Search Results (1,904)

The agglomeration of the Unmanned Aerial Vehicle (UAV) industry is a key driver of the low-altitude economy. To understand how UAV industrial agglomeration emerges across cities with different socioeconomic foundations, this study investigates its dynamic configurational pathways. It develops an analytical framework that integrates the institutional environment, market conditions, and knowledge-based capabilities. Using panel data for 280 Chinese cities from 2017 to 2023, we apply panel data qualitative comparative analysis (QCA) to identify configurational pathways toward UAV industrial agglomeration. Seven socioeconomic conditions are considered: science and technology expenditure, policy support, infrastructure, social consumption level, financial development, urban innovation capacity, and human capital. The results show that UAV industrial agglomeration arises from the joint effects of multiple conditions, not from any single factor. We identify six pathways that are grouped into three archetypes: institution–knowledge-driven, institution–market-driven, and multidimensional synergistic configurations. The dominant pathways shift over time and differ across city sizes. These findings provide macro-level evidence on the mechanisms underpinning UAV industrial agglomeration. They also offer implications for strengthening the UAV industrial ecosystem. Full article

Onchocerca flexuosa is a vector-borne filarial nematode infecting red deer (Cervus elaphus) throughout Europe. Despite numerous reports from Central, Northern, and Southern Europe, its occurrence in South-Eastern Europe has remained largely undocumented. This study provides the first molecularly confirmed report and the first systematic epidemiological assessment of O. flexuosa in red deer in Croatia. During the 2024–2025 hunting season, 110 legally harvested red deer from central Croatia were examined for subcutaneous nodules. Nodules were evaluated morphologically, and adult nematodes were identified and confirmed by sequencing of a fragment of the mitochondrial cytochrome c oxidase subunit I (COI) gene. Subcutaneous nodules were detected in 53.6% (59/110) of examined animals. O. flexuosa was confirmed in 52 deer, corresponding to an overall prevalence of 47.3%. Co-infection with Hypoderma diana occurred in 21.2% of infected animals. Sequence similarity ranged from 96.37% to 99.85% compared to published European O. flexuosa isolates. Phylogenetic analysis placed Croatian sequences within the established European lineage, without evidence of regional genetic divergence. The observed prevalence falls within the intermediate range reported across Europe and indicates stable local transmission. These findings close an important geographical knowledge gap and demonstrate that nodular onchocercosis is established in red deer populations in South-Eastern Europe. Full article

The proliferation of Internet of Things (IoT) devices has intensified the need for efficient real-time anomaly and intrusion detection, making the selection of an appropriate Complex Event Processing (CEP) engine a critical architectural decision for security-aware data pipelines. Python-based CEP frameworks offer compelling advantages through the seamless integration with data science and machine learning ecosystems; however, rigorous comparative evaluations of such frameworks under realistic IoT security workloads remain absent from the literature. This study presents the first systematic comparative evaluation of Faust and Streamz—two Python-native CEP engines representing fundamentally different architectural philosophies—specifically in the context of IoT network intrusion detection. Faust was selected for its actor-based stateful processing model with native Kafka integration and distributed table support, while Streamz was selected for its reactive, lightweight pipeline design targeting high-throughput stateless processing, making them representative of the two dominant paradigms in Python stream processing. Although both engines target different application niches, their performance characteristics under realistic CEP workloads have never been rigorously compared, leaving practitioners without empirical guidance. The primary evaluation employs an IoT network intrusion dataset comprising 583,485 events from 83 heterogeneous devices. To assess whether the observed performance characteristics are specific to this single dataset or generalize across different workload profiles, a secondary IoT-adjacent benchmark is included: the PaySim financial transaction dataset (6.4 million records), selected because its event schema, fraud-pattern temporal structure, and volume differ substantially from the intrusion dataset, providing a stress test for cross-workload robustness rather than a claim of domain equivalence. We acknowledge the reviewer’s valid point that a second IoT-specific intrusion dataset (such as TON_IoT or Bot-IoT) would constitute a more directly comparable validation; this is identified as a priority for future work. The load levels used in scalability experiments (up to 5000 events per second) intentionally exceed the dataset’s natural rate to stress-test each engine’s architectural ceiling and identify saturation thresholds relevant to large-scale or multi-sensor IoT deployments. We conducted controlled experiments with comprehensive statistical analysis. Our results demonstrate that Streamz achieves superior throughput at 4450 events per second with 89% efficiency and minimal resource consumption (40 MB memory, 12 ms median latency), while Faust provides robust intrusion pattern detection with 93–98% accuracy and stable, predictable resource utilization (1.4% CPU standard deviation). A multi-framework comparison including Apache Kafka Streams and offline scikit-learn baselines confirms that Faust achieves detection quality competitive with JVM-based alternatives (Faust: 96.2%; Kafka Streams: 96.8%; absolute difference of 0.6 percentage points, not statistically significant at $p=0.318$) while retaining the Python ecosystem advantages. Statistical analysis confirms significant performance differences across all metrics ($p<0.001$, Cohen’s $d>0.8$). Critical scalability thresholds are identified: Streamz maintains efficiency above 95% up to 3500 events per second, while Faust degrades beyond 2500 events per second. These findings provide IoT security engineers and system architects with actionable, empirically grounded guidance for CEP engine selection, establish reproducible benchmarking methodology applicable to future Python-based stream processing evaluations, and advance theoretical understanding of the accuracy–throughput trade-off in stateful versus stateless Python CEP architectures. Full article

