Cooperative Networks Research Articles

Substituent Effects on Cooperativity in Three-Component H-Bond Networks Involving Phenol-Phenol Interactions.

Cooperativity between H-bonding interactions in networks is a fundamental aspect of solvation and self-assembly in molecular systems. The interaction of a series of bisphenols, which make an intramolecular H-bond between the two hydroxyl groups, and quinuclidine was used to quantify cooperativity in three-component networks. The presence of the intramolecular H-bond in the bisphenols was established by using 1H NMR spectroscopy in solution and X-ray crystallography in the solid state. The interactions with quinuclidine were investigated using UV-vis and 1H NMR titrations, which show that the intramolecular hydrogen bonds persist in the 1:1 complexes. By varying substituents on one of the phenol groups, it was possible to measure the effect of changing the strength of the intramolecular H-bond between the hydroxyl groups on the strength of the intermolecular H-bond with quinuclidine. Strong positive cooperativity was observed between the two interactions, with increases in binding free energy of up to 16 kJ mol-1. By varying substituents on the other phenol group, which makes both an intramolecular H-bond and an intermolecular H-bond in the complex, it was possible to measure how the properties of this central hydroxyl group modulate cooperativity between the interactions with the other two functional groups. Changing the polarity of this phenol had no effect on the measured cooperativity. The results indicate that cooperativity in H-bond networks can be understood as a polar interaction between two remote functional groups that is damped by a central functional group. The extent of damping is quantified by cooperativity parameter κ, which is 0.33 for the hydroxyl group and appears to be an intrinsic property of the geometry or polarizability of the functional group rather than polarity.

Menavigasi Era Disrupsi: Menuju Transformasi Manajemen Mutu Pendidikan Islam yang Adaptif dan Inovatif

This study aims to determine the implications of the transformation of Adaptive and Innovative Islamic Education Quality Management in the era of disruption. This research uses a qualitative method with a case study approach at the Ulya Muadalah Education Unit (SPM) school institution at the Darussalam Blokagung Islamic Boarding School. Data collection techniques were collected through in-depth interviews, participatory observation, and document analysis, with the main informants consisting of principals, teachers, administrative staff and students. While data analysis used thematic analysis method with data coding to identify key themes that emerged from interviews, observations, and document analysis. The results showed that the Transformation of Adaptive and innovative islamic education quality management in the era of disruption included collaboration and cooperation networks, teacher professional development and 21st Century Skills-Based curriculum development. collaboration and cooperation networks between the Ulya Muadalah Education Unit (SPM) with madrasah diniyyah Al Amiriyyah, SPM Wustho, and Ma'had Aly institutions have proven to be an effective strategy in improving the quality of education and academic competence of students while teacher professional development is carried out with activities such as consortium, shawir and Batsul Masail

Optimizing Spectrum Efficiency With MIMO NOMA PD Approach in a 5G Cooperative Spectrum Sharing Environment

