Evolution Of System Research Articles

Emergence and evolution of standardization systems in medical biology laboratories

Abstract Introduction The history of standardization relating to the activities of medical laboratories traces the development of quality system standards in the world, and their evolution. Content In this study, we have included the key benchmarks that represent the stages of the quality system’s evolution in recent decades. Accreditation of medical laboratories has become compulsory in most countries, regarding national or international standards. International acknowledgment of the effectiveness of the results delivered to the many stakeholders, particularly patients and prescribers, is conferred through the use of standards. Summary The ISO 15189 standard represents the latest and most specific international standards for medical laboratories of all types. Outlook More research is necessary to study if laboratory practices reflect the evolution of standards within the medical laboratory field.

Volatile budgets and evolution in porphyry-related magma systems, determined using apatite

Volatile-bearing minerals, such as apatite, Ca5(PO4)3(OH,F,Cl), can record changes in dissolved magmatic volatile species during differentiation and, unlike melt inclusions, are sensitive to the presence of an exsolved fluid phase. Populations of apatite crystals from an individual sample can therefore be used to define the progressive volatile evolution of melt ± fluid during magma differentiation. Despite the importance of fluid chemistry in mineralisation processes, this approach remains relatively underdeveloped for porphyry mineralisation scenarios. Here, we present a model, in the form of a MATLAB app, for melt + apatite ± fluid fractionation that incorporates non-ideal, temperature-dependent KDs for OH-Cl-F exchange and permits an analysis of uncertainty arising from non-unique parameter combinations. We apply the model to apatite from the Corrocohuayco porphyry-skarn system and analyse differences in volatile saturation state and fluid salinity between different units. We find that there is little difference in the overall fluid salinity, and thus copper loads, but that the more primitive unit reached fluid saturation much later (after around 50% crystallisation) than the more evolved units, implying that the melt volatile concentration recorded by the apatites in this unit is not representative of the initial magma volatile budget. This work demonstrates that apatite can be a good alternative means of reconstructing the evolving magmatic fluid salinity within mineralising systems, and linking this to the trace metal load of the melt.

Enhancing PAPR reduction efficiency in MIMO-OFDM systems via selective mapping and metaheuristic algorithms

The relentless evolution of communication systems, driven by the demands of 5G and the impending 6G networks, necessitates heightened data rates and spectral efficiency. orthogonal frequency division multiplexing (OFDM), a form of multicarrier modulation employed in multi-input multi-output (MIMO) systems, stands as a pivotal technology. Yet, OFDM grapples with challenges, notably the peak-to-average power ratio (PAPR) issue. Selective mapping (SLM) has been a favored technique for mitigating PAPR in OFDM, albeit challenged by computational complexities in its pursuit of discovering optimal phase factors. This paper pioneers a transformative approach by integrating metaheuristic algorithms genetic algorithm (GA), particle swarm optimization (PSO), and the innovative fireworks algorithm (FWA) into SLM for PAPR reduction while minimizing computational complexity. Simulation results not only affirm the efficacy of SLM-based techniques but also spotlight the potential of metaheuristic algorithms in addressing PAPR challenges in modern communication systems. The study transcends single-antenna systems, extending to MIMO-OFDM systems based on WiMAX standards, validating the efficacy of these techniques in multi-antenna configurations. Crucially, the FWA, proposed for the first time in this paper, emerges as a robust candidate, striking an enviable balance between computational efficiency and performance, achieving a notable PAPR reduction with a favorable search number.

Enhancing sustainability: Exploring the evolution and dynamics of the grassland social-ecological system in Inner Mongolia over the past 260a

Understanding the intricate relationship between social-ecological systems (SES) coupling and long-term regional sustainable development is critical for effective management strategies. While recent research has predominantly focused on human-earth coupling, there is a dearth of knowledge concerning the transition of grassland SES from one regime to another and the underlying drivers. This study employs a comprehensive SES framework to identify and analyze interactions within typical pastoral areas of Inner Mongolia, aiming to shed light on the evolution of the grassland SES over the past centuries. Our research defines five distinct evolutionary phases in the grassland SES since the mid-Qing Dynasty. Each phase is characterized by unique social and ecological features, providing a nuanced understanding of the system's dynamics. We establish empirical links between the phases and their driving forces and impacts by assessing the main changes between these periods. Specifically, our findings reveal instances of negative cross-scale effects emerging during the evolution process. We observe that unreasonable resource utilization and an inability to curb ecological degradation may lead to unsustainable traps, posing challenges to long-term sustainability. To illustrate, during the transition from Phase 3 to Phase 4 in the late 19th century, a shift towards sedentary pastoralism led to increased land degradation due to intensified grazing practices. This unsustainable trajectory highlights the importance of adaptive management strategies to mitigate such negative consequences. This study contributes insights into the social and ecological management of grassland pastoral areas in China and for global analogous regions. By addressing the identified phases and their associated challenges, our research provides a foundation for crafting sustainable policies and practices to ensure the resilience of grassland SES in diverse geographical contexts.

