Digital Commons Network^™

Reimagining Intelligence: A Comprehensive Review Of Human-Centric Ai Systems And Their Societal And Healthcare Integration, Zakaria Benlalia, Ghada Al-Kateb, Mourad Mzili, Konstantina Diamanti

Mesopotamian Journal of Artificial Intelligence in Healthcare

Human-Centric Artificial Intelligence (HCAI) is rapidly emerging as a transformative paradigm, shifting the focus of AI development from mere algorithmic optimization to ethical alignment, user trust, and societal integration most notably within the critical domain of healthcare. This review offers a comprehensive examination of the principles, architecture, challenges, and future directions underpinning HCAI, with an emphasis on its applications in health-related contexts. We begin by exploring the conceptual foundations of human-centricity, including core values such as transparency, fairness, autonomy, and privacy, all of which are essential in sensitive environments like clinical decision-making and patient data management. The paper then surveys …

Artificial Intelligence-Powered Robotic Technology For Transforming Palliative Care, Adebo Thomas, Asiku Denis, Wamusi Robert, Simon Peter Kabiito, Zaward Morish, Aziku Samuel, Malik Sallam, Ioannis Adamopoulos

Mesopotamian Journal of Artificial Intelligence in Healthcare

Palliative care seeks to improve the quality of life of patients with life-threatening illnesses by addressing their physical, emotional, and psychological needs. However, global challenges such as workforce shortages, limited access to specialized care, and inconsistent care quality demand innovative solutions. Advances in artificial intelligence (AI)-powered robotics offer transformative potential to overcome these barriers and strengthen palliative care delivery. This study explores how AI-driven robotic technologies support palliative care through applications in symptom monitoring, clinical decision-making, emotional companionship, and personalized care planning. It reviews cutting-edge robotic systems, including assistive, companion, diagnostic, nursing, procedural, service, and rehabilitation robots. Enabled by machine …

An Artificial Intelligence Model For Predicting Hospital Readmission Using Electronic Health Records Data, Rezarta Cara, Klodian Dhoska, Fjona Cara, Fredrick Kayusi, Linety Juma

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study investigates the application of a machine learning model—specifically the Light Gradient Boosting Machine (LightGBM)—to predict 30-day hospital readmissions using structured electronic health record (EHR) data. Hospital readmissions remain a critical challenge in healthcare systems, often indicating gaps in continuity of care and contributing to higher costs. By leveraging demographic, clinical, and diagnostic variables from 350 anonymized patient records, the model aimed to accurately identify individuals at high risk of readmission. Key features included age, number of previous admissions, length of stay, number of medications, chronic disease status, and gender. Data preprocessing, model training, and evaluation were conducted using …

Research For All: Building A Diverse Researcher Community For The All Of Us Research Program, Rubin Baskir, Minnkyong Lee, Sydney J Mcmaster, Jessica Lee, Faith Blackburne-Proctor, Romuladus Azuine, Nakia Mack, Sheri D Schully, Martin Mendoza, Janeth Sanchez, Yong Crosby, Erica Zumba, Michael Hahn, Naomi Aspaas, Ahmed Elmi, Shanté Alerté, Elizabeth Stewart, Danielle Wilfong, Meag Doherty, Margaret M Farrell, Grace B Hébert, Sula Hood, Cheryl M Thomas, Debra D Murray, Brendan Lee, Louisa A Stark, Megan A Lewis, Jen D Uhrig, Laura R Bartlett, Edgar Gil Rico, Adolph Falcón, Elizabeth Cohn, Mitchell R Lunn, Juno Obedin-Maliver, Linda Cottler, Milton Eder, Fornessa T Randal, Jason Karnes, Kitani Lemieux, Nelson Lemieux, Nelson Lemieux, Lilanta Bradley, Ronnie Tepp, Meredith Wilson, Monica Rodriguez, Chris Lunt, Karriem Watson

Faculty, Staff and Students Publications

OBJECTIVES: The NIH All of Us Research Program (All of Us) is engaging a diverse community of more than 10 000 registered researchers using a robust engagement ecosystem model. We describe strategies used to build an ecosystem that attracts and supports a diverse and inclusive researcher community to use the All of Us dataset and provide metrics on All of Us researcher usage growth.