ABSTRACTThe fifth generation (5G) of cellular communication networks has introduced various advanced technologies to address the increasing demand for higher data rates and improved spectrum utilization. One of these technologies, non‐orthogonal multiple access (NOMA), has gained significant attention due to its ability to enhance spectral efficiency by allowing multiple users to share the same time‐frequency resource block. NOMA affords a number of advantageous features including increased spectrum efficiency (SE). It comes in various forms, such as power‐domain (PD) NOMA and code‐domain (CD) NOMA. This paper attentions mainly on enhancing the SE of downlink (DL) PD‐NOMA in a 5G cooperative spectrum sharing environment using single input single output (SISO), massive MIMO (M‐MIMO), and multiple input multiple output (MIMO). Two methods are approached here. In the first one, the NOMA handlers access the free/unconstrained channels using competing channel (C‐Ch) approach, whereas the next one uses dedicated channel (D‐Ch) approach. Five users are considered at distances of 1000, 800, 600, 400, and 200 m from the base station (BS) with different power allocation coefficients at transmitting power of 40 dBm and bandwidth of 70 MHz. Quadrature phase shift keying (QPSK) is used with successive interference cancellation (SIC) at the receiver side and superposition coding (SC) at the transmitter side under frequency selective Rayleigh fading environment. The PD DL NOMA system's results demonstrated that combining 32 × 32 MIMO, 64 × 64 MIMO, and 128 × 128 M‐MIMO in a single cell and the same network with cooperative cognitive radio network (CoCRN) significantly improved the SE reliability. The user Ur5 produces an optimal SE performance of 3.753 bps/Hz/cell for PD DL NOMA with SISO, 5.77 bps/Hz/cell for CoCRN PD DL NOMA with SISO using C‐Ch, and 7.45 bps/Hz/cell for CoCRN DL PDNOMA with SISO using D‐Ch with a 40 dBm transmitting power. Furthermore, the SE for Ur5 (nearest user) was increased to 64%, 67%, and 69%, respectively, using PD‐NOMA with 32 × 32 MIMO, PD‐NOMA with 32 × 32 MIMO using C‐Ch, and DL NOMA PD with 32 × 32 MIMO using D‐Ch. DL PD‐NOMA with MIMO(64 × 64) using D‐Ch improved the SE rate by 77% having transmission power of 40 dBm in comparison with the SE outcome for DL PDNOMA with SISO; however, DL PD‐NOMA with MIMO (64 × 64) most dramatically upgraded the SE rate for Ur5 by 73%. Using C‐Ch and CoCRN DL PD‐NOMA with MIMO (64 × 64), the SE performance was boosted by 76%. The best user, Ur5, had an 82% improvement in SE performance when DL PD‐NOMA with M‐MIMO (128 × 128) was compared to DL NOMA with SISO. With a 40 dBm transmission power, CoCRN DL NOMA with 128 × 128 M‐MIMO using C‐Ch showed an 88% improvement, whereas CoCRN DL PD‐NOMA with M‐MIMO (128 × 128) using D‐Ch experienced an 89% improvement.

Intrafirm collaboration network dynamics, external cooperation network embeddedness, and firm knowledge search

ABSTRACT In the context of open innovation, firms urgently expand knowledge search and acquisition externally, forming complex interactions between internal networks and their knowledge exploration behaviours. However, prior research has overlooked network dynamics and treated internal networks as static. Drawing upon social network theory and the knowledge-based view, our study constructs a theoretical model that links intrafirm collaboration network dynamics with knowledge search within firms. We also investigated external contextual mechanisms such as the relationship strength, relationship breadth, and network centrality of corporate external networks. These moderate the relationship between intrafirm collaboration network dynamics and firms’ knowledge search. We empirically test the hypotheses using data from listed firms in the Chinese computer, communication, and electronic equipment manufacturing industry (C39) between 2014 and 2021. The results indicate that the intrafirm collaboration network dynamic has an inverted U-shaped effect on firms’ knowledge search breadth and depth. Relationship strength and network centrality weaken these effects.

A Literature Analysis of Coastal Zone Carbon Cycle Research Based on Knowledge Graphs

This paper conducts a comprehensive literature analysis of coastal zone carbon cycle research utilizing CiteSpace software to visualize the intellectual structure and evolution of the field from 1999 to 2025. The study categorizes various coastal ecosystems into 12 groups, examining 12,460 documents sourced from the Web of Science databases. The analysis reveals publication dynamics, identifies key publication types, and maps the research topics and cooperation network of participating countries, with a particular focus on the United States and China as leading contributors. The paper also highlights influential authors and thematic clusters within the literature, such as dissolved organic matter, blue carbon, and ocean acidification. The analysis provides a systematic overview of the coastal carbon cycle research field, informing future research directions and policy decisions related to coastal carbon management and climate change mitigation strategies. The study concludes that while significant advancements have been made, there are still considerable gaps and challenges that need to be addressed, emphasizing the potential of coastal ecosystems in mitigating climate change and promoting sustainable development.