Recent Advances in Prefabrication Techniques for Biobased Materials Towards a Low-Carbon Future: From Modules to Sustainability

The evolution of building-structure manufacturing systems is propelled by dynamic shifts in formal requirements, prompting heightened research endeavors to enhance manufacturing process efficiency. Integrating renewable materials and technology is pivotal for sustainability, with natural material prefabrication offering promising solutions by reducing carbon footprint. This article comprehensively explores existing natural material prefabrication technologies, delving into their capabilities and assessing their suitability for application in single-family housing within Central and Eastern Europe. Additionally, this article deliberates a thorough assessment of bio-based materials in the construction sector towards a less carbon perspective, with a focus on advancements from 2015 to 2024. A bibliometric analysis of 949 research articles from Web of Science (WOS) and Scopus databases reveals a substantial increase in publications, rising from 29 in 2015 to 175 in 2023 and 17 in 2024 (and still counting), underscoring the growing emphasis on practical applications and technological progress in this field. The research findings offer valuable insights for practitioners, policymakers, and researchers, guiding the integration of renewable materials into traditional construction practices for a more sustainable built environment.

Multi-Agent Distributed Optimal Control for Tracking Large-Scale Multi-Target Systems in Dynamic Environments.

This article considers the problem of motion coordination for a multiagent (MA) network whose goal is to track a large-scale multitarget (MT) system in a region populated by dynamic obstacles. We first characterize a density path which corresponds to the expected evolution of the macroscopic state of the MT system, which is represented by the probability density function (PDF) of a time-varying Gaussian mixture (GM). We compute this density path by using an adaptive optimal control method which accounts for the distribution of the (possibly moving) obstacles over the environment described by a time-varying obstacle map function. We show that each target of the MT system can find microscopic inputs that can collectively realize the density path while guaranteeing obstacle avoidance at all times. Subsequently, we propose a Voronoi distributed motion coordination algorithm which determines the individual microscopic control inputs of each agent of the MA network so that the latter can track the MT system while avoiding collisions with obstacles and their teammates. The proposed algorithm relies on a distributed move-to-centroid control law in which the density over the Voronoi cell of each agent is determined by the estimated macroscopic state evolution of the MT system. Finally, simulation results are presented to showcase the effectiveness of our proposed approach.

Reducing Road Mishaps: A CNN Model for Driver Fatigue Detection

Over the last few decades, there have been substantial developments in a variety of domains, including computer science, artificial intelligence, and machine learning, which has accelerated the evolution and application of intelligent systems in specific areas such as transportation. One way these systems are used in transportation is through fatigue detection, and to enable this technology, Convolutional Neural Networks serve as the foundation on which this system is built. CNNs are frequently employed in computer vision applications because they can automatically extract pertinent features from input data without the need for manual feature engineering. This CNN-based fatigue detection system was built in-order to address the repercussions of fatigued driving by monitoring the driver’s facial features in real-time so as to predict the fatigue levels and send out an alert to restore the driver’s alertness level so as to reduce road mishap. The system relies on visual input from a camera, which sends this input to a fatigue detection program installed on a Raspberry Pi microprocessor and sends out via alerts via a display and audio alerts via a piezoelectric buzzer. The model shows excellent performance, consistently achieving high accuracy, peaking at 97.34% on the 64th epoch, and consistently maintaining high validation accuracy, reaching 96.02% in the 67th epoch, indicating its ability to function effectively.