MATERIALS AND METHODS: Researcher audiences and diversity categories were defined to guide a strategy. A researcher engagement strategy was codeveloped with program partners to support a researcher engagement ecosystem. An adapted ecological model guided the ecosystem …

Structure/Property/Processing Of A 3d Printed Self-Healing Polymer Blend Based On A Thermoplastic Healing Agent, Vincent Mei

Theses

Self-healing polymers can regain mechanical performance following damage, offering increased material durability and sustainability. This thesis establishes structure/property/processing relationships for a 3D printable extrinsically self-healing polymer based on a UV polymerizable thermosetting resin system blended with a low temperature thermoplastic healing agent. This work serves as the first example of a vat polymerization 3D printed soft, low Tg low-melt thermoplastic extrinsically self-healing polymer blend. This development enables high resolution fabrication of complex geometries with self-healing functionality. This strategy of imbuing self-healing properties onto vat polymerization resins will enable functionality in many application spaces including aerospace, biomedical, soft robotics, coatings, and …

Fake News Detection In Arabic Media Using Machine Learning And The Afnd Dataset, Hussain Ali Bahri

Theses

The proliferation of fake news in digital media poses a significant challenge to information credibility, particularly in linguistically diverse regions such as the Arab world. This study addresses the critical problem of detecting fake news in Arabic media by leveraging advanced natural language processing (NLP) techniques and the AFND dataset, which contains over 600,000 news articles categorized into "credible," "not credible," and "undecided" classes. The research focuses on developing a robust system using AraBERT, a transformer-based model specifically pre-trained for Arabic text. Key contributions of this work include a comprehensive preprocessing pipeline tailored to Arabic linguistic complexities, incorporating stopword removal, …

Support For Older People Living With Chronic Life-Limiting Illnesses In Rural Ghana, Barbara Adonteng-Kissi, Obed Adonteng-Kissi

Research outputs 2022 to 2026

Summary: This research aims to address formal support needs of informal caregivers (ICs) in the context of long-term care of older people (OP) living with chronic life-limiting illnesses and examine the relationships of ICs of OP with formal support in rural Ghana. We undertook ethnographic interviews with 15 OP; 15 ICs; and 10 healthcare professionals (HPs) after participatory observations during 6 months of fieldwork. This was supported with daily field notes used to collect the needed data and purposively sampled across Gomoa West District in Ghana. The average age of participants was 76 years. Interviews were recorded and transcribed, using …

A Deep Dive Into Taught Postgraduates’ Participation In Work-Integrated Learning, Denise Jackson

Research outputs 2022 to 2026

This study draws on national data to explore postgraduate participation in different types of work-integrated learning (WIL) in Australia. Despite considerable interest in WIL engagement in higher education, research is primarily focused on undergraduates with relatively little known about participation in postgraduate cohorts and how this varies across disciplines. Consequently, this study analyses how 119,000 graduates of Australian postgraduate coursework degrees engaged in work-based WIL (e.g., internships/placements); non-workplace WIL (e.g., projects/consultancies) and global WIL experiences between 2020 and 2023. In addition to breakdowns by discipline and international/domestic student status, the study examines relationships between WIL engagement and personal, study and …

Students As Designers With 3d Design And Fabrication Technologies, Carol Puddicombe, Rob Rouse, Marco Tolomei, David Ellis

Research outputs 2022 to 2026

This chapter explores integrating 3D design and fabrication technologies into educational settings, emphasising their potential to enhance student creativity, problem-solving skills, and real-world capabilities. Through using 3D design and fabrication tools such as computer-aided design (CAD) software, 3D printers, laser cutters, and computer numerical control (CNC) machines, students can transition from passive learners to active creators, engaging with tangible projects that connect theoretical concepts and practical challenges. The chapter highlights the importance of supporting teachers in adopting these technologies, addressing challenges such as hardware costs, software accessibility, and teacher training. By progressively increasing project complexity and incorporating real-world applications, educators …

Corrosion Behavior Of Niti Alloys Fabricated By Laser Powder Bed Fusion In Relation To The Formed Passive Films In Hank's Solution, Yi Fan Zhang, Liang Yu Chen, Yong Liu, Hong Yu Yang, Jin Hua Peng, Chuanbo Zheng, Lina Zhang, Lai Chang Zhang