Green Energy Co-operation Mechanisms Between China and Countries along the Belt and Road: The Role of Chinese Local Governments and International Organizations

As global climate issues have intensified, promoting green energy has become the key to solving the problem. This paper explores the role of Chinese local governments and international organizations in promoting green energy cooperation under the Belt and Road Initiative (BRI). It highlights the importance of such partnerships for accelerating energy transitions in underdeveloped countries. The study argues that local governments in China have translated central policies into local action, supporting the development of green energy projects along the Belt and Road through policy responses, promoting local projects, and mobilizing local businesses to invest. At the same time, this article classifies the international organizations participating in the BRI as platform-type organizations and participatory organizations. The former provides effective financial tools for Belt and Road green energy projects, and the latter uses existing influence to promote the construction of an international discourse on a consensus-driven green Belt and Road. Effective green energy cooperation requires a multi-level approach that includes policy adaptations, infrastructure construction, and knowledge-sharing mechanisms. Research on the role and influence of actors within cooperation networks and the relationships among multiple actors may provide a reference for broader green cooperation on a global scale.

Enhancing System Capacity Through Joint Space‐Ground Multi‐Beam Coordination for LEO Satellite Systems

ABSTRACTDue to the long transmission distance of the constellation network represented by the low‐orbit satellite system, the satellite‐to‐ground link is subject to large path loss and limited communication performance. This paper uses multi‐satellite and multi‐beam joint transmission technology to form a virtual multiplex network with ground multi‐antenna terminals (Multiple‐Input Multiple‐Output [MIMO] system). However, due to the high‐speed movement of satellites, the topology of the MIMO system is unstable, which in turn affects the stability of the system throughput. This article proposes two inter‐satellite cooperation modes to improve the stability of MIMO system capacity. The first method is to optimize the channel capacity by rationally allocating the beam power of the gateway station so that the gateway station can achieve transparent forwarding through satellites. The second method rotates the angle of the user's receiving antenna to combat channel changes caused by changes in satellite position. Simulation results show that both methods can effectively improve the minimum channel capacity. Transparent forwarding can increase the capacity by about 22.7%, while the rotating antenna can still improve the performance gain by at least 36.3% even with a limited rotation angle. This research contributes to the development of stable and efficient communication systems in satellite‐ground cooperative networks.

Density amplifiers of cooperation for spatial games

Spatial games provide a simple and elegant mathematical model to study the evolution of cooperation in networks. In spatial games, individuals reside in vertices, adopt simple strategies, and interact with neighbors to receive a payoff. Depending on their own and neighbors' payoffs, individuals can change their strategy. The payoff is determined by the Prisoners' Dilemma, a classical matrix game, where players cooperate or defect. While cooperation is the desired behavior, defection provides a higher payoff for a selfish individual. There are many theoretical and empirical studies related to the role of the network in the evolution of cooperation. However, the fundamental question of whether there exist networks that for low initial cooperation rate ensure a high chance of fixation, i.e., cooperation spreads across the whole population, has remained elusive for spatial games with strong selection. In this work, we answer this fundamental question in the affirmative by presenting network structures that ensure high fixation probability for cooperators in the strong selection regime. Besides, our structures have many desirable properties: (a) they ensure the spread of cooperation even for a low initial density of cooperation and high temptation of defection, (b) they have constant degrees, and (c) the number of steps, until cooperation spreads, is at most quadratic in the size of the network.

The evolution and hotspots of radioactive iodine therapy in hyperthyroidism: a bibliometric analysis.