Evolution of impact-generated hydrothermal systems in basaltic targets on Earth and implications for habitats on Mars

Evolution of impact-generated hydrothermal systems in basaltic targets on Earth and implications for habitats on Mars

A multi-methodological approach to record dynamics and timescales of the plumbing system of Zaro (Ischia Island, Italy)

Determining the time spans of processes related to the assembly of eruptible magma at active volcanoes is fundamental to understand magma chamber dynamics and assess volcanic hazard. This information can be recorded in the chemical zoning of crystals. Nevertheless, this kind of study is still poorly employed for the active volcanoes of the Neapolitan area (Southern Italy), in particular, for Ischia island where the risk is extremely high and this information can provide the basis for probabilistic volcanic hazard assessment. For these reasons, we acquired chemical composition on clinopyroxene crystals erupted at Ischia during the Zaro eruption (6.6 ± 2.2 ka) and performed numerical simulations of the input of mafic magma into a trachytic reservoir, in order to investigate various aspects of pre-eruptive dynamics occurring at different timescales. This event emplaced a ~ 0.1 km3 lava complex, in which the main trachytic lava flows host abundant mafic to felsic enclaves. Previous petrological investigation suggested that mafic magma(s) mixed/mingled with a trachytic one, before the eruption. In this work, the clinopyroxene zoning patterns depict the growth of crystals in different magmatic environments, recording sequential changes occurred in the plumbing system before the eruption. The evolution of the plumbing system involved a hierarchy of timescales: a few hours for magma mingling caused by mafic recharge(s) and likely occurred multiple times over a decade during which a dominant magmatic environment was sustained before the eruption. Such timescales must be considered in volcanic hazard assessment at Ischia and similar active volcanoes in densely populated areas.

JWST/NIRCam Detection of the Fomalhaut C Debris Disk in Scattered Light

Observations of debris disks offer important insights into the formation and evolution of planetary systems. Though M dwarfs make up approximately 80% of nearby stars, very few M dwarf debris disks have been studied in detail—making it unclear how or if the information gleaned from studying debris disks around more massive stars extends to the more abundant M dwarf systems. We report the first scattered-light detection of the debris disk around the M4 star Fomalhaut C using JWST's Near Infrared Camera (NIRCam; 3.6 and 4.4 μm). This result adds to the prior sample of only four M dwarf debris disks with detections in scattered light and marks the latest spectral type and oldest star among them. The size and orientation of the disk in these data are generally consistent with the prior Atacama Large Millimeter/submillimeter Array submillimeter detection. Though no companions are identified, these data provide strong constraints on their presence—with sensitivity sufficient to recover sub-Saturn mass objects in the vicinity of the disk. This result illustrates the unique capability of JWST to uncover elusive M dwarf debris disks in scattered light and lays the groundwork for deeper studies of such objects in the 2–5 μm regime.

An Energy Management System to Schedule the Optimal Participation to Electricity Markets and A Statistical Analysis of the Bidding Strategies over Long Time Horizons

This paper presents a tool that allows to perform an ex-ante estimation of the profitability to participate to the electric energy and service markets for a microgrid or a polygeneration power plant. The tool is the evolution of an Energy Management System (EMS) previously developed by the University of Genoa and Renantis Solutions Srl. Constraints are added to the original EMS to model the Ancillary Service Market (ASM) and Day Ahead Market (DAM) mechanisms in the framework of a planning tool that allows to get estimates of the microgrid/plant costs/revenues over a long-time horizon. As the market outcome strongly depends on the Transmission System Operator (TSO) acceptance/rejection of bids and offers, a statistical approach is proposed. The optimization process is split in two steps: the first one optimally dispatches the energy units and proposes DAM offers and ASM bid and offers over a specified time horizon. Then, a Monte Carlo method is launched; at each extraction the TSO acceptance/rejection of each ASM bid and offer is simulated and there is a second step of optimization in which the energy sources are optimally re-dispatched to meet the bidding program and so to avoid imbalance power exchange that would increase the energy cost. The cost/revenue is thus computed at each extraction. The result is the Probability Density Function of the costs/revenues that allows to estimate the profitability of the participation to the electricity markets. One test performed on a real microgrid shows that the computational time needed to complete one iteration related to a time horizon of one month is approximately 20 seconds. Moreover, the comparison of the outcomes with two independent launches to define the set of bids and offers to be accepted in ASM demonstrates that the statistical analysis allows to avoid misleading conclusions on the costs/revenues. Consequently, the fact that the developed EMS allows to perform a statistical analysis in a reasonable time enables the possibility of comparing multiple scenarios and gives an indication related to the range of cost/revenues in which the microgrid/plant may incur. Finally, the computational efficiency of the proposed approach allows to conclude that the developed EMS is appropriate to perform a long-time horizon (of the order of magnitude of years) analysis and, at the same time, allow to model all the involved components with a high level of details.