Robust and transferable approaches for evaluating research capacity—whose measurable expression is reflected in research output—are essential for evidence-based science policy and strategic research management. This study develops an integrated framework to assess global scholarly capacity and regional disparities by combining semantic-similarity-based literature filtering, bibliometric mapping, dynamic performance assessment, and spatial analytical techniques into a coherent and replicable model. A Sentence-BERT model ensures thematic precision and dataset consistency, while CiteSpace 6.1.R3 is used tomap publication trajectories, thematic evolution, and influential contributors. A dynamically weighted TOPSIS model incorporates temporal variation to quantify national research capacity, and spatial analyses—including gravity center analysis, Theil index decomposition, spatial autocorrelation, gray relational analysis, and the Geographical Detector Model—identify disparity patterns and their explanatory associations. Applied to urban ecosystem security research (2001–2023), an emerging interdisciplinary field within sustainability science, the framework shows that China and the United States dominate research output, whereas European journals exert strong academic influence. The field has advanced through three stages, with increasing emphasis on ecosystem services and sustainable development. GDP, environmental pressure, and urbanization rate show the strongest explanatory associations with research capacity, and interactive effects—especially those involving GDP—exceed single-factor explanatory strength. Ecological baseline conditions such as NDVI and climate exhibit only limited associations, functioning mainly as contextual factors. Policy implications highlight four priorities: strengthening interdisciplinary and cross-regional collaboration in developing regions; promoting equity-oriented research agendas in developed regions; establishing unified definitions and validated evaluation frameworks; and advancing dynamic, systems-based approaches to ecosystem security analysis. By shifting attention from ecological status assessment to the dynamics of scientific knowledge production and research capacity, this study advances methodological foundations for research evaluation and enriches analytical approaches in urban ecosystem security, offering a generalizable framework for identifying capacity differences and supporting evidence-informed policy design. Full article

Dirofilaria immitis constitutes a significant global veterinary burden and an emerging zoonotic risk. Despite decades of study, the structural evolution of its scientific landscape remains unexplored. This study provides a comprehensive longitudinal analysis of global research on D. immitis to evaluate its trajectory, intellectual structure, and conceptual shifts over the last eight decades. A systematic bibliometric analysis was conducted following PRISMA guidelines adapted for bibliometrics. Data were retrieved from Web of Science Core Collection and Scopus, covering the period from 1945 to 2025. After deduplication and manual screening, a final corpus of 3589 documents was analyzed using performance indicators and science mapping techniques to assess growth patterns, geographic leadership, collaboration networks, and thematic evolution. The field exhibits a mature profile with a sustained mean annual growth rate of 2.39%. Production is geographically polarized, with the United States and Italy acting as the primary research hubs, though international collaboration networks are increasingly integrating endemic regions in the Global South. Thematic analysis reveals a profound paradigm shift: while early research (1945–1980) focused on parasite morphology and clinical description, the 21st century is characterized by a multidisciplinary approach dominated by molecular biology, the study of the endosymbiont Wolbachia, and the genetic mechanisms of macrocyclic lactone resistance. The intellectual structure is currently organized into distinct but interconnected clusters, linking established clinical pathology with emerging genomic and environmental control strategies. Research on D. immitis has evolved from a classical parasitology discipline into a complex biomedical ecosystem aligned with the One Health framework. The persistence of the disease, driven by drug resistance and climate-mediated vector expansion, has catalyzed a transition toward integrative research models. Future control strategies must transcend geographic borders, combining advanced genomic surveillance with ecological modeling to mitigate the impact of this transboundary disease on both animal and human health. Full article

