graph theory, illicit trafficking, radioactive source.

Performance evaluation of an online monitor based on X-ray fluorescence for detecting elemental concentrations in ambient particulate matter

Abstract. Knowledge of the chemical composition of particulate matter (PM) is essential for understanding its source distribution, identifying potential health impacts of toxic elements, and developing efficient air pollution abatement strategies. Traditional methods for analysing PM composition, such as collection on filter substrates and subsequent offline analysis with, for example, inductively coupled plasma mass spectrometry (ICP-MS), are time-consuming and prone to measurement errors due to multiple preparation steps. Emerging near-real-time techniques based on non-destructive energy dispersive X-ray fluorescence (EDXRF) offer advantages for continuous monitoring and source apportionment. This study characterizes the Horiba PX-375 EDXRF monitor by applying a straightforward performance evaluation including (a) limit of detection (LoD), (b) identification and quantification of uncertainty sources, and (c) investigation and comparison of measurement results from three contrasting sites in Luxembourg (urban, semi-urban, rural). We used multi-element reference materials (ME-RMs) from UC Davis for calibration and performed measurements during spring and summer 2023. The LoDs for toxic elements like Ni, Cu, Zn, and Pb were below 3 ng m−3 at 1 h time resolution. Higher LoDs were observed for lighter elements (e.g. Al, Si, S, K, Ca). Expanded uncertainties ranged between 5 % and 25 % for elemental concentrations above 20 ng m−3 and were maximal for concentrations below 10 ng m−3, reaching 60 %–85 %. Elemental analysis revealed S and mineral elements (Fe, Si, Ca, Al) as dominant contributors to PM10. Although the PM mass contribution of toxic trace elements (e.g. Zn, Cu, As) was generally very low, they were found to be enriched at the urban site Belvaux and the semi-urban site Remich compared to the more rural site Vianden. Our results explained on average 51 %–74 % of the gravimetric PM10 mass at the three sites. The study highlights the suitability and importance of the continuous PX-375 particle monitor for future air quality monitoring and source apportionment studies, particularly under changing emission scenarios and air pollution abatement strategies.

Three-dimensional analytical solution of self-potential from regularly polarized bodies in a layered seafloor model

Abstract. The self-potential (SP) method is a sensitive geophysical technique to locate seafloor polymetallic sulfide deposits. Reasonable SP forward modeling can provide a good foundation for the inversion and interpretation of the measured data. Based on the mirror image theory, we proposed a method to derive the three-dimensional analytical solution of the SP generated by regularly polarized bodies in layered media, which is explained in detail within the context of the models. We discussed the analytical solutions for different types of layered models, considering variations in the number of layers and the distribution of sources. A lab-based oxidation–reduction experiment was conducted to record SP data. These data are used to simulate the SP generated by seafloor massive sulfide (SMS) deposits and validate the previous analytical solution. The result shows that the measured SP data match the analytical solution well, demonstrating the correctness of the proposed method and the corresponding analytical solution. This approach is significant for achieving fast and precise forward modeling and inversion in SMS explorations.

Experimental study on fire characteristics of urban rectangular tunnels based on different slopes

Abstract To explore the combustion pattern and temperature distribution law of urban rectangular tunnels when a fire occurs. Considering the influence of variables such as different firepower, fire source spacing, and tunnel slope, the vertical and horizontal flame combustion patterns and tunnel temperature distribution of double fire sources under different slopes were studied by the indoor model experiment method. The results show that under the same conditions of the fire source spacing ratio μ, when the slope of a rectangular tunnel is between 0% and 3%, the influence of dual flames combustion morphology on tunnel slope is relatively small; When the tunnel slope is 4% to 5%, that has a significant impact on the combustion morphology of dual flames, and the flames are more dispersed and sparse than the tunnel slope is between 0% and 3%. As the tunnel slope increases, a high-temperature zone forms at the top of the tunnel and gradually moves towards the uphill direction of the tunnel, the high-temperature area gradually decreases as the slope increases with the same μ. The research results provide a theoretical basis for the fire protection design standards and fire prevention measures of urban rectangular tunnels.

