Search Results (8,316)

Word order in Andean Spanish has attracted considerable scholarly attention, particularly regarding the extent to which sustained contact with Quechua has shaped its syntactic and pragmatic patterns. However, there are no recent studies investigating whether this variation in contemporary Andean Spanish has become consolidated or remains a minor phenomenon. This study was conducted to describe the frequency of verb-final constructions in a corpus of 25 bilingual Spanish–Quechua speakers and Spanish monolinguals from the city of Juliaca (Perú). The central objective of this study is to identify patterns in constituent order as they emerge from the narratives of speakers in Juliaca, examining how the verb position relates to the degree of new and given information, pragmatic function, and discourse situation. The variation in verb placement is analyzed from both quantitative and qualitative perspectives, considering informational, pragmatic, and syntactic factors. This research was conducted within the framework of Contact Linguistics, employing a dynamic approach to language interaction. It is based on the principle that speakers employ available grammatical constructions to incorporate distinctions or semantic nuances that might not exist in non-contact Spanish but are present in the Amerindian language. In this way, speakers draw on their linguistic background to develop innovative expressive tools or diverse communicative alternatives, incorporating them into their daily communication. Full article

Micro-structured SAE H13 tool steel inserts for polymer injection molding require accurate replication of sub-millimeter features while retaining adequate densification and heat-treatment response. This study compared two powder-based routes on the same hemispherical insert containing pyramidal features of approximately 0.145 mm base width: hot embossing (HE) of water-atomized SAE H13 powder (supplier d50 = 5.7 µm, irregular morphology) compounded with a commercial M1 binder, and material extrusion (MEX) of a commercial gas-atomized SAE H13 filament processed on a Markforged Metal X. Rheological screening selected a 57:43 vol% powder-to-binder ratio for the in-house HE feedstock, and DSC/TGA measurements defined two-step debinding windows. The best HE conditions were 220 °C, 8 MPa, and 45 min for the in-house mixture, and 210 °C, 8 MPa, and 30 min for the granulated commercial filament; the latter showed a 0.15% linear deviation from the silicone replica diameter among the best-rated samples. Under the tested commercial MEX configuration, the pyramidal features were not resolved because the 0.40 mm deposition line width exceeded the target feature base width, causing the slicer to omit the sub-line-width geometry. The defect populations differed qualitatively: HE specimens showed porosity and local cracking associated with powder morphology and pressureless sintering, whereas MEX specimens showed build-direction-aligned inter-raster voids associated with the toolpath. Microhardness and tensile data are therefore interpreted as process-history-specific results rather than as a direct route ranking, because sintering conditions were not uniform across all specimens. The study defines an experimentally bound process-selection limit for SAE H13 micro-tooling: HE remains preferable for sub-nozzle surface features, whereas MEX remains attractive for macro-scale geometric freedom, if resolution, densification, and post-sintering consolidation are addressed. Full article

For over 70 years, microalgae have been considered promising ingredients for developing sustainable, nutritionally rich foods. Their high protein content, presence of essential amino acids, fatty acids, natural pigments, and a myriad of bioactive compounds position them as potential alternatives to conventional ingredient sources. However, despite their significant potential, the large-scale incorporation of microalgae into food products remains limited. This study presents a critical analysis of the main challenges associated with the use of microalgae in the food industry. Key bottlenecks include high production costs, technological difficulties related to biomass processing, and challenges in extracting desirable compounds. Additionally, the strong flavor, odor, and intense coloration of microalgal biomass can negatively affect sensory acceptance in food products. Other limitations involve scalability issues in cultivation systems, risks of contamination during production, and regulatory constraints related to food safety approval. Consumer perception and limited familiarity with microalgae-based foods also contribute to slower market adoption. Therefore, although microalgae represent a promising and sustainable food resource, overcoming technological, economic, and sensory barriers is essential for their broader integration into the food industry and for achieving successful market consolidation. Full article

Information disorders condition electoral processes, becoming a major institutional concern. In response, the European Union and various fact-checking organisations co-organised the Elections24Check project to curb disinformation in the 2024 European elections. This research analyses the activities, strategies, and editorial behaviour of the five Spanish fact-checking agencies that are integrated into the initiative. Through a content analysis applied to 3256 publications, the findings demonstrate the maturity of the Spanish ecosystem, which led the project by contributing 32.8% of the total content. Strategically, reactive action predominated, except for Newtral, which prioritised prebunking (62.6%). Political scrutiny was minor (6.6%), focusing on major coalitions and far-right leaders. Thematically, highlights included war conflicts, migration, and national/regional frameworks utilised for emotional polarisation, displacing the focus from the strictly European debate. In conclusion, Spain consolidates itself as a cornerstone of European fact-checking. However, the results reveal inefficiencies in the project’s extended timeframe, suggesting more constrained and effective frameworks for election campaigns. Furthermore, the persistence of narratives anchored to local agendas evidences a strategic fragmentation that hinders the construction of a fully pan-European public space. Full article