Cassiopea andromeda is an invasive alien jellyfish that is increasingly reported across the Mediterranean Sea, yet its invasion dynamics and ecological implications remain poorly understood. This study provides an updated assessment of its spatial and temporal distribution, evaluates its potential impacts on ecosystem services and biodiversity, and explores management options through the 8Rs framework. An aggregated dataset of georeferenced records (1886–2025) was compiled from scientific literature and citizen-science platforms. Spatio–temporal analyses—including kernel density, key spatial distribution characteristics, spatial autocorrelation, and local hotspot detection—were applied to identify invasion phases, aggregation patterns, and directional dispersion. Results reveal two distinct invasion stages: a century-long arrival phase confined to the Levantine Basin, followed by an accelerated expansion since 2008, with a persistent hotspot in the eastern Mediterranean Sea and a westward dispersal trajectory. Evidence of ecological impacts within the Mediterranean Sea remains limited, however studies from other regions indicate both potential benefits and localized negative interactions with marine organisms. Application of the 8Rs model highlights implemented, feasible and challenging coordinated basin-wide strategies to support adaptive management of this alien resource. Full article

This article introduces Memetic/Metaphorical Digital Twins (MDTs) as a novel extension of Digital Twin typologies by twinning conceptual schemes, complementing Industrial, Human, and Cognitive Digital Twins. MDTs embed cultural, organizational, and semiotic knowledge into digital frameworks, enabling the recombination and evolution of knowledge structures across disciplines. Drawing on Schlaile’s economic perspectives and Mavromatidis’s architectural lens of entropy and constructal thermodynamics, this study demonstrates how MDTs can address systemic challenges in communication, knowledge transfer, and design. A Digital Community Platform, under development for supporting decentralized Personal Knowledge Management Systems (PKMS), provides the operational foundation, integrating iterative KM cycles to support knowledge co-creation. Its logic and logistics substitute the traditional document paradigm with a memetic approach by utilizing memes as replicable, adaptive knowledge units, thereby mimicking biological evolution and ecosystem resilience in digital platform environments. It aims to offer distributed, decentralized, bottom-up, affordable, knowledge-worker-centric applications prioritizing personalization, mobility, generativity, and entropy reduction; its mission is to serve a knowledge-co-creating community characterized by highly diverse individual Abilities, Contexts, Means, and Ends (ACME) facing increasingly volatile, uncertain, complex, and ambiguous futures (VUCA). A Boundary Object Taxonomy to Omnify Memetic Storytelling (BOTTOMS) is proposed to further structure atomic units of meaning—such as memes, mythemes, narratemes, and reputemes—into a unified framework for authorship and dissemination. The article situates MDTs within a design science research paradigm, outlines current implementation progress, and identifies future developments, including AI-supported curation, personalized metrics, and expanded boundary objects. Together, these contributions position MDTs as a universal framework for adaptive, transdisciplinary knowledge co-creation. Full article

This study investigates how data science competencies, conceptualized as the micro-foundations of digital dynamic capabilities (DDCs), combine to influence the development of digital business capability (DBC). Using fuzzy-set qualitative comparative analysis (fsQCA), we examine configurations of competencies that enable DBC and identify necessary and sufficient conditions. The necessary-condition testing indicates no single competency is universally required, highlighting the configurational, micro-foundational nature of DDC development. The fsQCA uncovers three equifinal competency configurations that act as sufficient pathways to high DBC. Beyond capability building, the study demonstrates how distinct competency bundles facilitate business model renewal capabilities, translate analytics into data-enabled services, and reconfigure capabilities to embed servitized offerings into scalable architectures in the digital ecosystem business. These insights offer actionable guidance for practitioners, educators, and policymakers seeking to design data science competency systems that not only strengthen DDCs but also enable sustained business model innovation in AI, Industry 4.0, and other data-driven contexts. Full article