Source distribution correlation enabled self-attention residual network for effective reconstruction of optical molecular tomography

As a promising preclinical imaging technique, optical molecular tomography (OMT) shows great potential in early detection and diagnosis of tumor diseases. However, its widespread application has been hindered by the limitations of traditional reconstruction methods, specifically the accuracy of optical transmission models and the ill-posed nature of inverse reconstruction. The development of deep learning has offered novel solutions for OMT, enabling efficient reduction of the ill-posed nature in reconstruction. The existing deep learning approaches employ conventional neural networks and objective functions, which retains significant scope for enhancing the accuracy of image reconstruction. In this paper, we propose a source distribution correlation enabled self-attention residual network (DCeSR network) to address the need for accurate OMT reconstruction. The DCeSR network leverages a residual learning strategy and a self-attention mechanism to effectively integrate the deep and shallow features, subsequently extracting highly informative surface measurements to accurately predict the three-dimensional distribution of light sources within tissues. The efficacy of the DCeSR network was validated through training and testing with two distinct numerical simulated datasets, each encompassing both single and dual source configurations. Both qualitative and quantitative analyses demonstrate the superior performance of the DCeSR network in achieving accurate OMT reconstructions.

Role of phase change materials and digital twin technology in thermal energy storage system: A review

The exponential growth in energy consumption and demand, along with the depletion of natural resources, is exerting a catastrophic impact on global ecosystems. Recent advances in research and development have focused on the distribution of renewable energy sources and the reduction of traditional energy usage as strategies to address pressing environmental concerns, such as climate change and global warming. Moreover, there is an urgent need for appropriate technologies that can enhance the thermal performance of buildings, given the rapid increase in global cooling and heating demands. This study examines the role of phase change materials (PCMs) and digital twin (DT) technology in thermal energy storage (TES), drawing on an analysis of 89 research articles sourced from multiple databases and references. The findings demonstrate that TES systems optimized through meticulous selection of PCMs can effectively meet thermal comfort requirements. Integrating DT technology with building systems allows for the analysis of cooling effects and optimization of energy demand through DT models of smart buildings. The present study provides a comprehensive overview of the different PCMs used in cooling applications and explores the implementation of DT technologies within building systems. In addition, practical applications of DT technologies for TES systems are presented, providing insights into their potential for enhancing energy efficiency in building systems.

Feasibility verification of deep-learning based collimator-less imaging system using a voxelated GAGG(Ce) single volume detector: A Monte Carlo simulation

A 4π-field of view deep-learning-based collimator-less imaging system was designed with the Monte Carlo method and performance of the system was studied to verify the feasibility of system. A 4 × 4 × 4 voxelated single-volume GAGG(Ce) system and 57Co, 133Ba, 22Na, and 137Cs point sources at 2000 positions were modeled using Monte-Carlo N-particle transport code version 6 (MCNP6). Two types of the localized energy deposition acquired with a voxelated detector system with and without energy bins, were calculated. The F6 tally was used to provide the entire energy deposited in each voxel and the F8 tally to provide energy spectrum data for each voxel. This system utilized these energy deposition patterns depending on the source type and position to reconstruct the source distribution image. A fully convolutional network which is advantageous for the prediction of image outputs was used to estimate source distribution. The models utilizing energy deposition patterns generated on total energy deposition and energy spectrum data were trained with labels from 30° to 10 degree of full-width half-maximum (FWHM). As a result of training with single and multiple source data, types of isotopes and source locations were discriminated up to 5 sources when using energy spectral data, and the average image similarity between ground truth images and predicted ones were 0.9936 for total energy deposition model and 0.9966 for divided energy bin model. These results showed the feasibility of a collimator-less imaging system based on deep learning method that requires no filtration of any type of interaction.

A distributed and process-based model coupling water-sediment-antibiotic interactions to simulate dynamic source-transport-fate of antibiotics at catchment scale

A lack of hydro-biogeochemical models for catchment-scale antibiotic dynamics limits our mechanistic understanding of the transport and fate of antibiotics. This study addresses this gap by developing a distributed and process-based model that focuses on the complex water-sediment-antibiotic interactions. We applied the model to a typical agricultural catchment and selected tetracyclines (TCs) as the target antibiotics. Parameter sensitivity analysis demonstrated that source distribution, groundwater discharge, and water-soil/sediment partitioning were crucial processes. The multi-site performance evaluation generally proved the model's validity, though some overestimation of riverine concentration dynamics was observed. The grid-based distribution of the annual source inputs of the summation of the four TCs (∑4TCs) highly varied in space (μ = 3494.92 mg·ha−1·yr−1, σ = 4761.20 mg·ha−1·yr−1). About 99 % of the source inputs were retained in soil, with mixing layer as the largest reservoir and degradation as the primary loss pathway. Daily terrestrial discharged loading of ∑4TCs peaked with rainfall events. Surface runoff contributed more than 50 % of the terrestrial load of ∑4TCs in summer, while groundwater discharge dominated in other seasons. These results imply that the catchment-scale TCs dynamics are transport-limited rather than source-limited. Our model offers new insights into the high-resolution sources-transport-fate of antibiotics, aiding in developing strategies to mitigate antibiotic contamination.