Research outputs 2022 to 2026

Laser powder bed fusion (L-PBF) produced NiTi alloys have significant potential in biomedical applications. Varying the parameters of the L-PBF process may result in the NiTi alloys with different ratios of B2 and B19′ phases, thereby, the different corrosion performance in the human body. However, a dearth of research efforts remains dedicated to resolving this issue. This work employed three different but comparable sets of parameters in the L-PBF process to produce NiTi alloys with different ratios of B2 and B19′ phases. The corrosion behavior of samples in Hank's solutions with the addition of lactic acid and their evolution of …

Mxene Based Composite Phase Change Materials For Thermal Energy Storage Applications: Featuring Bio-Mimic Approaches, Md Shahriar Mohtasim, Barun K. Das

Research outputs 2022 to 2026

Phase change materials (PCMs) are widely used in thermal energy storage systems, but their underlying drawbacks, such as poor heat conductivity and phase transition leakage, make them unsuitable for widespread use. MXenes have received a lot of curiosity due to having extraordinary mechanical properties, high electrical conductivity, and unique layered structure. Owing to the exquisite arrangements, numerous unique biomimetic morphologies have drawn attention. Numerous investigations regarding bio-mimic MXene/PCM composites (BMX-CPCMs) have found improvements in latent heat up to 106.50 % on average, along with excellent thermal stability with no matrix leakage in 500 cycles and an upsurge in thermal conductivity …

Evaluating The Efficacy Of A Serious Game To Deliver Health Education About Invasive Meningococcal Disease: Clustered Randomized Controlled Equivalence Trial, Lauren Bloomfield, Julie Boston, Martin Masek, Lesley Andrew, Donna Barwood, Amanda Devine

Research outputs 2022 to 2026

Background: Invasive meningococcal disease (IMD) is a serious, vaccine-preventable infectious disease that can be life-threatening. Teaching adolescents about the early detection and prevention of IMD can be challenging in a school environment, with educators reporting they lack confidence or expertise to cover this in the classroom environment. Professional guest educators are an alternative to cover specialist topics such as IMD; however, time and resourcing constraints can mean that these educators are not always available. Serious games may be an alternative to face-to-face education, where complex health information may be delivered via self-directed gameplay. Objective: This study aims to develop a …

Sub-Bituminous Coal As A Peculiar Adsorbent For Dye Removal From Wastewater, Z. H. Rada, H. R. Abid, M. B. Ahmed, M. Zargar

Research outputs 2022 to 2026

Coal, an abundant and cost-effective adsorbent, is explored for its potential in environmentally friendly greenhouse gas storage. Herein, the adsorption of anionic (methyl orange) and cationic (methylene blue) dyes on sub-bituminous coal was intensively studied. This study is the first application of sub-bituminous coal to examine the removal of different concentrations of dyes from water. The properties of the coal were studied using advanced analytical techniques. The initial dye concentration, solution pH, and adsorbent-adsorbate contact time were investigated for their influence on the adsorption efficiency of the dyes. Adsorption kinetics were then studied by applying common kinetic models and the …

Genai’S Impact On Global It Management: A Multi-Expert Perspective And Research Agenda, Yogesh K. Dwivedi, Laurie Hughes, Mohammad S. Al-Ahmadi, Vincent Dutot, Syed Q. Ahmed, Shahriar Akter, Rahul De’, Keyao Li, Nitish Singh, Paul Walton

Research outputs 2022 to 2026

Generative AI (GenAI) is disrupting global IT management and challenging established practice. The increasing use of GenAI technology is redefining localization, transforming existing workforce roles, outsourcing strategy, and team dynamics. Simultaneously, GenAI’s security complexities have prompted the rethinking of existing risk frameworks to meet a new set of challenges from GenAI enhanced cyber threats. This article explores these complex and converging factors, providing a roadmap to address GenAI’s significant impact on global IT management. We advocate the responsible adoption of GenAI and importance of building resilient, value-driven, globally consistent IT ecosystems able to adapt to the significant challenges and opportunities …

A Critical Review On Parameters Affecting The Feasibility Of Underground Hydrogen Storage, Chiradip Bagchi, Samarth D. Patwardhan, Stefan Iglauer, Hisham Ben Mahmud, Muhammad Fazil Jaffar Ali