In recent decades, the increasingly widespread diffusion of plastic contamination (plastamination) has attracted growing attention from both the scientific and public community due to its harmful effects on human health and environmental balance. Several studies have highlighted a link between exposure to microplastics and nanoplastics and the onset of central nervous system problems, impaired reproductive function, altered liver metabolism, dysbiosis and other chronic diseases. At the same time, research has highlighted how plastamination negatively impacts natural ecosystems, accelerating biodiversity loss and compromising the stability of the planet. Faced with these critical issues, scientific and professional debate has progressively shifted toward defining effective and sustainable strategies, often based on innovative technologies, aimed at limiting the overall impact of this global phenomenon. This study, consisting of a systematic literature review through a bibliometric analysis in the Web of Science database (1974–June 2025), aims to examine plastamination through a broad and integrated approach, combining biological, medical, engineering, managerial and cultural perspectives, to offer a systematic and multidimensional reading of the problem. Preliminary findings underscore the importance of an integrated vision that brings together technology, culture, society, and medicine, emphasizing the need for shared global policies and collective responsibility. The study thus aims to offer an innovative contribution to the understanding of plastamination and to the definition of multidimensional intervention strategies to address one of the most pressing challenges of our time. Full article

Species of the genus Thunbergia, native to Africa, Asia, and Australia, are widely cultivated as ornamental plants; however, their ability to escape cultivation and establish themselves in novel environments poses a growing threat to tropical forests. Here, we provide the first nationwide assessment of Thunbergia species occurring in Ecuador, integrating data from citizen science platforms, herbarium collections, and field surveys. We analyzed spatiotemporal patterns of occurrence, evaluated invasion status based on wild persistence and spread, and assessed environmental preferences using climatic niche analyses. Species distributions were further examined across land-cover types, conservation areas, and forest–non-forest interfaces. We confirmed the presence of five Thunbergia species in Ecuador, two of which also occur in the Galapagos Islands. All species were recorded both in cultivation and in the wild, indicating ornamental horticulture as the main introduction pathway for the genus, and occurrences were documented within 24 conservation areas. Thunbergia alata, T. fragrans, and T. grandiflora were categorized as invasive in Ecuador. Among them, T. fragrans exhibited broad environmental tolerance across bioregions. Wild occurrences were predominantly associated with human-modified landscapes but frequently occurred near forest edges, indicating ongoing encroachment into natural forests. These findings highlight the urgent need for preventive and targeted management strategies, particularly against T. alata, which represents an emerging threat to Andean forest ecosystems. Full article

Wetlands, frequently termed the “kidneys of the Earth,” represent one of the most vital global ecosystems. Despite their limited spatial extent, plateau wetlands function as unique ecological units that play a pivotal role in the global carbon cycle, water resource regulation, and biodiversity conservation, while exhibiting acute sensitivity to climate change. Advances in remote sensing technology—characterized by macro-scale cover-age, temporal efficiency, and non-invasive operations—have established it as a corner-stone for the dynamic monitoring and analysis of these environments. This study presents a bibliometric synthesis of 2138 publications (1982–2024) retrieved from the Web of Science Core Collection. We systematically evaluated publication trajectories, international collaborative networks, disciplinary shifts, core journals, and the spatiotemporal evolution of research hotspots. Our findings reveal an exponential growth in scholarly output alongside a marked diversification of research fields. Geographically, research is predominantly clustered around the Tibetan Plateau, flanked by the Alps and the Himalayas, with sparse representation in other regions. Future endeavors should prioritize underrepresented low-latitude and remote regions through strengthened international synergy and the integration of emerging technologies, such as UAVs and hyperspectral sensors. Full article

Rapid advances in automation, artificial intelligence, and Industry 4.0 technologies have intensified concerns about job displacement and reshaped employment relations globally. While technological unemployment has been widely examined, its psychological dimension—technological unemployment anxiety—remains fragmented and relatively underexplored in the literature. This study conducts a bibliometric analysis of 930 articles published between 2001 and 2025 and indexed in the Web of Science database to map the intellectual structure and thematic evolution of research on technology-related employment, including anxiety-related dimensions. Using keyword co-occurrence, collaboration mapping, and thematic clustering, this study identifies a gradual shift from macro-level economic discussions toward micro-level concerns, including job insecurity perceptions, employability expectations, and worker well-being. The findings indicate that post-pandemic digital acceleration has intensified individualized forms of workplace anxiety within contemporary workplaces. The novelty of this study lies in explicitly positioning technological unemployment anxiety as a distinct analytical construct, rather than a secondary outcome of technological change, thereby extending existing bibliometric research. The results offer insights for scholars and provide practical implications for policymakers and organizational actors seeking to address technology-driven anxiety in the emerging post-digital ecosystem. Full article