Improved fast deconvolution algorithms based on functional beamforming for gas leakage sound source imaging

Fast deconvolution algorithms have high computational efficiency, but they often overlook spatial variations in the point spread function (PSF) and wrap-around errors, resulting in the degradation of sound source imaging performance. Accordingly, this paper proposes two improved fast deconvolution algorithms based on functional beamforming (FB). The proposed algorithms establish a linear equation involving the FB output, sound source distribution, and raised-power spatial shift-invariant PSF, specially with irregular focus grid point. Furthermore, iterative solutions are obtained based on fast Fourier transform, enhancing imaging performance while maintaining computational efficiency. Simulations and experimental results demonstrate that compared to the fast deconvolution algorithms, the proposed algorithms expand the effective imaging area to 36.3°, and the Rényi entropy is reduced by approximately 45 %, which has higher imaging spatial resolution and dynamic range. Finally, the compressed gas leakage source imaging results validate the effectiveness of the proposed algorithms, indicating that they have promising engineering application prospects.

Vertical Distribution, Diurnal Evolution, and Source Region of Formaldehyde During the Warm Season Under Ozone-Polluted and Non-Polluted Conditions in Nanjing, China

Formaldehyde (HCHO), a key volatile organic compound (VOC) in the atmosphere, plays a crucial role in driving photochemical processes. Satellite-based observations of column concentrations of HCHO and other gaseous pollutants (e.g., NO2) have generally been used in previous studies to elucidate the mechanisms behind secondary organic aerosol (SOA) and ozone (O3) formation. This study aimed to investigate the characteristics of HCHO by retrieving its vertical profile over Nanjing during the warm season (May–June 2022) and analyzing the diurnal variation in vertical distribution and potential source regions on non-polluted (MDA8 O3 < 160 μg m−3, NO3P) and O3-polluted (MDA8 O3 ≥ 160 μg m−3, O3P) days. Under both conditions, HCHO was primarily concentrated below 1.5 km altitude, with average vertical profiles displaying similar Boltzmann-like distributions. However, HCHO concentrations on O3P days were 1.2–1.6 times higher than those on non-polluted days at the same altitude below 1.5 km. Maximum HCHO concentrations occurred in the afternoon, while the peak value in the 0.1–0.4 km layers was reached around noon (~11:00 a.m.). The variation rates (VR) of HCHO in the 0.3–1.2 km altitudes had a maximum on O3P days (approximately 0.33 ppbv h−1), and were significantly higher (p < 0.01) than the VR observed on NO3P days (0.14–0.20 ppbv h−1). The analysis of footprints showed that HCHO concentrations were jointly influenced by the upstream region and the surroundings of the study site. The study results improve the understanding of the vertical distribution and potential source regions of HCHO.

Machine learning-based multi-objective optimization of thermo-mechanical field of anisotropic plates

Designing plates is highly challenging due to the complex relationship between material layout and its properties. Traditional experimental, analytical, and computational methods suffer from problems such as long computation time and high cost, limiting their application in predicting and optimizing plates. In this paper, we propose an end-to-end prediction and multi-objective optimization framework integrating machine learning (ML) and non-dominated sorting genetic algorithm (NSGA-II). This framework can have high fidelity and simultaneously predict multiple thermo-mechanical fields of the anisotropic plate-heat source system. It can also perform multi-objective optimization for specific requirements by optimizing the distribution of materials and heat sources. To demonstrate the effectiveness of our approach, the maximum temperature and von Mises stress are considered as objectives, and the framework is applied to two different discrete multi-objective optimization problems, i.e., non-temperature constrained and temperature constrained optimization problem. By integrating ML and optimization algorithm, our framework offers a comprehensive solution for tackling complex optimization problems in the field of anisotropic plate-heat source system.

