Stream Model Research Articles

A prediction method of oil recovery for hot water chemical flooding in heavy oil reservoirs: Semi-analytical stream tube model

Abstract Chemical agents (polymer and surfactant) assisted hot water flooding is an effective means of enhancing oil recovery in heterogeneous and heavy oil reservoirs. The rapid prediction of oil recovery through hot water chemical flooding is very important. The stream tube model is a fast analytical method for predicting water flooding recovery, but it is not suitable for hot water chemical flooding. In this paper, a permeability distribution model for multi-stream tubes is established based on permeability variation coefficient using normal distribution function for reservoir heterogeneity, Using GOMPERTZ growth function model to characterize the changes in stream tube temperature, polymer viscosity, and surfactant concentration with injection volume, Using Brooks-Corey model to describe the influence of interfacial tension and temperature on the relative permeability curve. Finally, an analytical stream tube model for hot water chemical flooding of heavy oil reservoirs was established. The time discrete method is used to solve the model, then the graphs of the relationship between oil recovery and water cut are obtained. Compared with numerical simulation methods, the prediction error of oil recovery is less than 2%, and the calculation time is reduced by 89%. This model has been successfully applied to X oilfield. Based on historical fitting, it is predicted that hot water chemical flooding can enhance oil recovery by 6.3% compared to water flooding. This paper provides a fast calculation method for predicting and evaluating the effectiveness of hot water chemical flooding in heavy oil reservoirs.

One stream or two - exploring Andromeda’s North West stream

Abstract We present results of our dynamical stream modelling for the North West Stream in the outer halo of the Andromeda galaxy (M31). Comprising two main segments, the North West Stream was thought to be a single structured arching around M31. However, recent evidence suggests that it is two separate, unrelated, streams. To test this hypothesis we use observational data from 6 fields associated with the upper segment of the North West Stream together with 8 fields and 5 globular clusters associated with the lower segment to constrain model orbits. We fit both segments of the stream using a fixed potential model for M31 and an orbit integrator to compare orbits with the observed streams. We measure the central tracks and predict proper motions for for the upper segment (lower segment) finding ${\mu ^*_{\alpha }}$ = 0.078$^{+0.015}_{-0.012}$ (0.085$^{+0.001}_{-0.002}$) mas/yr and μδ = $-0.05^{+0.008}_{-0.009}$ ($-0.095^{+0.003}_{-0.005}$) mas/yr. Our results support the hypothesis that the dwarf spheroidal galaxy Andromeda XXVII is the progenitor of the upper segment of the North West Stream and that the upper and lower segments do not comprise a single structure. We propose that the upper segment, which appears to be on an infall trajectory with M31, be renamed the “Andromeda XXVII Stream” and the lower segment, also apparently infalling towards M31, retain the name “North West Stream”.

Live streaming channel and product assortment with both national and store brand products

To counteract the fierce competition in the online retailing market, retailers are increasingly adopting live streaming selling model and introducing store brand product to enhance their competitiveness. In this context, we attempt to examine whether and when a retailer should launch a live streaming channel. If launched, we further investigate how the retailer should assort both national and store brand products across available channels. To delve into these questions, we consider a supply chain consisting of a manufacturer and an online retailer, where the retailer resells the manufacturer's national brand product and also sells a store brand product. We examine the retailer's optimal channel strategy and product assortment strategy by considering six scenarios, differentiated by whether introducing the live streaming channel and various product assortment tactics. Our findings indicate that as long as the fixed setup cost of the live channel is relatively low, the retailer will always introduce a live streaming channel. The retailer's optimal assortment of both products across channels highly depends on the consumers’ additional value derived from the live streaming channel and the perceived quality of the store brand product. We also find that, the retailer's optimal channel strategy and product assortment may not always benefit the manufacturer, but there exist conditions that can create win-win situations for both players. Our study further shows that if the retailer launches the live streaming channel at the start, it may not always be necessary to introduce the store brand product under certain conditions.