Research outputs 2022 to 2026

The need and demand for energy are ever increasing with the rapid urbanization of the global population. Near-future economic development and consequent expected industrialization are the strongest indicators of the rising energy requirement. Though fossil fuel and coal are catering toward a major chunk of energy demand, their negative or adverse impact in terms of emission of greenhouse gases (GHGs) and carbon dioxide (CO2) is causing global warming and imbalance in environmental conditions, leading to a search for commercially viable alternate energy types. As renewable energies like solar and wind are weather-dependent, the search for an alternate energy supply needs …

Exploring The Barriers To Mental Health Help-Seeking Among African Migrants In Australia: A Qualitative Study, Nnaemeka Meribe, Obed Adonteng-Kissi, Kathomi Gatwiri, Lillian Mwanri, Frank Darkwa Baffour, Agness Tembo, Edith N. Botchway-Commey, David Chisanga, Ahmed A. Moustafa, Kerrie E. Doyle, Uchechukwu Levi Osuagwu

Research outputs 2022 to 2026

Background: The health of African migrants in Australia is a largely under-researched topic despite the steadily increasing size of the population and its uniqueness. In particular, few studies have explored the mental health of African migrants in Australia or their utilization of mental health services.

Aims: This study explored the barriers to mental health help-seeking among first-generation African migrants in Australia.

Methods: In this qualitative study conducted using the hermeneutical phenomenological research approach, the purposive sampling method was used to recruit participants. In-depth interviews with participants were undertaken online via Zoom, Teams, and WhatsApp calls. Interviews were recorded and transcribed …

Sensitivity Analysis Of Reservoir Characteristics And Flue Gas Composition For Enhanced Oil Recovery In Heterogeneous Reservoir, Mehdi Nassabeh, Zhenjiang You, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

The success of enhanced oil recovery depends on optimizing various reservoir factors. While CO2 and flue gas injections are common methods, they encounter challenges that require a deep understanding of reservoir characteristics and thorough analysis of pertinent parameters for effective mitigation. This study aimed to explore the synergistic relationship between flue gas compositions, reservoir characteristics, and injection rates for optimal oil recovery. Unlike prior studies that primarily examined the isolated effects of CO2 or flue gas, this research uniquely investigates the combined impact of real-world flue gas compositions from industrial sources under heterogeneous reservoir conditions. Through extensive sensitivity analysis and …

Towards Robust Multimodal Land Use Classification: A Convolutional Embedded Transformer, Muhammad Zia Ur Rehman, Syed Mohammed Shamsul Islam, Anwaar Ulhaq, David Blake, Naeem Janjua

Research outputs 2022 to 2026

Multisource remote sensing data has gained significant attention in land use classification. However, effectively extracting both local and global features from various modalities and fusing them to leverage their complementary information remains a substantial challenge. In this paper, we address this by exploring the use of transformers for simultaneous local and global feature extraction while enabling cross-modality learning to improve the integration of complementary information from HSI and LiDAR data modalities. We propose a spatial feature enhancer module (SFEM) that efficiently captures features across spectral bands while preserving spatial integrity for downstream learning tasks. Building on this, we introduce a …

Novel Digital Twin Deployment Approaches: Local And Distributed Digital Twin, Shahid Rauf, Fazal Muhammad, Akhtar Badshah, Hisham Alasmary, Muhammad Waqas, Sheng Chen

Research outputs 2022 to 2026

The Digital Twin (DT) technology is considered as a backbone in the Industrial 4.0 revolution as it is playing a vital role in the digitization of various industries. A DT is a virtual representation of a physical entity, thus having the ability to simulate real data generated at physical space to optimize, estimate, control, monitor and forecast states/configurations. Despite enormous benefits, DT technology has several implementation challenges. Although deploying DT on edge or cloud platforms yields a plethora of services, its implementation in both spaces faces certain limitations. These limitations include latency, data communication overload, transmission energy consumption, privacy concerns, …

Investigating The Potential Of Remote Ultraviolet Sensing For Real-Time Produced Water Monitoring: A Lab-Scale Study, M. Weir, T. Robertson, D. I. Maroef, M. L. Johns, M. Zargar