Determining sources in the bioluminescence tomography problem

Abstract In this paper, we revisit the bioluminescence tomography\,(BLT) problem, where one seeks to reconstruct bioluminescence signals (an internal light source) from external measurements of the Cauchy data. As one kind of optical imaging, the BLT has many merits such as high signal-to-noise ratio, non-destructivity and cost-effectiveness etc., and has potential applications such as cancer diagnosis, drug discovery and development as well as gene therapies and so on. In the literature, BLT is extensively studied based on diffusion approximation (DA) equation, where the distribution of peak sources is to be reconstructed and no solution uniqueness is guaranteed without adequate a priori information. Motivated by the solution uniqueness issue, several theoretical results are explored. The major contributions in this work that are new to the literature are two-fold: first, we show the theoretical uniqueness of the BLT problem where the light sources are in the shape of $C^2$ domains or polyhedral- or corona-shaped; second, we support our results with plenty of problem-orientated numerical experiments.

Internal tides and the inviscid dynamics of an oscillating ellipsoid in a stratified fluid

A boundary integral representation is derived for the translational oscillations of a triaxial ellipsoid in a uniformly stratified fluid. The representation is of single-layer type, a distribution of sources and sinks over the surface of the ellipsoid. The added mass tensor of the ellipsoid is deduced from it and, from this tensor, the impulse response function together with the energy radiated away as internal waves. Horizontal oscillations correspond to the generation of an internal or baroclinic tide by the oscillation of the barotropic tide over ellipsoidal topography at the bottom of the stratified ocean. Such topography is unconditionally supercritical, namely of slope larger than the slope of the wave rays, irrespective of the frequency of oscillation. So far, analytical work on supercritical topographies has been limited, for the most part, to two-dimensional set-ups. Here, for the ellipsoidal seamount, the orientation of the barotropic tide and the anisotropy of the topography have their effects analysed in detail. As the height of the seamount increases, the rate of conversion of barotropic energy into baroclinic form is seen to first increase according to the square law expected for a topography of small slope, then saturate and eventually decrease.

Geolocation of Fixed Emission Sources Produced by Artisan Brick Kilns in the Atmospheric Basin of the City of Juliaca, Peru

Objective: The study objective is to investigate the application of georeferencing systems to identify the geospatial location of fixed sources of atmospheric emissions produced by artisanal brickyards in the air basin of Juliaca city-Peru. Theoretical Framework: Previous studies have shown that artisanal brickyards are a significant source of air pollution in developing urban and on the outskirts. Emissions of fine particles, nitrogen oxides and other pollutants from the burning of traditional fuels, such as firewood and coal contribute to the degradation of air quality and can have adverse effects on human health and the environment. The georeferencing application and geospatial analysis techniques in the atmospheric pollution study have allowed a better understanding of the spatial distribution of emission sources and their impact on the environment. These tools are essential to identify and map the artisanal brickyard locations and to evaluate their contribution to air pollution in urban and on the outskirts. Method: The methodology adopted for this research includes data collection and compilation of existing information; georeferencing of brickyards through the use of geographic information systems (GIS); analysis of geospatial data for the identification of spatial patterns; preparation of thematic and spatial distribution maps; and the interpretation of results. Results and Discussion: The study results highlight the importance of locating the fixed sources of emissions produced by artisanal brick factories in the Juliaca air basin. This precise spatial identification provides a solid basis for the formulation of policies and mitigation strategies aimed at reducing air pollution in the region, in addition to representing fundamental data for the use and exploitation of GIS for environmental protection and modelling, among others. Research Implications: The results can be applied or influence practices in the environmental and forestry engineering field, the ICTs application, modelling and simulation, and territorial planning, among others. Originality/Value: This study contributes to the literature using georeferencing techniques for environmental modelling purposes. The relevance and value of this research are evident in obtaining georeferenced points for the estimation of emission factors for the predictive calculation of volumes, flows and dispersion of pollutants in an air basin.