Redefinition for Fundamental Characteristics of Waterway Traffic Stream Considering Vessel Displacement

As the basis for characterizing traffic conditions in waterways, fundamental characteristics of waterway traffic streams are of great practical significance in ensuring traffic safety and improving navigation efficiency. In the study of the fundamental characteristics of waterway traffic flow, although some scholars consider the length or area of the vessel, few scholars take the displacement of the vessel into account and make light of the influence of the three-dimensional size of the vessel. This paper proposes a method for defining the fundamental characteristics of a waterway traffic stream considering vessel size. This method defines fundamental characteristics in terms of vessel displacement and quantifies flow, density, and speed based on vessel trajectories in time–space regions. This study selects a unidirectional channel in the south trough waters of Shanghai Harbor for a case study and draws the fundamental diagram of the waterway traffic stream while considering vessel number and displacement. The comparison result shows that the definition considering vessel displacement can more accurately reflect the actual traffic condition of the selected channel. Finally, based on the flow–density subgraph of the waterway traffic stream (measured by vessel displacement), this paper constructs a traffic stream model and derives critical parameters. The definition proposed in this study effectively characterizes how vessels occupy the time–space resources of waterways, revealing the inherent mechanisms governing waterway traffic stream and, thus, enhancing accuracy in describing fundamental relationships among waterway stream characteristics. The outcome of this research underlies how the waterway traffic stream is measured, operated, and managed to ensure safety and productivity.

Application of a reaction-based water quality model to the total dissolved solids concentration of the Pasig River.

With the goal to support effective water resource management, water quality models have gained popularity as tools for evaluating the distributions of pollutants and sediments. This work focuses on the application of the numerical solution of an advection-dispersion-reaction (ADR) water quality model for rivers and streams to a major Philippine waterway, the Pasig River. The water quality constituent is described by a system of reaction and advection-dispersion-reaction equations. The model and method are based on a previously used strategy where Guass-Jordan decomposition is applied to the matrix system and the resulting conservative form of the model is solved numerically using the fully implicit scheme and finite element method. The methodology is demonstrated by a case study in Pasig River involving the concentrations of total dissolved solids (TDS) obtained from the Department of Environment and Natural Resources (DENR) through the Pasig River Unified Monitoring Stations (PRUMS) report. Sensitivity analysis and parameter estimation are also applied to the model to assess which parameters influence the model output the most.

Modelling the Contributions of Riparian Vegetation and Topography to Stream Shade Using LiDAR and Conventional Digital Elevation Data

ABSTRACTStream temperature is widely considered the master variable in stream ecosystems. One of the key drivers of diel and seasonal stream temperature variability is the solar radiation received at the stream surface, which can be influenced by shading associated with both larger scale topographic features and riparian vegetation. In this study, a stream shade model was developed that uses LiDAR point cloud data to model shading by riparian vegetation, including canopy overhang, and conventional elevation data to model stream shading by topography. The model was applied to a dominantly north–south oriented river flowing in a floodplain within a mountain valley. When compared with shade interpreted from PlanetScope visual imagery, the model predicted stream shade at the point scale with 92% agreement. Sources of error were attributed to pixel and azimuth band size, which can be refined within the model arguments, although at the cost of increased processing time. The shade model was re‐run after virtually rotating the reach by 90° and 270° clockwise to evaluate the effect of valley orientation. Peak reach‐wide sunlight exposure occurred approximately 2 h later in the day when the stream reach was rotated 90°, and produced greater shading from mid‐morning to mid‐afternoon. Further work should test the model on smaller streams using ground‐based oblique or drone‐based photography to provide ground‐truthing, particularly to assess the accuracy of predicted shade below over‐hanging vegetation.

Quantitative analysis of the fluvial geomorphology and erosion on Hainan island: implications for the source-to-sink system in the NW South China Sea

