Cross-disciplinary Research Research Articles

Assessing industry 4.0 readiness: a TOE-P framework for the sugar industry in developing economies

Industry 4.0 concepts have recently significantly supported transparency and reliability in every industrial sector. Organizations must adapt their traditional paradigms and approaches to align with market demands. Hence, developing a framework that can change these conventional approaches with fresh ideas is essential. The Industry 4.0 (I4.0) readiness model presents a creative concept that holds promise for the entire organizational and industrial value chain. Existing research focused only on technological, organizational, and environmental aspects. However, in process-extensive industries, like the sugar sector, the process is critical and considerably impacts the business. So, providing a strong framework for such sectors is necessary. The novelty of this paper is putting a process dimension in the TOE framework, which is critical for sugar industries. The study develops the extended framework to assess readiness. Experts have validated the framework as the study enhances it by adding process dimensions. Practitioners can apply the modeling concept to study the readiness framework in various sectors. Consequently, essential findings and recommendations drive the discussion forward. The study highlights opportunities for cross-disciplinary research across sectors.

Quantum algorithms and complexity in healthcare applications: a systematic review with machine learning-optimized analysis

This paper presents a systematic review of quantum computing approaches to healthcare-related computational problems, with an emphasis on quantum-theoretical foundations and algorithmic complexity. We adopt an optimized machine learning methodology—combining Particle Swarm Optimization (PSO) with Latent Dirichlet Allocation (LDA)—to analyze the literature and identify key research themes at the intersection of quantum computing and healthcare. A total of 63 peer-reviewed studies were analyzed, with 41 categorized under the first domain and 22 under the second. This approach revealed two primary research directions: (1) quantum computing for artificial intelligence in healthcare, and (2) quantum computing for healthcare data security. We highlight the theoretical advances underlying these domains, from novel quantum machine learning algorithms for biomedical data to quantum cryptographic protocols for securing medical information. A gradient boosting classifier further validates our taxonomy by reliably distinguishing between the two categories of research, demonstrating the robustness of the identified themes, with an accuracy of 84.2%, a precision of 88.9%, a recall of 84.2%, an F1-score of 84.5%, and an area under the curve of 0.875. Interpretability analysis using Local Interpretable Model-Agnostic Explanations (LIME) exposes distinguishing features of each category (e.g., references to biomedical applications versus blockchain-based security frameworks), offering transparency into the literature-driven categorization, with the latter showing the most significant contributions to topic assignment (ranging from −0.133 to +0.128). Our findings underscore that quantum algorithms offer significant potential to enhance data security, optimize complex diagnostic computations, and provide computational speedups for health informatics. We also identify outstanding challenges—such as the need for scalable quantum algorithms and error-tolerant hardware integration—that must be addressed to translate these theoretical advancements into real-world clinical impact. This study emphasizes the importance of hybrid quantum-classical models and cross-disciplinary research to bridge the gap between cutting-edge quantum computing theory and its practical applications in healthcare.

Synergizing AI and blockchain: a bibliometric analysis of their potential for transforming e-governance in smart cities

Integrating AI and blockchain technologies holds significant potential for enhancing e-governance, particularly in improving predictive policy execution within smart cities. This study conducts a comprehensive review and bibliometric analysis of existing literature to identify trends, key publications, and research gaps. Using peer-reviewed articles indexed by Scopus and published between 2019 and 2024, we observe a significant rise in research output, focusing on the separate applications of AI and blockchain in e-governance. Key themes identified include enhanced transparency, efficiency in public services, and concerns related to data privacy. However, our analysis uncovers a clear gap in empirical studies addressing the combined use of AI and blockchain technologies. The bibliometric coupling map reveals central clusters around “smart city” and “blockchain,” while topics such as “sustainability” and “climate change” show significant impact, highlighting their relevance to governance. Additionally, the study identifies a lack of cross-disciplinary research, emphasizing the need for future interdisciplinary collaborations. Despite the insights gained, the study is constrained by its reliance on bibliometric methods, which may not capture the complexities of real-world technology integration. Future research should prioritize longitudinal case studies and pilot projects to address regulatory, ethical, and practical challenges, contributing to the responsible adoption of AI and blockchain in digital governance.

A scoping study of the whole-cell imaging literature: a foundational corpus, potential for mesoscale data synthesis, and implications for standardization of an emerging field.