Hyperthyroidism, a prevalent endocrine disorder, disrupts metabolic balance and cardiovascular health, affecting millions globally. Radioactive iodine (RAI), a treatment for hyperthyroidism, employs high-energy beta particles to reduce thyroid tissue, lowering volume and hormone levels. This study utilizes bibliometric analysis to outline RAI's evolution and identify hotspots in hyperthyroidism treatment. A total of 2904 articles and reviews published between 1981 and 2023 were retrieved from the Web of Science Core Collection using the research strategy. Bibliometric analyses, employing VOSviewer and CiteSpace, were performed to visualize the cooperation network, evolution, and hot topics. Annual publications rose in waves, 2904 papers from 2564 institutions, and 84 countries. The USA led, contributing the largest share, with the journal Thyroid dominating publication. The University of Pisa contributed the most articles. Co-occurrence analysis classified keywords into five clusters: treatment mechanism, safety, effectiveness assessment, individualized radioactive dosage, and management. The development of RAI therapy for hyperthyroidism can be divided into three stages: safety and efficacy assessment, personalized treatment plans, and treatment of drug-resistant and surgery-resistant hyperthyroidism. Attention to RAI in hyperthyroidism should be significantly increased. It is necessary to establish collaborations between authors, countries, and institutions to promote the development of this field. Recent research has focused on personalized radioactive dosage formulation and follow-up. Future studies are likely to concentrate on drug-resistant and surgery-resistant hyperthyroidism, which is also worthy of investigation. These findings provide a new perspective on the study of RAI in hyperthyroidism, potentially contributing to the improvement of the quality of life for patients with hyperthyroidism.

Multiple PUE Attack Detection in Cooperative Mobile Cognitive Radio Networks

The Mobile Cognitive Radio Network (MCRN) are an alternative to spectrum scarcity. However, like any network, it comes with security issues to analyze. One of the attacks to analyze is the Primary User Emulation (PUE) attack, which leads the system to give the attacker the service as a legitimate user and use the Primary Users’ (PUs) spectrum resources. This problem has been addressed from perspectives like arrival time, position detection, cooperative scenarios, and artificial intelligence techniques (AI). Nevertheless, it has been studied with one PUE attack at once. This paper implements a countermeasure that can be applied when several attacks simultaneously exist in a cooperative network. A deep neural network (DNN) is used with other techniques to determine the PUE’s existence and communicate it with other devices in the cooperative MCRN. An algorithm to detect and share detection information is applied, and the results show that the system can detect multiple PUE attacks with coordination between the secondary users (SUs). Scenarios are implemented on software-defined radio (SDR) with a cognitive protocol to protect the PU. The probability of detection (PD) is measured for some signal-to-noise ratio (SNR) values in the presence of one PUE or more in the network, which shows high detection values above 90% for an SNR of -7dB. A database is also created with the attackers’ data and shared with all the SUs.

A merging approach for hole identification with the NMM and WOA-BP cooperative neural network in heat conduction problem

Defect identification is an important issue in structural health monitoring. Herein, originated from inverse techniques, a merging approach is established by the numerical manifold method (NMM) and whale optimization algorithm-back propagation (WOA-BP) cooperative neural network to identify hole defects in heat conduction problems. On the one hand, the NMM can simulate varying hole configurations on a fixed mathematical cover, which eases the generation of “big data” for the training of neural network to a large extent. On the other hand, the WOA, a global optimization algorithm, is adopted to optimize the initial weights and thresholds of the BP neural network to alleviate its frequently encountered local optimum phenomenon. The boundary temperatures of sampling points by the NMM and the associated hole geometries are used for the learning of WOA-BP neural network, which is then applied to predict the hole defects. Numerical examples concerning the detection of circular/ elliptical holes demonstrate that the proposed method possesses higher accuracy and satisfying robustness in holes prediction compared with standard BP network under the same condition. The present work provides a convenient pathway and great potential in application of structural health monitoring.

Research trends and hotspots of the applications of single-cell RNA sequencing in cardiovascular diseases: a bibliometric and visualized study.