The sediment delivery from Hainan island into the NW South China Sea during the Quaternary is less well-defined. An investigation into the uplift, exhumation and fluvial geomorphology of the Hainan island is crucial for improving our understanding on the source-to-sink system in this region. In this study, we employed the digital elevation analysis, the stream power incision model and the cosmogenic nuclide isotope analysis to unravel how and why the Hainan island provide sediment to the NW South China Sea. The results show that the average HI values of the main catchments on the Hainan island are below 0.35, which indicates that the rivers on the Hainan island tend to be stable. After mapping the channel steepness index of the Hainan island, a high channel steepness index is constrained in the central and western Hainan island. The χ analysis shows minor variations in χ values across the Hainan island, except of the watershed between the Wanquanhe and Nandujiang rivers, as well as that between the Changhuajiang and Nandujiang rivers, which indicates the potential migration of the river watersheds here. In addition, we carried out the cosmogenic nuclide 10Be analysis on the river sand from the Hainan island. The spatial distribution of 10Be concentrations is identified to be high in the west and low in the east. The catchment-averaged erosion rates are quantified to be 35 m/Myr, 42.5 m/Myr and 69.9 m/Myr for the Changhuajiang, Wanquanhe and Lingshuihe catchments, respectively. We also estimated the sediment deliveries from the Changhuajiang, Wanquanhe and Lingshuihe catchments to the Qiongdongnan and Yinggehai Basins to be 0.46 Mt/yr, 0.45 Mt/yr and 0.21 Mt/yr, respectively. We compared our results of the fluvial geomorphology analysis and erosion rate estimates of the Hainan island with those of the Taiwan island. We concluded that the difference of the erosion pattern and river evolution of the Hainan and Taiwan islands may be associated with the variation of the tectonics. Our investigation on the evolution of the Hainan island will improve our understanding on the source-to-sink systems in the NW South China Sea.

Illicit drug use in Limerick City: A stakeholder and policy analysis using multiple streams model.

The changing drug situation in Ireland has led to the development of various drug policies. This paper aims to use Limerick City as a case study to examine approaches to policy development. The study is qualitative and uses a hybrid technique that combines document, content, and stakeholder analysis. Kingdon's multiple streams model underpins this study. In addition, guidelines for the systematic search for grey literature were adopted as the search strategy. Problem Stream: Illicit drug use and its related problems have changed. The increasing availability of drugs, increasing usage and changes in the types of drugs being used have led to increased drug-related crimes, adverse health outcomes and elevated demand for treatment services. Local drug policies and initiatives emerge by recognising drug-related problems in the region. Policy Stream: The current national drug strategy 2017-2025 which informs action plans in Limerick is the first to focus on a unified health approach. Some national policies have evolved to ensure that guidelines meet current service needs. However, these changes have occurred in some cases with no clear actions. Political Stream: Statutory, voluntary and community stakeholders provide drug addiction and drug addiction-related services, which have evolved rapidly since their first introduction. The Mid-West Regional Drug Task Force was identified as essential in coordinating stakeholders locally. One area for improvement is limited evidence of the voices of persons who take drugs included in service/policy development. This regional analysis also suggests that local implementation of policies concerning dual diagnosis and supervised injection facilities can be further expanded. Despite the challenges experienced by stakeholders in Limerick, a hands-on approach has been adopted in the creation of strategies to tackle the drug problem. The approaches to drug policy development have delivered continuous development of services. However, services remain underdeveloped in areas removed from the capital city of Dublin. Navigating the complex drug landscape reveals that inclusivity, adaptation, and ongoing research are critical components of successful and long-lasting drug policies.

The changing politics of road death in Britain: from policy action to kicking the can down the road

Britain has one of the lowest road casualty rates globally, yet tens of thousands of people are killed or seriously injured annually, and numbers have plateaued since 2012. Despite the consequential impact of road trauma, there has been limited evaluation of Britain's policy response. This paper uses Kingdon's Multiple Streams Model to understand agenda setting and analyses how road safety policies were made or not made over time. Critical discourse analysis evaluates patterns and themes in new data acquired via thirty-five interviews with politicians and policy participants, and data from Parliamentary debates and policy documents, spanning the period between 1987 and 2021. The data suggests two distinct time periods: 1987 to 2002, the policy problem was accepted, policy solutions advanced, when policy windows opened as political discourse was constructive, the multiple streams coupled, and policy change resulted. Policy development in road safety is therefore possible when it is viewed as an important policy agenda in need of attention. After 2003, there was a perception the problem had been resolved. Road safety lost out to a dominant mobility framing, road deaths were reframed as accidental and so unavoidable, solutions were contested, the politics stream flowed slowly, and from 2011, with the tight fiscal environment, discarded targets, and significant competition for attention from alternative policy areas, policy stasis resulted. The prevailing politics meant that the policy problem remained sidelined and policy solutions continued to be kicked down the road. The paper explores how this shift occurred and the consequences on the politics of road death.

Dynamic modeling and online monitoring of tensor data streams with application to passenger flow surveillance

Dynamic modeling and online monitoring of tensor data streams with application to passenger flow surveillance

When Does the Concavity Index Constrain Stream Power Parameters?