Research outputs 2022 to 2026

Traditional produced water discharge monitoring techniques involve ‘end of pipe’ sample collection and analysis, offering a snapshot of discharged fluid composition and predicting the marine environmental risk through dispersion models. This study presents a proof-of-concept analysis of using ultraviolet remote sensing for real-time produced water monitoring, enabling data capture directly within the marine environment. Ultraviolet imaging was used to quantify the sheen intensity of artificially prepared produced water standards and to evaluate the relationship between image signal intensity and total petroleum hydrocarbon concentration over time. A statistically significant relationship was observed between signal intensity and total petroleum hydrocarbon concentrations, with …

Measuring Career Aspirations In Science, Technology, Engineering, Mathematics And Education, Michael Fitzgerald, Saeed Salimpour, David Mckinnon, Rachel Freed, Dan Reichart

Research outputs 2022 to 2026

There has been a sustained interest in student perceptions about STEM fields and their choice of careers over the past few decades. Research has shown that there is a decline in students pursuing STEM careers, and this has raised global concern. Despite these issues, no unistructural, broad, parsimonious and unambiguous quantitative instrument exists to probe student career aspirations. This paper highlights the background, extension and validation of an instrument, derived from a previous science-focussed high-quality instrument that allows student career aspirations to be quantitatively characterised. Participants were 1221 undergraduate students, 1003 of whom were judged to have provided good data, …

The Careful Project: Evaluating The Acceptability Of Local Virtual Reality Experiences As A Leisure Activity For Residents In Aged Care, Davina Porock, Patricia Cain, Christopher Young, Julieanne Hilbers, Maria Bomm, Manonita Ghosh, Mandy Stanley

Research outputs 2022 to 2026

Objectives: The aim of this project was to evaluate the feasibility and acceptability of virtual reality (VR) as a leisure activity for people living in residential aged care. Virtual reality experiences may offer alternatives for residents with limited mobility, or during times when older people are unable to leave residential care. Methods: The intervention used VR videos delivered via a head-mounted device. Video content was created by a local artist specifically for use with older Western Australian adults and used local content. VR sessions were videotaped for analysis. The evaluation included structured observation of video content to assess mood and …

Optimizing Hospital Operational Efficiency Using Ai: A Multi-Objective Nsga-Ii Model For Real-World Medical Data In Syria, Khder Alakkari, Bushra Ali, Teba Majed Hameed

Mesopotamian Journal of Artificial Intelligence in Healthcare

This study presents an AI-driven multi-objective optimization approach using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to enhance hospital operational efficiency in Syria. Using real-world data from the Tishreen University Hospital over a 60-day period, the research addresses three conflicting objectives: minimizing average patient waiting time, reducing daily operational costs, and maximizing the number of patients treated. Six key operational variables were selected to build the optimization model, including bed availability, physician count, and daily admissions. The NSGA-II algorithm successfully generated a set of Pareto-optimal solutions, each reflecting different trade-offs among the objectives. Statistical analysis and visualizations confirmed the complexity …

Industry 4.0 Digital Transformation And Opportunities For Supply Chain Resilience: A Comprehensive Review And A Strategic Roadmap, Morteza Ghobakhloo, Mohammad Iranmanesh, Behzad Foroughi, Ming Lang Tseng, Davoud Nikbin, Ahmad A.A. Khanfar

Research outputs 2022 to 2026

Despite interest in opportunities that Industry 4.0 offers for Supply Chain Resilience (SCR), little is known about the underlying mechanisms for such contributions. The study develops a roadmap that explains how supply chains can capitalize on Industry 4.0 SCR functions. The study conducted a content-centric literature review and identified 16 functions through which Industry 4.0 enhances SCR. Results reveal that the Industry 4.0 SCR functions identified are highly interrelated, and supply chain members should align their digitalization strategies with the sequence in which Industry 4.0 delivers these functions. Industry 4.0 contribution to SCR first involves delivering data-centric functions such as …

The Influence Of Ultra-Widefield Fluorescein Angiography On The Diagnosis And Management Of Diabetic Retinopathy, Nicole K Scripsema, Tala Al-Khaled, Amy Song, Joelle A Hallak, Rawan Allozi, Aziz A Khanifar, Thanos D Papakostas, Christina Y Weng, Ronald C Gentile, J Peter Campbell, Jessica G Lee, Gennady Landa, Felix Y Chau, William F Mieler, Meenakashi Gupta, Amani A Fawzi, Judy E Kim, Jennifer I Lim, Robison Vernon Paul Chan

Faculty, Staff and Students Publications

Purpose: To study the influence of ultra-widefield fluorescein angiography (FA) on the diagnosis and management of diabetic retinopathy (DR).