Cardiovascular diseases (CVDs) are the leading causes of death globally. The use of single-cell RNA sequencing (scRNA-seq) in CVDs has gained significant attention in recent years, and there is a growing body of literature on the subject. However, a thorough and impartial analysis of the existing state and trends of scRNA-seq in CVDs is lacking. This study aims to examine the development of scRNA-seq in CVDs using bibliometric and visualized analysis. Global publications on scRNA-seq and CVDs from 2009 to 2023 were extracted from the Web of Science Core Collection (WoSCC) database. The R package "Bibliometrix", VOSviewer, and CiteSpace were employed to perform a bibliometric study. After applying the screening criteria and omitting documents that met exclusive criteria, this bibliometric study included 1170 papers. These were authored by 8595 scholars from 1565 organizations in 57 countries or regions and were published in 369 journals, with 51073 co-cited references included. Publication volume, citations, and relative research interest index focusing on this field have dramatically increased since 2019. The cooperation network showed that the USA, the Chinese Academy of Medical Sciences, and Qingbo Xu were the most active countries, institutes, and authors in this field, respectively. Circulation Research was the journal with the most publications, which was confirmed to be the top core source by Bradford's law. The hotspots and emerging direction in the field manifest in (1) three CVDs (atherosclerosis, myocardial infarction, and heart failure) and (2) three cell types (macrophage, fibroblast, and smooth muscle cell). Our study provides a systematic visualization of the research literature on scRNA-seq in CVDs and provides guidance and reference for understanding the current research status and discovering new research directions.

Oxytocin in Human Social Network Cooperation.

Human society is organized in structured social networks upon which large-scale cooperation among genetically unrelated individuals is favored and persists. Such large-scale cooperation is crucial for the success of the human species but also one of the most puzzling challenges. Recent work in social and behavioral neuroscience has linked human cooperation to oxytocin, an evolutionarily ancient and structurally preserved hypothalamic neuropeptide. This review aims to elucidate how oxytocin promotes nonkin cooperation in social networks by reviewing its effects at three distinct levels: individual cooperation, the formation of interpersonal relationships, and the establishment of heterogeneous network structures. We propose oxytocin as a proximate mechanism for fostering large-scale cooperation in human societies. Specifically, oxytocin plays an important role in facilitating network-wide cooperation in human societies by 1) increasing individual cooperation, mitigating noncooperation motives, and facilitating the enforcement of cooperative norms; 2) fostering interpersonal bonding and synchronization; and 3) facilitating the formation of heterogeneous network structures.

Bacterial and fungal diversity, community composition, functional groups, and co-occurrence network succession in dryland and paddy soils along a 3000-year chronosequence

There is a limited understanding of soil microbial community successional trajectories during dryland and paddy soil long-term management after wetland reclamation. We examined the effects of long-term reclamation on the microbial diversity, community composition, functional groups, and co-occurrence network in dryland and paddy soils using a 3000-year soil chronosequence established in the floodplain of the middle and lower Yangtze River, employing the “space-for-time” method and 16S rRNA and ITS amplicon sequencing. Over time, reclaimed land experienced varying losses in microbial richness and diversity, with paddy soils exhibiting higher alpha diversity than drylands due to greater resources and ecological niches. Proteobacteria dominated drylands, Chloroflexi prevailed in paddy soils, and fungal communities in both land-use types were primarily Ascomycota and Basidiomycota. Functional predictions showed higher chemoheterotrophy and aerobic_chemoheterotrophy in dryland soils and more animal_parasites_or_symbionts and dung_saprotrophs in paddy soils. During the 2000–3000 year reclamation, the abundance of pathogens increased, posing risks to agricultural production. Co-occurrence network analysis indicated that, compared to paddy soils, dryland soils may form a more complex and stable microbial cooperative network. Soil organic carbon and pH influenced microbial communities in drylands, while bulk density and cation exchange capacity were crucial in paddy soils. Partial least squares path modeling indicated that reclamation duration impacts microbial network complexity and diversity, with soil properties regulating paddy soil microbial networks. These findings broaden our understanding of microbial community succession in dryland and paddy soils after long-term wetland reclamation, supporting soil health and sustainable agriculture.