AbstractBy defining the attributes of river networks, we can quantitatively extract records of climatic and tectonic changes from them. The stream power incision model (SPIM) provides a framework within which this can be achieved, as it facilitates the calculation of the relative rock uplift from river characteristics. One parameter that has been widely employed in tectonic and fluvial geomorphology is the channel steepness index, a metric that can represent the normalized rock uplift rate experienced by a river. However, to accurately infer the channel steepness index, we must accurately estimate m/n, the ratio between the two positive exponents of the SPIM. Present methodologies to constrain m/n rely on an assumption that rock uplift and erodibility are spatially invariant. These conditions are rarely present on Earth. In this study, we use a synthetic example and examples from the Siwalik Hills and Olympic Mountains to demonstrate how existing methodologies to constrain m/n produce systematic errors when there is spatial variation, and particularly spatial gradients, in the processes driving landscape evolution. To solve this problem, we present a methodology to estimate m/n based on a large river network inversion that accounts for spatial variation in landscapes. After demonstrating that the methodology can accurately recover m/n in our synthetic landscape, we show that our methodology can reconcile contrasting observations in the Siwaliks, and is critical to inferring accurate values of channel steepness index in the Olympic Mountains. This highlights the utility of large topographic inversions for investigating landscape dynamics.

P2P credit risk management with KG-GNN: a knowledge graph and graph neural network-based approach

Credit risk management is crucial for the credit loan decision-making process on P2P platforms, essential for mitigating credit defaults. The rapid decline of China’s P2P platform market highlights the urgent need for Internet financial institutions to enhance their credit risk management strategies. Previous studies have applied machine learning to assess credit risk; however, their effectiveness is often hampered by a lack of consideration for semantic information and individual correlation. In response, we propose an innovative approach, KG-GNN, which integrates knowledge graph (KG) and graph neural network (GNN). KG-GNN leverages KG to encapsulate semantic information within complex categorical features and explore potential relationships between borrowers. Utilizing GNN, our framework extracts representation features from the KG to build comprehensive and accurate credit risk models. Our findings indicate that KG-GNN not only can predict credit risk more accurately than conventional machine learning models but also improves the stream model performance by over 20% through KG and GNN-based data augmentation techniques. By integrating KG with GNN, our approach enriches the methodologies for credit risk management and can be adapted to other data mining challenges that require processing complex semantic and relational information, thereby enhancing model learning capabilities.

Deep learning based fine-grained recognition technology for basketball movements

The technical essentials of basketball are very complex, in order to accomplish the identification of fine-grained basketball movements and improve the quality of basketball training, the study innovatively proposes a region screening strategy to obtain the local region information of image frames, and draws on the SlowFast network structure to design the static and dynamic detail models, and finally utilizes the 3D attention feature fusion module to complete the multi-feature relationship processing and recognition. Performance testing experiments have confirmed that the dual stream model based on region filtering has achieved a maximum improvement in average accuracy of 16.35 % and 60.36 % in the recognition of RGB images, preserving relatively complete local effective region information of RGB images. The model based on channel domain attention mechanism improves its average accuracy to over 60 %. The model recognition accuracy calculation time after dual stream fusion is reduced by about 50 %. The model based on 3D attention feature fusion module exhibits stronger robustness when the feature dimension changes. And the loss value of this model rapidly decreases and converges to the minimum loss value, with its accuracy and recall reaching 90.03 % and 88.47 % respectively, and its AUC value reaching a maximum of 0.761. The design of the study contributes to the digital development of teaching and training in basketball and enriches the theoretical body of knowledge on deep learning and action recognition.