Noise generation and contribution of a single-gap bridge expansion joint: An experimental and numerical study

Noise generated from bridge expansion joints during vehicle passing has caused localized environmental problems around the world. The purpose of this paper is to investigate the vibration and noise radiation from the single-gap expansion joint induced by passing vehicles. First, a vibration and noise field test was performed for single-gap expansion joints in the highway ramps. Based on the tested results, two numerical models, involving a 3D tire-bridge expansion joint hybrid finite element model for the vibration analysis, as well as an acoustic boundary element model for the prediction of the noise radiation, were established and validated. The results of the numerical simulations and the field tests are well matched, which offers opportunities to predict the vibration and noise induced by vehicles passing through using the proposed methodology. Finally, the acoustic contribution and sound pressure distribution of different sound sources were discussed. The research showed that, for the single-gap expansion joint, the contribution of tire noise to the total noise level is dominant, and the contribution of structure-borne noise of the expansion joint and girder to the total noise level is insignificant. The findings emphasize the importance of tire noise and provide new ideas for noise control of single-gap expansion joints.

Physics-informed and graph neural networks for enhanced inverse analysis

PurposeThis paper presents an original approach for learning models, partially known, of particular interest when performing source identification or structural health monitoring. The proposed procedures employ some amount of knowledge on the system under scrutiny as well as a limited amount of data efficiently assimilated.Design/methodology/approachTwo different formulations are explored. The first, based on the use of informed neural networks, leverages data collected at specific locations and times to determine the unknown source term of a parabolic partial differential equation. The second procedure, more challenging, involves learning the unknown model from a single measured field history, enabling the localization of a region where material properties differ.FindingsBoth procedures assume some kind of sparsity, either in the source distribution or in the region where physical properties differ. This paper proposed two different neural approaches able to learn models in order to perform efficient inverse analyses.Originality/valueTwo original methodologies are explored to identify hidden property that can be recovered with the right usage of data. Both methodologies are based on neural network architecture.

Disparities in Global Authorship and Data Source in the Pediatric Blood and Cancer Journal 2011-2021: Realities and Strategies for Improvement.

Research expands knowledge and improves outcomes. Research is needed in all settings, but most often occurs in high-income countries (HIC) compared to low- and middle-income countries (LMICs). Publication in scientific peer-reviewed journals and authorship position are important for academic/clinical advancement. We explored the current state of global authorship and data source distribution for publications in the Pediatric Blood and Cancer (PBC) journal. LMIC-affiliated author inclusion and position in selected article categories of the PBC (2011-2021) were recorded. Articles with at least one LMIC-affiliated author (first-listed affiliation) and 5% of exclusively HIC-authored articles were verified. Descriptive statistical analysis was performed. Of 4504 articles reviewed, 593 (13%) included at least one LMIC-affiliated author (517/593 [87%] as first author and 488/593 [82%]) as senior author. In a subset of articles with LMIC-sourced data, 148/675 (22%) included exclusively HIC authors. Within the LMIC-sourced data subset, 81/675 (12%) articles were mixed HIC/LMIC affiliation and 446/675 (66%) were exclusively LMIC-affiliated. The frequency of LMIC-affiliated authors as first or senior author within HIC/LMIC-affiliated collaborations was 31/81 (38%) and 9/81 (11%), respectively. As more than 80% of children live in LMICs and the WHO Global Initiative for Childhood Cancer is increasingly engaged across LMICs, all researchers/clinicians must justly be given an opportunity to conduct, write, publish, and be recognized for their research. PBC is uniquely poised to promote equitable publishing practices and opportunities for professional recognition by drawing on emerging best practices for equitable authorship, including potentially restructuring authorship guidelines and requirements.

Metaphorical meaning dynamics: Identifying patterns in the metaphorical evolution of English words using mathematical modeling techniques

Abstract Conceptual metaphor theory has been criticized due to its emphasis on concepts instead of words and its top-down direction of analysis. In response to these criticisms, this paper employs a new strategy, utilizing established mathematical modeling methods to allow a systematic, quantitative analysis of the entire dataset produced by the Mapping Metaphor project at the University of Glasgow. This dataset consists of 9609 words performing 18916 metaphorical mappings between 414 domains. The data is represented as a network consisting of 414 nodes, the domains, connected by shared words. Words are represented by groups of directed mappings between all domains in which they occur. This is made possible by the use of a directed hypergraph representation, a tool commonly used in discrete mathematics and various areas of computer science but not previously applied to the metaphorical meanings of words. Examining the dataset as a whole, rather than focusing on individual words or metaphors, allows global patterns of behavior to emerge from the data without pre-filtering or selection by the authors. Outcomes of the analysis relating to the distributions of source and target domains within the network, the growth mechanisms at work in the spread of metaphorical meanings and how these relate to existing concepts in CMT are discussed.