Adaptive neural boundary control for multi-agent manipulators system with uncertainties through cooperative disturbance observers network

This paper addresses vibration control problem of multi-agent flexible manipulators systems in the presence of simultaneous uncertainty and unknown external disturbance. Particularly, the goal is to suppress vibration of both flexible link and joint angular. In this paper, the dynamic model of the considered flexible manipulator is described by the fourth order partial differential equation. Without control, the system is unstable and vibrate constantly due to initial states, the external unknown disturbances and system uncertainties. To compensate the uncertainty in each agent, the neural networks are employed and novel adaptation laws are developed to update weighting parameters in the neural networks. While for the compensation of the external disturbance a cooperative network of disturbance observers is proposed to enhance the observation reliability. With the resulting estimations of uncertainties and the unknown disturbance, adaptive distributed boundary controllers are derived to suppress vibration in-domain and keep joint angular position to zero. The closed-loop system is proven to be uniform ultimately bounded through Lyapunov stability theory. Numerical simulations result shows that compared with the proportional–derivative control, the proposed method almost reduces all overshoot and steady-state error.

ANALYSIS OF STRATEGY WOMEN'S COOPERATIVE POTENTIAL DEVELOPMENT BASED ON HUMAN RESOURCES

This study is a qualitative study, aimed at analyzing the development of Human Resources in women's cooperatives in Lumajang Regency using Strength, Weakness, Opportunity, and Threats analysis, so that it becomes a consideration in determining the strategy for developing women's cooperative business. The target of this study was 54 women's cooperatives. The research used were primary and secondary data’s. The data collection technique used a questionnaire. The results of this study indicate that the strengths of women's cooperatives in Lumajang Regency are the level of knowledge and experience of cooperative managers, both with an average service period of 8 years. The level of education of the management is good, generally high school or equivalent. The internal capital and financial management of the cooperative is good, namely by paying attention to the principles of good and healthy governance. Women's Cooperatives strive to maximize their strengths as supporting factors for improving performance so that the weaknesses of Women's Cooperatives can be minimized. The results of the IFAS matrix analysis in the form of opportunity factors show that the potential for cooperative development due to the presence of a third party to establish partnerships through the support of information technology and government policies is very good. There is potential for business network cooperation between women's cooperatives at the regional and area levels, opportunities through government programs in the development of women's cooperatives and ease of licensing in the formation of new cooperatives as well as an increasingly open and conducive cross-sectoral business climate.

Framing matters: LGBTQIA+ organisations’ boundary spanning within and across collective action fields

Western-based LGBTQIA+ mobilisations have often been described as both internally fragmented and isolated from other social struggles. However, recent studies show that LGBTQIA+ (lesbian, gay, bisexual, trans*, queer, intersex, asexual/aromantic and other) organisations have increasingly used social media to span organisational boundaries by networking with other groups and framing common concerns. This article addresses these concerns by examining the interplay between digital networking and collective framing in different socio-political contexts and over time. The investigation focuses on the collective action events promoted on Facebook by LGBTQIA+ organisations located in Milan and Madrid between 2011 and 2020. After mapping the socio-semantic networks resulting from the promotion of the collective action events, the article analyses the brokerage roles played by different frames. Our findings show that while social media facilitates the creation of both within- and cross-field cooperative networks, framing congruence is necessary for transforming occasional cross-field network choices into sustained efforts to span boundaries and form intersectional alliances.