Crystal plasticity finite element method investigation of normal tensile deformation anisotropy in rolled pure titanium sheet

Industrial pure titanium with hexagonal close-packed (HCP) crystal structure has a high degree of anisotropy at room temperature. On the mesoscopic scale, this is due to the rolling texture presented by its crystal orientation. Tensile tests were performed on smooth specimens with five angles in the first quadrant at room temperature, and the central deformation region and fracture region were characterized using EBSD and SEM, respectively. The modified Salem anisotropic hardening model is incorporated into the crystal plasticity finite element method (CPFEM) framework in the form of incremental hardening to describe the initial strength and hardening increment evolution of each deformation system of pure titanium. Both slip dislocation and twinning mechanisms are considered in the CPFEM simulation. Three models with different meshing strategies are used to simulate the tensile conditions to capture the evolution of macro and micro variables of pure titanium sheet. The results show that there are anisotropy in stress-strain, system activity, cumulative shear strain, crystal orientation, twin volume fraction, stress triaxiality and Lode parameter. The purpose of this paper is to explore the anisotropy of macro-meso variables in different directions before damage occurs, so as to provide reference for the subsequent construction of related damage models.

Acid-Activated TAT Peptide-Modified Biomimetic Boron Nitride Nanoparticles for Enhanced Targeted Codelivery of Doxorubicin and Indocyanine Green: A Synergistic Cancer Photothermal and Chemotherapeutic Approach.

The evolution of nano-drug delivery systems addresses the limitations of conventional cancer treatments with stimulus-responsive nanomaterial-based delivery systems presenting temporal and spatial advantages. Among various nanomaterials, boron nitride nanoparticles (BNNs) demonstrate significant potential in drug delivery and cancer treatment, providing a high drug loading capacity, multifunctionality, and low toxicity. However, the challenge lies in augmenting nanomaterial accumulation exclusively within tumors while preserving healthy tissues. To address this, we introduce a novel approach involving cancer cell membrane-functionalized BNNs (CM-BIDdT) for the codelivery of doxorubicin (Dox) and indocyanine green to treat homologous tumor. The cancer cell membrane biomimetic CM-BIDdT nanoparticles possess highly efficient homologous targeting capabilities toward tumor cells. The surface modification with acylated TAT peptides (dTAT) further enhances the nanoparticle intracellular accumulation. Consequently, CM-BIDdT nanoparticles, responsive to the acidic tumor microenvironment, hydrolyze amide bonds, activate the transmembrane penetrating function, and achieve precise targeting with substantial accumulation at the tumor site. Additionally, the photothermal effect of CM-BIDdT under laser irradiation not only kills cells through thermal ablation but also destroys the membrane on the surface of the nanoparticles, facilitating Dox release. Therefore, the fabricated CM-BIDdT nanoparticles orchestrate chemo-photothermal combination therapy and effectively inhibit tumor growth with minimal adverse effects, holding promise as a new modality for synergistic cancer treatment.

Modern Industrial Policy and the World Trade Organization

This article surveys the economics of industrial policy as it relates to the World Trade Organization (WTO). Motivated by concern that the modern use of industrial policy is emerging in ways that threaten cooperation in the international trading system, the article begins with the basic historical economic framework for tying industrial policy to underlying market failures. It then introduces the dominant economic understanding of the role played by the WTO, examining the WTO's rules on subsidies (and thus industrial policy), the unease with the evolution of the trading system's subsidy rules, gaps in knowledge, and important data and measurement shortcomings. The main part of the article examines four areas in which modern industrial policy operates differently and has become especially important for the trading system: China, supply chain resilience, supply chain responsiveness, and climate change. The article identifies the evidence to date, open questions, and potential paths forward for economic research to help inform policymakers’ efforts to restore international economic cooperation in trade and industrial policy.