Redefining STEAM to STEAM ∀H (STEAM for All Humanity) in Higher Education

This article presents the revision of the STEAM model originally proposed by Yakman, in 2008, introducing the Human variable, as an extremely important element for the model, which was defined as STEAM ∀H, where ∀H is for all Humanity. This proposal is motivated by several factors. On the one hand, the evolution of industrial design from the 19th century to present, going from designing objects focused on facilitating industrialization and focused on the user, to design focused on the human being and humanity. On the other hand, since the formulation of the STEAM model, different improvements have been proposed in the literature in order to introduce humanistic disciplines into the model, also seeking to introduce society as a fundamental element. For example, the literature has proposed the STREAM model, where R is religion, or STEAM-ED, where -ED implies an approach based on the constructivist social theory. The STEAMS model, where S is Society, has also been proposed to try to improve training in understanding society and the implications of designing for it. Initially Yakman introduces the “A” in the STEM model as the sum of different disciplines that use the word “art” in their description: Fine Arts, Physical Arts, Manual Arts and Liberal Arts. The first three disciplines are associated with the practical and also creative part, while the Liberal Arts approach various disciplines in the humanities and social areas. Yakman’s definition of STEAM was quickly accepted and assimilated by the scientific community. However, for the purposes of application, the “A” is treated fundamentally as that creative and artistic component transversal to the rest of the model, relegating humanistic and social learning to the background. In the first section of this article the redefinition of the “A” in the STEAM model is proposed, which was originally defined by Yakman, by integrating the areas of Fine Arts, Physical Arts and Manual Arts; adding ∀H, as STEAM ∀H, which integrates the Liberal Arts, defining the model as: “the learning of Science and Technology interpreted through Engineering and Art based on the language of Mathematics and taking into account the implications of Science, Technology, Engineering, Art and Math’ for all Humanity” The second section of this article proposes the implementation in detail of the STEAM ∀H model in higher education, specifically, in the first year of the Degree in Industrial Design Engineering and Product Development, where the STEAM areas represented by the subjects of Physics, Mathematics, Basic Design, Representation of Shapes, etc., must be integrated with the subject of Social Doctrine of the Church. The model has been tested in three consecutive courses. An empirical qualitative study, case study method was carried out thorugh multiple-question Likert scale questionnaries to analize the perpective and perception of the participants to the new method. The frequency of the results obtained are shown and analized at the end of the article.

Using Shunt Capacitors to Mitigate the Effects of Increasing Renewable Energy Penetration

Over the past two decades, Renewable Energy Sources (RESs) have gained global popularity. Control issues are becoming more difficult as the system inertia decreases due to the absence of typical synchronous generators. Innovative methods like fault current limiters, energy storage devices, and alternative control systems are utilized to deal with these difficulties. This study provides a summary of the challenges associated with incorporating high-level RESs into the existing grid. The increased penetration of the RESs has a negative impact on the system oscillations and harmonics, generating the need for power quality improvement techniques, such as adaptive control, adding energy systems, power stream assessment, or weight stream examination. This paper presents a framework of the power stream issue, its arrangement as well as different game plan methods. The power stream model of a power structure can be built using the significant association, weight, and age data.

Anomaly detection of power grid data based on storm cloud platform sliding window

Abstract To realize the monitoring and diagnosis of multi-source data in the power industry and meet the real-time processing requirements of the power system, the storm-distributed real-time computing platform is introduced to process the data. On this platform, the streaming data processing model based on a sliding window is deployed to realize the anomaly diagnosis of data flow. By calculating the predicted value of a point and the confidence interval of the predicted value of the point, we can judge whether the actual point is an abnormal value. By testing the data processing capacity of a cluster and a single machine, the experiment shows that in the cluster environment, reasonably setting the component parallelism can improve the throughput of flow computing.

Utilizing Silhouette and Head Information for Improved Cloth-changing Person Re-Identification

In recent years, significant progress has been made in person re-identification (ReID). However, as the time span increases, the phenomenon of changing clothes often occur, and the performance of methods based on person re-identification may decrease in this case. In this article, we focus on solving the problem of cloth-changing person re-identification from a single RGB image, which is more challenging, and improving the accuracy and robustness of traditional methods for recognition. We propose a cloth-changing Feature Regularization learning framework by fusing Silhouette and Head information (SHFR), a two-stream framework which transfers the silhouette information and head information learned by auxiliary stream to the main stream and supplements features unrelated to clothing. Specifically, the main stream approach we adopt is the traditional cloth-changing person re-identification network. In the auxiliary stream, we use the DeepLabV3 semantic segmentation model to extract person silhouette features, and the FCHD fully convolutional head detection model to extract head information with advanced semantic information. We concatenate the head information and background information into the silhouette as input for BackBone to continue training the network. In order to utilize silhouette information and head information, we regularize the cloth-changing features on both main stream and auxiliary stream, allowing main stream model to pay more attention to features unrelated to clothing and improve the accuracy of model recognition. We conduct extensive experiments on our model on the PRCC dataset, and the results show that our method has highly competitive performance.