Conventional signature-based defenses no longer protect the heterogeneous, large-scale infrastructures that the Internet of Things (IoT) now constitutes. Large language models (LLMs) and agentic artificial intelligence (AI)—systems that autonomously perceive, reason, plan, and act—open a path to self-defending IoT ecosystems, but the integrating literature remains fragmented. Within the IEEE Xplore, ACM Digital Library, and MDPI literature, this survey is, to the best of our knowledge, among the first systematic reviews of agentic AI and LLM-driven approaches for autonomous IoT cybersecurity. Following a PRISMA 2020 protocol, we analyze 153 peer-reviewed studies published between 2020 and 2026 in IEEE Xplore, the ACM Digital Library, and MDPI journals. We organize the corpus along a four-pillar taxonomy: agent architecture (single- vs. multi-agent), reasoning strategy (chain-of-thought, ReAct, plan-and-solve, tool use), action scope (detection, response, threat hunting, vulnerability discovery, deception), and deployment topology (edge, fog, cloud). We synthesize four flagship application domains, consolidate datasets and benchmarks, and analyze open challenges including hallucination, prompt-injection robustness, explainability, privacy, latency, and governance. A 2026 research roadmap identifies federated agentic learning, verifiable autonomous reasoning, trustworthy multi-agent collaboration, and resource-hardened edge agents as high-priority directions. A companion reproducibility kit—prompt templates, reference single- and multi-agent loops, and an Edge-IIoTset-style evaluation harness, released as illustrative scaffolding rather than a validated framework—is released publicly and archived on Zenodo (DOI 10.5281/zenodo.20726552). Full article

Automotive Noise, Vibration, and Harshness (NVH) has emerged as a critical interdisciplinary field influencing vehicle performance, passenger comfort, brand perception, and regulatory compliance. This thematic literature review synthesizes key research trends, methodological approaches, and technological developments shaping contemporary NVH studies. Drawing on 255 scholarly and industry sources, the review identifies five dominant themes: (1) sources and characterization of noise and vibration in internal combustion, hybrid, and electric vehicles; (2) advanced modeling and simulation techniques—including finite element analysis, statistical energy analysis, and machine learning–based prediction models; (3) materials, components, and structural optimization strategies for NVH mitigation; (4) the rapidly evolving landscape of electric and autonomous vehicle NVH; and (5) emerging active noise and vibration control technologies and data-driven diagnostics. The analysis highlights a definite shift toward holistic, data-driven, and multi-physics approaches, driven by lightweighting imperatives, widespread electrification, and increasingly stringent occupant comfort expectations. Key gaps in current research—including the need for unified evaluation metrics, real-time in-vehicle NVH monitoring, closer integration of subjective psychoacoustic perception with objective physical measurement, and validated simulation workflows for novel EV architectures—are identified and discussed. This review provides a consolidated and expanded framework for understanding contemporary NVH research directions and articulates opportunities for transformative innovation in next-generation vehicle development. Full article

Although sustainability has consolidated as a central criterion of value and performance in project management, a deep gap persists between its conceptual recognition and its effective application, making it difficult to structure and measure its real scope. Faced with this complexity, this study aims to dimension sustainable project management in productive sectors by analyzing its strategic alignment and operational trends. Methodologically, the research relies on a meta-aggregative review of 124 articles, integrating qualitative synthesis with quantitative structural analysis to decipher how the field is operationalized. Qualitatively, the results reveal that sustainability redefines project success, shifting toward the integral generation of long-term economic, social, and environmental value, contingent upon its anchoring in corporate strategy, governance, and the project lifecycle. However, quantitative analysis exposes an inherent thematic multidimensionality. The Latent Dirichlet Allocation (LDA) model identifies multiple simultaneous dimensions (entropy = 0.74), and the Principal Component Analysis (PCA) explains 27.24% of the cumulative variance. While these values align with the standard benchmarks for high-dimensional textual data, they empirically represent a highly complex and distributed knowledge structure rather than a unified theoretical framework. Consequently, while consolidated nuclei exist around management and governance, critical empirical gaps persist regarding risk integration, performance metrics, and, particularly, the circular economy. It is concluded that, although the discipline enjoys high theoretical legitimacy and growing measurement capabilities, its integration into operational decision-making remains partial. The ultimate challenge lies in articulating conceptual knowledge, tangible metrics, and strategic governance, ensuring that sustainability evolves from a declarative ideal into the inescapable, cross-cutting operational framework of project management. Full article