Deciphering Stakeholder Strategies in Electric Vehicle Battery Recycling: Insights from a Tripartite Evolutionary Game and System Dynamics

Given that the global fleet of electric vehicles is expanding rapidly, leading to a surge in demand for power batteries, the significance of battery recycling has come sharply into focus. In this paper, we develop a tripartite evolutionary game model coupled with a system dynamics simulation approach to analyze the behavioral mechanisms of stakeholders in electric vehicle battery recycling and to identify the key factors influencing their strategic transformations. The model involves three key stakeholders: local governments, battery cathode manufacturers, and battery pack manufacturers. Through profit analysis and the formulation of a replicator dynamics system, coupled with the application of Vensim for system dynamics modeling, we analyze the effects of ten crucial exogenous variables on stakeholder strategies. Our research highlights the crucial role of government actions, such as subsidies and penalties, in directing corporate strategies. Notably, excessively high subsidies (over 2.1 million Chinese Yuan) may lead to dependency among cathode manufacturers. Market factors, including increased battery sales and the preference for low-carbon procurement by electric vehicle manufacturers, are shown to significantly motivate cathode manufacturers to adopt recycling strategies and encourage pack manufacturers to develop recyclable designs. Additionally, the introduction of EU battery regulations and the integration of cathode manufacturers into carbon trading schemes have been identified as positive catalysts for strategic shifts, especially for cathode manufacturers, while exerting minimal influence on pack manufacturers. This paper elucidates the intricate interaction of the behavioral patterns and key motivators affecting stakeholder strategies in electric vehicle battery recycling.

Cooperating Graph Neural Networks with Deep Reinforcement Learning for Vaccine Prioritization.

This study explores the vaccine prioritization strategy to reduce the overall burden of the pandemic when the supply is limited. Existing vaccine distribution methods focus on macro-level or simplified micro-level assuming homogeneous behavior within populations without considering mobility patterns. Directly applying these models for micro-level vaccine allocation leads to sub-optimal solutions. To address the issue, we first proposed a Trans-vaccine-SEIR model to incorporate mobility heterogeneity in disease propagation. Then we develop a novel deep reinforcement learning to seek the optimal vaccine allocation strategy for the disease evolution system. The graph neural network is used to effectively capture the structural properties of the mobility network and extract disease features. In our evaluation, the proposed framework reduces 7% - 10% of infections and deaths compared to the baseline strategies. Extensive evaluation shows that the proposed framework is robust to seek the optimal vaccine allocation with diverse mobility patterns. In particular, we find transit usage restriction is significantly more effective than restricting cross-zone mobility for the top 10% age-based and income-based zones under optimal vaccine allocation strategy. These results provide valuable insights for areas with limited vaccines and low logistic efficacy.

A comparative review of subsea navigation technologies in offshore engineering projects

Subsea navigation technologies play a critical role in enhancing precision and efficiency in offshore engineering projects. This comparative review examines the evolution and application of subsea navigation systems, with a focus on improving precision in offshore construction and surveying. The study evaluates various subsea navigation technologies, including acoustic positioning systems, inertial navigation systems, and optical imaging systems, highlighting their capabilities and limitations. The review begins by discussing the historical development of subsea navigation technologies, tracing their evolution from early acoustic systems to modern integrated solutions. It then explores the key components and operation principles of each technology, providing insights into their functionalities and suitability for different offshore applications. The study also examines the challenges and advancements in subsea navigation, including issues related to signal interference, accuracy, and real-time data processing. It discusses how these challenges have been addressed through technological innovations, such as improved sensor technologies and advanced data fusion algorithms. Furthermore, the review assesses the practical application of subsea navigation technologies in offshore engineering projects, including pipeline installation, subsea infrastructure maintenance, and underwater surveying. It analyzes case studies and industry practices to illustrate the effectiveness of these technologies in improving precision, reducing costs, and mitigating risks in offshore operations. Overall, this comparative review provides a comprehensive overview of subsea navigation technologies in offshore engineering projects. It highlights the evolution, capabilities, and applications of these technologies, emphasizing their role in enhancing precision and efficiency in offshore construction and surveying. The study concludes with recommendations for future research and development to further improve the performance and reliability of subsea navigation systems in offshore operations.

The synergistic evolution of supply-demand composite system for airport green development: A case study in Guangzhou Baiyun International Airport, China.