The level of cellular organization bridging the mesoscale and whole-cell scale is coming into focus as a new frontier in cell biology. Great progress has been made in unraveling the complex physical and functional interconnectivity of organelles, but how the entire organelle network is spatially arranged within the cytoplasm is only beginning to be explored. Drawing on cross-disciplinary research synthesis methods, we systematically curated the whole-cell volumetric imaging literature, resulting in a corpus consisting of 89 studies and 118 image datasets. We describe the trajectory and current state of the field between 2004 and 2024. A broad characterization, or "scoping review", of bibliometrics, study design, and reporting practices shows accelerating technological development and research output. We find high variability in study design and reporting practices, including imaging modality, model organism, cellular contexts, organelles imaged, and analyses. Due to the laborious, low-throughput nature of most volumetric imaging methods, we find trends toward small sample sizes (<10 cells) and small cell types. We describe common quantitative analyses across studies, including volumetric ratios of organelles and inter-organelle contact analyses. This work establishes the initial iteration of a growing dataset of whole-cell imaging literature and data, and motivates a call for standardized whole-cell imaging study design, reporting, and data sharing practices in the context of an emerging sub-field of cell biology. Our curated dataset now provides the basis for a plethora of future aggregate and comparative analyses to reveal larger patterns and generalized hypotheses about the systems behavior and regulation of whole-cell organelle networks. More broadly, we showcase the potential of new rigorous secondary research methods to strengthen cell biology's literature review and reproducibility toolkit, create new avenues for discovery, and promote open research practices that support secondary data-reuse and integration.

A ten-year bibliometric study on mathematical ability

&lt;span&gt;Mathematical ability is a crucial aspect of modern life as it influences various fields such as economics, technology, and science. This study, spanning 2014-2023, examines articles on mathematical ability in leading journals. Using the bibliometric methods, it includes article searches in Scopus and Google Scholar via Publish or Perish (PoP), classification for bibliometric analysis, metadata checks, and bibliometric analysis using VOSviewer. The research shows a consistent trend in publications on mathematical ability, with minimal fluctuations and significant citation patterns. High-citation articles underscore the field’s importance in knowledge advancement. Key terms are ‘ability’, ‘mathematical ability’, and ‘student’, indicating research focus areas. However, limited author collaboration suggests potential for increased interdisciplinary synergy and knowledge sharing. These findings highlight opportunities for enhancing cross-disciplinary collaborations and research networks. They offer insights for policymakers, educators, and researchers in understanding trends, developing effective learning strategies, and encouraging further research in mathematical ability. In summary, this bibliometric study provides a comprehensive overview of the significance of mathematical ability in research, emphasizing the need for collaborative, innovative educational and research practices. It underscores the importance of further research to deepen understanding and application of mathematical ability, promoting an integrative approach in this essential field.&lt;/span&gt;

Nanomechanical characterization of soft nanomaterial using atomic force microscopy.

Nanomechanical characterization of soft nanomaterial using atomic force microscopy.

Cross-Disciplinary Research on Music and Cultural Activities: Uncovering Trends and Interconnections via CiteSpace Visualization Analysis

Cross-Disciplinary Research on Music and Cultural Activities: Uncovering Trends and Interconnections via CiteSpace Visualization Analysis

Aging Equity and Diversity as Part of Age-Friendly Community Practice in the United States

ABSTRACT Despite calls for promoting equity and recognizing diversity within age-friendly community (AFC) efforts, there has been little research on how leaders attend to such considerations in practice. We iteratively coded data from qualitative interviews with leaders of eight AFC initiatives in New Jersey (United States [U.S.]) conducted across multiple years. Five themes were identified regarding areas in which considerations of aging equity and diversity emerged: communications to the public; outreach and advocacy; engagement structures; events and programming; and direct services. We discuss implications for cross-disciplinary research, policy, and practice to advance AFC initiatives in the U.S. and other similar contexts.

Ethical witnessing: participatory virtual reality production and the experience of homelessness

ABSTRACT Lost & Found, is a nonfiction 360-degree documentary film co-created by a cross-disciplinary research team from the University of Galway, virtual reality filmmakers, and clients of a homelessness service provider. Conceptualized in response to scholarly debates around VR and empathy, it draws on participatory video methodologies to situate the voice of community participants at the heart of VR documentary production. Here, Lost & Found is considered in relation to its impact on two cohorts: the end viewer of the film and the clients of Galway Simon who co-created it. The measured impact of the finished film on viewer empathy and attitudes develops existing debates around the potential for immersive experiences to produce attitudinal change. At the same time, the co-creation methodology that guided the film’s production and exhibition grapples with the questions of inclusion, authorship and viewer positioning that have animated the discourse around VR and documentary filmmaking more generally. Through this discussion, attention is brought to the dynamics of inclusion and exclusion that arise from the use of immersive technologies within community settings, as well how the viewer experience within VR can be conceptualized as a form of ethical witnessing.