Methods: Ten experts in DR completed an online survey in which they were asked to diagnose and manage DR cases using different imaging modalities. Experts independently reviewed 20 cases of DR and provided a diagnosis and management plan for each case, first based on ultra-widefield color-free and red-free images alone and again with the corresponding ultra-widefield FA images. Experts were polled on their diagnostic confidence, use of FA in clinical practice, and opinions on the value of ultra-widefield FA. Based on …

Enhancing Energy Efficiency In Solar Thermal Systems: The Role Of Hybrid Nanofluids In Sustainable Energy Harvesting And Storage, Seyedehzahra Haeri

Theses: Doctorates and Masters

Global energy demand continues to grow, making the reliance on fossil fuels increasingly unsustainable due to dwindling reserves and environmental impacts. Among these, solar thermal systems have emerged as a practical and environmentally friendly solution, with applications ranging from industrial heating and solar water heating to concentrated solar power (CSP) plants and solar desalination units. Solar-based thermal systems offer a promising alternative, with nanofluids (NFs) emerging as a transformative solution. Engineered by dispersing nanoparticles into base fluids, NFs enhance thermal conductivity, heat absorption, and efficiency. Notably, nanoparticles such as titanium nitride also act as nano-catalysts, improving chemical reactions and reducing …

Applications Of Reservoir Simulation And Machine Learning In Subsurface Energy Systems For Decarbonization, Seyedmohammadmehdi Nassabeh

Theses: Doctorates and Masters

The transition to a low-carbon future necessitates innovative approaches to carbon management and hydrogen storage, particularly in the context of enhanced oil recovery (EOR) from hydrocarbon reservoirs. This study employs advanced analytics and machine learning techniques to optimize carbon management strategies. One key focus of this research is to evaluate the effectiveness of flue gas and CO2 in Water Alternating Gas (WAG) injection within a homogeneous fractured carbonate reservoir characterized by low porosity and permeability. A computational model was developed to depict the flow regime in the reservoir and simulate reservoir fluid behavior using Eclipse (E300) software, various hybrid EOR …

Once More On The Rank And File – Union Bureaucracy Interplay: Mining Unionism In Australia’S Pilbara Region, Alexis Vassiley

Research outputs 2022 to 2026

The trade union bureaucracy debate has significant implications for both analysis and union strategy. Recently receiving renewed academic attention, this debate centres around whether there is a dichotomy between rank-and-file workers and full-time union officials, and whether these officials – the trade union bureaucracy – tend towards industrial conservatism. The case study of labour relations in the Pilbara iron ore industry in the north of Western Australia 1965–1986 enriches our analysis of the trade union bureaucracy by viewing its role in the class struggle over a number of decades, in varying contexts of union development, union power and union decline. …

Gans And Synthetic Financial Data: Calculating Var*, David E. Allen, Leonard Mushunje, Shelton Peiris

Research outputs 2022 to 2026

Generative Adversarial Neural nets (GANs) are a new branch of machine learning techniques. A GAN learns to generate new data from the training data set. We examine the characteristics of the fake financial data using GANs trained on samples of daily S&P 500 and FTSE 100 index values. GANs feature two competing neural networks in a game theoretic context. The Generator net generates pseudo data that is presented to the discriminator net which then attempts to distinguish between the real and the fake data. This facilitates unsupervised learning on the dataset. The generative network generates data sets, while the discriminative …

Music, Terror, Disaster, Healing, Zuzana Jurková, Oldrich Podebradský, Zuzana Gulová

Journal of Urban Culture Research

On December 21, 2023, a student of Charles University in Prague, one of the safest places in the world, shot dead 14 academics and students. Amidst omnipresent grief and mourning, the process of coping and “healing” started immediately, manifested in particular through a series of events called the “Month for the Faculty.” This text is based on participation in and research of these activities. The theoretical part uses the Durkheim's concept of piacular rites, the aim of which is to “reconfirm [a] community's solidarity.” Following the recommendations of Bin Xu (2016), we investigated who the main agents were in the …