The rapid expansion of artificial intelligence (AI) in digital education has transformed gamification from a motivational strategy into a data-driven, adaptive learning paradigm. This systematic review conceptualizes AI-supported gamification as an information-centered ecosystem integrating learning analytics, behavioral modeling, adaptive algorithms, and intelligent feedback mechanisms to enhance cognitive development and critical thinking. Following PRISMA 2020 guidelines, a systematic search was conducted across Scopus, Web of Science, ScienceDirect, Google Scholar, and ResearchGate. Peer-reviewed empirical studies published between 2020 and 2025 were considered. Studies were included if they examined gamification in educational contexts with AI-driven or adaptive system components, while non-educational contexts, duplicates, and non-English publications were excluded. After screening and eligibility assessment, 100 studies were included in the final synthesis. The review examines how AI-driven personalization, neurotechnology, predictive modeling, and generative systems reshape the design and effectiveness of gamified e-learning environments. Architectural patterns identified include recommender systems, real-time behavioral adaptation, affect-aware feedback loops, and algorithmic content generation. Across the reviewed studies, AI-supported gamified systems were frequently associated with increased engagement and moderate improvements in executive functions, higher-order reasoning, and adaptive learning pathways. However, challenges related to system transparency, data governance, algorithmic bias, cognitive load management, and equitable access remain significant. The review was not registered. By framing gamification as an adaptive information system rather than solely a pedagogical intervention, this study proposes a structured taxonomy of AI-driven gamified architectures—including data acquisition, user modeling, predictive analytics, and adaptive feedback layers—and outlines research priorities for scalable, ethically grounded, and data-informed e-learning ecosystems. Full article

Understanding platypus health and disease is made challenging by the cryptic nature of this unique and iconic species. The retrospective medical record review methodology offers a valuable tool to better understand platypus health. A multi-institution review was performed, with 21 organisations and individuals contributing veterinary and pathology records spanning 34 years and 5 Australian states and territories. In total, records were reviewed from 278 wild platypuses and 40 zoo-housed platypuses, with a combined total of 383 presentations. Data from these were extracted and analysed, providing information on demography (age, sex), geographic location, season, reason for presentation, outcome of presentation, and clinical and pathological findings. For wild platypuses, key findings included that the juvenile age class was disproportionately represented in Queensland and New South Wales, and that the peak in juvenile presentations corresponded with weaning. For both wild and zoo-housed platypuses, novel reports of neoplasia were identified, and in wild platypuses, the first reports of neural angiostrongyliasis. For zoo-housed platypuses, an area identified for future research is the high prevalence of presentations for skin lesions. This study contributes to our understanding of platypus health and disease and should be used to guide further work to improve both conservation and welfare outcomes for one of the world’s most unique mammals. Full article

Mushrooms offer a promising solution for sustainable food production due to their nutritional value, low resource requirements, and ability to grow in diverse environments. As interest in mushrooms grows, it is important to understand where current research is focused and where key gaps remain. A bibliometric analysis of 776 research articles indexed in Web of Science revealed a strong emphasis on yield, substrate reuse, and enzymatic degradation, but limited attention to molecular approaches, climate adaptation, and studies from arid regions such as the Middle East. Building on these findings, this review explores the ecological diversity of mushrooms and their adaptations across tropical, temperate, boreal, and arid ecosystems. It discusses the role of mycorrhizal and microbial interactions in nutrient cycling and environmental resilience, including desert truffle symbioses. Key pathways and genetic regulation involved in lignin degradation are outlined, along with recent advancements in transcriptomics, proteomics, genomics, metabolomics, and metagenomics that support improved cultivation and bioactive compound production. The review also addresses sustainable practices, such as microbiome integration and resource recycling, to enhance mushroom farming. The aim is to bring together ecological insights and molecular strategies to support sustainable mushroom production, particularly in regions facing resource and climate challenges. Full article