A humble opinion on the advance of oral medicine research in China

To better reflect the current status and key research trends in oral medicine research of China and to enhance the overall research abilities in this field, this special issue on oral medicine research integrates the work of several young academic leaders from oral medicine research centers nationwide. Their work focuses on key areas such as artificial intelligence-assisted diagnosis, the pathogenic mechanisms of intracellular bacteria, the relations between oral mucosal diseases and systemic diseases, as well as the study and reporting of rare and unique cases, aligning with the forefront of biomedical research. Although it does not encompass all the high-level researches conducted in China, it presents a rich and diverse array of academic achievements. Those achievements of researches reflect that it is important to further advance interdisciplinary and cross-disciplinary research collaborations, particularly by strengthening cooperation with engineering and technological disciplines in the future. We also need to set sights on driving researches in novel pathogenesis mechanisms of oral mucosal diseases, exploring innovative diagnostic technologies, enhancing diagnostic accuracy and treatment efficacy, and developing new effective intervention strategies. Additionally, greater emphases will be placed on ensuring the accuracy, comprehensiveness, readability, and scientific rigor of case studies and reports to promote sustained progress in this field.

Expansion microscopy in Placozoa: improving resolution and preservation of fragile samples during marine expedition

Placozoa are small disc-shaped animals representing one of the early branching metazoan lineages with only a dozen cell types, fast effector reactions, and complex behaviors. The simplest organization and small cell sizes limit standard microscopy applications. Here, we implement a new methodology and protocol for expansion microscopy, improving both the resolution and preservation of fragile placozoans and kin. As a result, the proposed approaches can be applicable to a diversity of microscopic animals and their larvae with broad applicability for both laboratory and cross-disciplinary field research during long-term marine expeditions.

Is the Relationship Between Adolescent Social Isolation and Anxiety-Like Behaviors Altered by Microglia Ablation in Female Long Evans Rats?

Despite extensive, cross-disciplinary research revealing a relationship between early life stress (ELS) and an increased risk for neuropsychiatric disorders, the underlying processes mediating this relationship are not fully understood. Further, the majority of preclinical studies investigating this relationship have not taken sex differences into consideration. A growing body of work suggests that microglia, resident immune cells of the brain, are impacted by ELS and contribute to some of the maladaptive behavioral phenotypes in adulthood. Here, we utilized an adolescent social isolation (aSI) model of ELS in female rats to test the role of microglia in mediating the effects of ELS on anxiety-related behaviors. The present study sought to determine whether microglia ablation during aSI could prevent anxiety-like behaviors in female Long Evans rats. A colony-stimulating factor 1 receptor (CSF1-r) inhibitor, PLX3397, was provided in chow to ablate microglia at the start of the isolation period (postnatal day (P) 21-42). During the aSI period, animals performed a battery of behavioral assays including the open field test, elevated plus maze, and successive alleys test. Following completion of the behavioral assays, brain tissue was collected to confirm the efficacy of PLX3397 and identify changes in microglia population density. Relative to group-housed (GH) controls, aSI rats showed increased locomotor activity in the open field test and higher closed-arm entries on the elevated plus maze. Although PLX3397 effectively ablated microglia across all animals, this treatment had minimal effects on observed aSI-associated phenotypes. Together, these data suggest that microglia are not required for behavioral adaptations promoted by aSI. Future studies will be needed to assess the role of microglia in the relationship between ELS and maladaptive behavioral phenotypes.

Large Language Models Empowering Interpreting Teaching: A Research on User Satisfaction Survey and Functional Optimization Strategies

To address the limitations of the "DeepSeek" large language model (LLM) in interpreting education, this study investigates user satisfaction and proposes optimization strategies by analyzing its application across pre-interpreting, while-interpreting, and post-interpreting phases. Targeting translation majors and learners, a questionnaire was designed to identify key factors influencing user satisfaction. Data analysis reveals critical insights, leading to tailored optimization strategies for each phase. The findings emphasize the necessity of integrating LLMs into interpreting pedagogy to enhance training efficiency, reduce cognitive load, and foster cross-disciplinary research capabilities.

Overcoming the Smart City Governance Challenge: An Innovation Management Perspective

ABSTRACT This commentary explores the potential of strengthening smart city development (SCD) governance theory through a more meaningful integration of innovation management studies. We highlight the limited theoretical framework in SCD governance and show how theoretical stimuli from innovation management can address key governance challenges affecting SCD. Our focus encompasses several governance challenges that we use as exemplary cases: conceptualizing SCD, strategizing citywide SCD efforts, introducing monitoring methods and indicators for SCD projects, intermediating among stakeholders, and managing multi-level governance dynamics. The primary goal of our commentary is to advocate for increased multidisciplinary research in the SCD field, emphasizing the accelerated knowledge accumulation achievable by linking it with the more established field of innovation management studies. We conclude that innovation management offers valuable insights for advancing SCD governance theories. This commentary initiates a dialogue on the necessity of cross-disciplinary research in the smart city domain, which is expected to benefit both academics and practitioners.