Given the pressing requirements for sustainable development in civil aviation, conducting a synergistic evolution analysis of the supply and demand aspects in the airport green development holds great significance. This analysis helps achieve sustainable airport development and facilitates the green transformation of civil aviation development. Taking a collaborative learning approach and utilizing historical data from Guangzhou Baiyun International Airport spanning 2008 to 2019, the supply-demand composite system for airport green development was deconstructed into two subsystems-demand and supply-and relevant evaluation index systems were established in this paper. A screening and optimization model of supply and demand synergy indicators for airport green development was constructed, and it was solved using a simulated annealing genetic algorithm. The Haken model was constructed to analyze the synergistic evolutionary relationship of the composite system of supply and demand for green airport development in two stages. The results indicate a shift in the order parameter of the co-evolution of the supply-demand composite system at Guangzhou Baiyun International Airport, moving from the demand subsystem in the first stage (2008-2015) to the supply subsystem in the second stage (2016-2019). The co-evolution of the airport supply-demand composite system has entered a new stage, but has not reached a high level of synergy. The study not only contributes theoretically by explaining the interaction mechanism between supply and demand for airport green development, but also offers targeted suggestions for achieving high-quality synergistic evolution of supply and demand for airport green development.

Vietnam tourism at the crossroads of socialism and market economy

Purpose Vietnam has repositioned itself from a war-torn country to a popular tourist destination. Although research on Vietnam tourism has grown in number, a macro analysis of national tourism governance and policies has largely been missing. Design/methodology/approach This synthesis paper offers a systemic analysis of Vietnam’s tourism accommodating intensified government intervention and dramatic market changes in recent decades. The authors offer a chronological analysis of tourism development along with the major political and economic turns of the country. Findings The patterns of tourism development reflect a compromise between centralization and decentralization of the governance system and a trade-off between economic and social objectives of development. Balancing these opposites, the internal strength of the domestic market and the resilience of communities and businesses become key assets for growth in circumstances where the socialist market economy continues to inform the current and future development of the industry. Research limitations/implications Although the case of Vietnam is unique, the adaptive mechanism of the tourism industry highlighted in this paper offers a useful lesson for other developing countries. The research addresses tourism in the political economy in developing countries, which is valuable for researchers, policy analysts as well as practitioners in tourism. Practical implications The practical contribution of the study is derived from authors’ academic and industrial backgrounds. Findings from the study serve as a useful reference for those who embark on the study of tourism governance and policy-making in developing countries and problems associated with the economic transitional process. Those problems of the disparity between centralization and decentralization of the political system might not be only significant in Vietnam, but also prevail in developing countries. Thus, this study offers a point of departure for future empirical and comparative research on the kindship of tourism and political economy in a full scale. Social implications The transitional economy as viewed through the tourism industry is prominently presented in the “evolutionary” approach to the transitional economy, which exhibits several unique features: the transition from a centrally planned (command) economy to a market economy and the manifestations of a socialist orientation in the modern economic management system (Vuong et al., 2019). While data from this study is mainly illustrative of the first point, the transition from a planned economy to a market economy, the second characteristic, the manifestation of a social orientation has only slightly been addressed and will need further elaboration in a future study. While Vietnam’s tourism positions itself in a socialist market-oriented economy might set a unique case, the study highlights the politics of tourism is shaped by the politico-economic system. The authors conclude that the adaptation of Vietnam tourism to a socialist market-orientated economy is better perceived as a social evolution achievement rather than a feature of capitalism. Originality/value The latest study on tourism governance (Bui et al., 2022) has outlined the evolution of the tourism administrative system and markets in the country; however, linkages of tourism to the broader political economic system have yet to be addressed. Addressing this gap, the authors carry out analysis of policies and governance from the insider’s viewpoint, when team members have been involved in numerous tourism planning and development projects, both on international and national scales. The practical experience along with thorough review of literature and statistical data contributes to shaping a fresh understanding of tourism in a transitional economy.

Evolution and Dynamics of Technology Based Accounting Information: A Bibliometric Study

This bibliometric study delves into the evolution and dynamics of technology-based accounting information systems (AIS), exploring the intersection of technological advancements and accounting practices. The integration of technology in accounting has catalyzed significant transformations, reshaping how financial data is managed, analyzed, and reported. Through a comprehensive analysis of 780 publications spanning from 1977 to 2024, this research uncovers key trends, influential works, and emerging themes in the field of technology-based AIS. Utilizing bibliometric techniques such as co-citation analysis and network visualization, the study provides insights into the collaborative landscape, thematic clusters, and temporal trends within the domain of technology-based AIS research. The findings shed light on the evolution of AIS research, highlighting the increasing relevance of emerging technologies such as artificial intelligence and blockchain, while also identifying potential areas for future investigation.