A prospective multi-center study quantifying visual inattention in delirium using generative models of the visual processing stream

The visual attentional deficits in delirium are poorly characterized. Studies have highlighted neuro-anatomical abnormalities in the visual processing stream but fail at quantifying these abnormalities at a functional level. To identify these deficits, we undertook a multi-center eye-tracking study where we recorded 210 sessions from 42 patients using a novel eye-tracking system that was made specifically for free-viewing in the (ICU); each session lasted 10 min and was labeled with the delirium status of the patient using the Confusion Assessment Method in ICU (CAM-ICU). To analyze this data, we formulate the task of visual attention as a hierarchical generative process that yields a probabilistic distribution of the location of the next fixation. This distribution can then be compared to the measured patient fixation producing a correctness score which is tallied compared across delirium status. This analysis demonstrated that the visual processing system of patients suffering from delirium is functionally restricted to a statistically significant degree. This is the first study to explore the potential mechanisms underpinning visual inattention in delirium and suggests a new target of future research into a disease process that affects one in four hospitalized patients with severe short and long-term consequences.

Projecting exceedance of juvenile salmonid thermal maxima in streams under climate change: A crosswalk from lab experiments to riparian restoration

Abstract Concern over rising water temperatures for freshwater ectotherms has led to application of experimentally derived thermal thresholds to stream temperature models for estimation of streams at high risk of exceeding thermal thresholds under current and future climate conditions. We optimised an approach that links field‐relevant thermal maxima experiments to corresponding stream temperature models and identifies opportunities to reduce stream temperatures through riparian tree growth. We conducted a thermal maxima experiment on cold‐water adapted juvenile Chinook (Oncorhynchus tshawytscha) and coho salmon (Oncorhynchus kisutch) that reflected natural temperatures by using incremental temperature ramping with diel fluctuations (IT‐Dmax) and refit a regionally specific stream temperature model for British Columbia, Canada to directly relate to lab‐derived thresholds. Salmon‐bearing streams across British Columbia were categorised by threshold exceedance risk (i.e., low, moderate, high, severe) based on risk tolerance scenarios for management decision making (i.e., considering a range of prediction intervals [PIs] and stream thermal sensitivities to air temperature). We linked these results directly to riparian management and restoration actions by estimating the potential for riparian tree growth to reduce threshold exceedance risk. Lab‐derived IT‐Dmax endpoints were consistently 24°C (based on the median value between the 7‐day average of the daily maximum and the mean weekly average temperature) across acclimation treatments for both species. Under current conditions, most stream reaches (99.6% using an intermediate risk tolerance scenario) were below the thermal threshold; streams with moderate to high risk of threshold exceedance were projected to increase from 0.4% to 1.5% (total linear stream length of 6,929 km) by end of century. The risk‐averse (high sensitivity, 75% PI) and risk‐tolerant (low sensitivity, 95% PI) scenarios differed by 1,107 km of streams predicted to have a moderate to severe risk of exceeding thresholds by end of century. Maximal riparian tree growth was predicted to shift 670 km of streams from moderate to low exceedance risk under end‐of‐century conditions and intermediate risk tolerance, showing the potential for mitigation from thermal impacts. Our integrative approach tackled several key considerations in identifying streams at high temperature risk for freshwater ectotherms that to date have not been addressed. Furthermore, we showcased the delineation of spatially comprehensive estimates that identify where management mitigation and a specific restoration activity may be most needed to reduce impacts of rising temperatures on rearing salmonids across an extensive region.

Promoting the participation of women: agenda setting in Swiss sports federations

ABSTRACT Following observations that efforts to promote female participation vary across sports federations, this study employs the multiple stream model to analyse agenda setting towards promotion programmes in Swiss sports federations. Through qualitative expert interviews in three case studies (football, ice hockey, and badminton), the study analyses why and when gender policies encouraging female participation at the grassroots level appear on a sports federation agenda. The findings show that the availability of external funding and the adaptation of external projects are essential opportunities for promotion activities. Engaged actors institutionalised within federations or emerging from personal commitment play a crucial role in seizing and exploiting opportunities. The study provides a conceptual contribution to the analysis of agenda setting of policies outside federations’ daily business and offers empirical insights to assist stakeholders in promoting women’s participation. Recommendations include involving committed individuals, especially in male-dominated sports, and securing (external) support to facilitate structural changes at the grassroots level.