Challenges and solutions to complex data governance issues in cross-national, cross-sectoral, multidisciplinary real world health research: a descriptive overview

Real-world clinical data is generated during clinical engagements. The collection and further processing and mining of clinical information requires consents and navigation of necessary and important data governance processes. PRECISION ALS is an academic industry programme that collects, collates and analyses clinical and para-clinical data from patients with ALS across 10 European sites. The infrastructure of PRECISION ALS represents a complex interplay of the clinical, governance, and technical frameworks. Incorporation of infrastructural and operational measures enables sophisticated cross-national, cross-sectoral and cross disciplinary health research. PRECISION ALS has established a range of domain expertise, technologies, governance and clinical data management practices that can be applied throughout the life cycle of patient data from generation, collation, delivery and secure storage for advanced analytics. PRECISION ALS is designed to move the field of ALS research to a true Precision Medicine based approach toward new and more effective therapeutics.

A Cross-Disciplinary Bibliometric Review of Family-Friendly Work Activities and Agenda for Future Research

Over the past few decades, scholarship on managing the work-family interface has expanded, particularly regarding family-friendly work activities (FFWAs) designed to alleviate various forms of work-family conflict. We bring together the broad, cross-disciplinary research on FFWAs using bibliometric performance and mapping techniques. Using these techniques, we review 40 years of FFWA research across different scientific disciplines to then synthesize the existing knowledge and identify its contributing entities (e.g., authors, journals), collaborations among some of the entities (e.g., co-author relationships), and main themes, and collaborations among authors. In other words, we map and describe the intellectual, social, and conceptual structures of the FFWA literature. Based on this, we organize and integrate the cross-disciplinary literature across levels of analysis using the Ability-Motivation-Opportunity (AMO) model into a nomological network of FFWAs’ antecedents and consequences. Then, we use this nomological net to further delineate research questions and provide avenues for future research. Taken together, our comprehensive review offers clarity on the current state of FFWAs research and provides recommendations for future studies to advance theory, research, and practice.

Cross-Disciplinary Methods in Peace Studies Research: Agency, Uncertainty and Emancipation

Cross-disciplinary peace research frequently focuses on social and political power differentials between people. Like the tradition found in the broader social sciences, peace studies seeks to raise consciousness about, and address, unequal relationships and lends itself to the application of cross-disciplinary methodologies. It is concerned with relational inequities and how they might be remedied, including those between the researcher and research participants. This article discusses a suite of methods developed for a peace research agenda about Sri Lanka including intersectionality, social interactionism, semi and unstructured interviews, and interpretative phenomenological analysis. The methods were informed by Sri Lanka’s conflicted social and political spaces. Through the creation of spaces influenced by democracy and rights-based approaches, the methods sought to enable the exercise of participants’ democratic entitlements whilst extinguishing the potential for harm. Through the individual experiences of 22 participants, the methods selected helped to crystalise with greater clarity the structural barriers frustrating people’s agency and the reasons behind their resulting marginalisations. The article affirms that with patience and resources, ground constraints can be overcome, harm mitigated, bias reflexivity and positionality managed, and a set of methods constructed consistent with achieving a peace research agenda.

Far-right narratives of online groups: A systematic review of recent cross-disciplinary research.

Far-right narratives of online groups: A systematic review of recent cross-disciplinary research.

Strategies for the Remediation of Micro- and Nanoplastics from Contaminated Food and Water: Advancements and Challenges.

Micro- and nanoplastic (MNP) pollution is a significant concern for ecosystems worldwide. The continuous generation and extensive utilization of synthetic plastics have led to the widespread contamination of water and food resources with MNPs. These pollutants originate from daily-use products and industrial waste. Remediation of such pollutants is essential to protect ecosystems and human health since these ubiquitous contaminants pose serious biological and environmental hazards by contaminating food chains, water sources, and the air. Various remediation techniques, including physical, chemical, sophisticated filtration, microbial bioremediation, and adsorption employing novel materials, provide encouraging avenues for tackling this worldwide issue. The biotechnological approaches stand out as effective, eco-friendly, and sustainable solutions for managing these toxic pollutants. However, the complexity of MNP pollution presents significant challenges in its management and regulation. Addressing these challenges requires cross-disciplinary research efforts to develop and implement more efficient, sustainable, eco-friendly, and scalable techniques for mitigating widespread MNP pollution. This review explores the various sources of micro- and nanoplastic contamination in water and food resources, their toxic impacts, remediation strategies-including advanced biotechnological approaches-and the challenges in treating these pollutants to alleviate their effects on ecosystems and human health.

Jealousy, Jealousy

In this lightning talk I use an autoethnographic and narrative approach to discuss the generative and obstructive potential of discipline envy and method jealousy in developing research topics in Information Science (IS). I describe how envy and jealousy shaped the development of my doctoral research topic, information-sharing of artist-researchers, and aim to provoke reflection on cross-disciplinary research.