The evolution of doctrinal approaches to international police cooperation in the framework of the European Union

The article is devoted to the relevant in the science of international law the issue of evolution of doctrinal approaches to international police cooperation within the European Union. The literature on this issue is being investigated, on the basis of which observations of the nature of internal security management in the EU are made. The connection and the mutual stress between police integration and internal EU security policies are investigated on the one hand and the state sovereignty and the state monopoly to use force on the other. The evolution of the public sphere in the management of security policies is traced. The role of politicization in the management of international police cooperation is outlined. It is noted that politicization and public discourse can be both a favorable factor and an obstacle to police integration. The article highlights the evolution of management methods through soft and rigid law, as well as the growing role of internal and supranational actors in the management of police integration. The influence of differentiated informal networks on internal security management is noted. There is a trend available in the theoretical literature to mix powers through the generalization of cooperation networks. The issue of domestic and international internal security management is considered. It is concluded that not the state, but the network of police professionals determine the level of interest of states in integration in the field of international police cooperation. It is stated that a large array of research focuses on the institutionalization of the process of managing international police cooperation, while at the same time, relatively little work was carried out on the specific impact of differentiated networks on security management and the results of EU security policy. The asymmetry and variability of the integration preferences of states in the field of internal security are investigated. It is noted that this issue is best considered in the framework of the theory of functionalism. Such explanations are based on responding to common threats and functionality of ordinary institutions that allow to achieve certainty about the expected behavior of states.

Artificial intelligence and microbiome research: Evolution of hotspots, research trends, and thematic-based narrative review.

Artificial intelligence (AI) and microbiome have emerged in recent years as transformative fields with far-reaching implications for various biomedical domains. This paper presents a comprehensive bibliometric analysis examining the intersection of AI and the microbiome (AIM). The study aims to provide information on this interdisciplinary field's research landscape, trends, and emerging topics. Using a systematic approach, data-driven studies were extracted from the Scopus database on 23 November 2023 and analyzed using the VOSviewer and Bibliometrix applications. The regression coefficient of 0.94 and the yearly growth rate of 7.46% in AIM production indicate a consistent increase over time. Identification of essential contributors, organizations, and nations illuminated cooperative networks and research hotspots. The trend themes are the gut microbiome, disease prediction, machine learning, transfer learning, categorization, big data, artificial neural networks, chronic rhinosinusitis, epidemiology, COPD, and bronchoalveolar lavage. These hot issues in AIM reflect the present emphasis on research and developments in our knowledge of the microbiome's function in health, sickness, and individualized treatment. The findings give researchers, policymakers, and industry experts a thorough picture of the research environment and guide future paths in AIM's fascinating and promising subject.

Navigating the Fourth Industrial Revolution: insights from a comprehensive bibliometric study on Industry 4.0

Abstract The purpose of this study is to outline the current state of research and development in Industry 4.0 by highlighting key topics, cooperative networks, and emerging trends that characterize this ground-breaking stage of manufacturing and technology. The article answers the question what are the key keywords, countries, collaboration networks and most frequently occurring terms in Industry 4.0 research, and what conclusions can be drawn from the bibliometric analysis regarding their frequency, strength of connections and mutual relationships. With a focus on the incorporation of digital technology into manufacturing processes, the article aims to provide a detailed overview of the international initiatives driving the fourth industrial revolution. This study uses bibliometric analysis to look at 4,981 scientific papers from 2020 to 2024 that are available in the Scopus database. The text of these articles is carefully examined, with an emphasis on titles, abstracts, and keywords, in order to map out the network of co-authorships and the frequency of certain terminologies. The VOSviewer program was used to provide a network visualization, offering a pictorial depiction of the connections of coauthoring nations and the phrases that are shared across the corpus of work. The results show a strong and complex web of global partnerships, suggesting a broad dedication to pushing the boundaries of Industry 4.0. Five significant co-authorship clusters were found, demonstrating the prominent significance that certain nations have played in various Industry 4.0 research domains. Key phrases like “digital transformation,” “smart manufacturing,” “machine learning,” and “internet of things” were used a lot, highlighting the importance of digitization and smart manufacturing technology. This publication offers a comprehensive statistical and visual study of the worldwide research dynamics in Industry 4.0, making it a unique contribution to the body of knowledge. Understanding the complex nature of the fourth industrial revolution is made easier with its mapping of cooperative networks and thematic goals as well as its emphasis on the discourse’s essential place for sustainability.