Legal regulation and market-oriented land property rights reforms have long been the mainstream, whereas the role of cultural embeddedness in driving land institutional innovation remains insufficiently explored. This paper develops an analytical framework that integrates institutional logics perspective with cultural embeddedness theory to examine the formation mechanism of homestead institutional innovation through a single-case study. Specifically, this study investigates a tripartite cost-sharing institution of homestead construction, involving the village enterprise, the village collective, and households in M Village, China. In this case, the findings reveal that the collectivist culture plays a facilitative role in institutional innovation of homestead land. First, institutional logics evolved in response to spatial resource constraints, thereby generating the demand for homestead institutional innovation. Second, through cultural embeddedness, institutional logics focus actors’ attention and reshape leadership identity, common goals, and collective action schemas. These processes facilitate decision making, sensemaking, and collective mobilization, thereby activating the formation of homestead institutional innovation. Third, the evolution of collectivist culture enhances the compatibility among multiple institutional logics, including those associated with the state, corporate, community, family, and professional actors. This compatibility consolidates the leadership identity of village elites, routinizes collective action, and ensures benefit sharing, thereby stabilizing homestead institutional innovation. The study suggests that integrating local culture with formal institutional regulations, as well as combining top-down rules with bottom-up practices, can effectively promote institutional innovation in homestead land governance. Full article

Sustainable finance has evolved rapidly in tandem with digital transformation and the circular economy; however, the simultaneous integration of these three domains remains fragmented. This study analyzes the intellectual structure of the field through a bibliometric analysis of a curated corpus of 2537 articles indexed in Scopus between 2015 and 2025, of which 2471 were classified into three thematic trajectories: sustainable finance combined with digital transformation (D1), sustainable finance combined with the circular economy (D2), and triadic convergence (D3). The classification followed a deductive, rule-based procedure, with documents independently coded by the two authors and discrepancies resolved by consensus. VOSviewer was used to construct networks of keyword co-occurrence, co-citation, and bibliographic coupling, identifying four thematic clusters. A complementary keyword-overlap projection was then used to articulate the deductive classification with the inductive clusters. The results reveal a rapidly expanding field, geographically concentrated in China, in which the dyadic trajectories anchor predominantly in a single conceptual cluster, while triadic convergence (D3), which appears only in 2021 and accounts for 2.7% of the classified corpus, is the only trajectory whose documents distribute across three clusters simultaneously. This pattern provides empirical support for interpreting triadic convergence as an emerging frontier rather than a consolidated stream. The findings are interpreted under the lens of economicità, an Italian accounting concept that frames sustainability as a condition for the firm’s long-term economic equilibrium. Full article

The implementation of medication adherence interventions is suboptimal. To guide implementation, this study aimed to tailor an existing implementation determinant framework to support the assessment of the implementability of such interventions in a specific context prior to implementation, and to investigate whether experts can assess in advance which determinants are important for implementing medication adherence interventions. In a Delphi study, experts rated determinants based on constructs of the Consolidated Framework for Implementation Research (CFIR) in terms of their importance for implementing medication adherence interventions. Determinants were then prospectively evaluated in four Dutch living labs implementing medication adherence interventions. The results were compared to assess agreement between expert opinion and real-world practice. Of 40 evaluated CFIR determinants, 16 were important in the majority of the living labs. These determinants concerned the inner setting, characteristics and roles of involved individuals, and implementation process domains of the CFIR. After comparing the prospective evaluation with Delphi results, expert opinions matched living lab observations for 18 out of 40 determinants (45%) regarding (un)importance. The CFIR was tailored to primary care medication adherence interventions based on practice observations, offering a potentially helpful framework to assess implementability of these interventions in specific contexts in advance. Determinant frameworks could benefit from incorporating real-world practice data. Full article

The General Data Protection Regulation (GDPR), adopted by the European Union in 2018, aims to enhance consumer trust and market efficiency by strengthening data protection. The concurrent stringent compliance requirements raise operational costs and could reshape competition by favoring larger firms with greater regulatory capacity. While the GDPR reduces data-related risks and promotes global digital trade through its extraterritorial reach, the potential advantage to larger firms could incentivize strategic responses such as mergers and acquisitions (M&A) to consolidate market power. Given the rapid expansion of Chinese digital firms in e-commerce, social media, and cloud services across the EU, this study examines how the GDPR has affected their cross-border M&A activities between 2014 and 2021. Based on difference-in-difference analysis, the study finds that the GDPR did not have a statistically significant impact on the number or value of mergers and acquisitions by Chinese digital firms in the EU in the short term. This suggests that firms may enhance their institutional adaptability by strengthening their compliance capabilities. However, institutional and cultural differences pose long-term entry barriers for the firms. The study contributes by highlighting how firms adjust internationalization strategies under stringent regulatory regimes, offering policy-relevant insights for governments and regulatory authorities. Full article

Silts are generally unsuitable for direct use as subgrade fill material due to their low shear strength and deformation resistance. In this study, a novel technique for strengthening silt using enzyme-induced calcium carbonate precipitation (EICP) with the addition of non-fat milk powder is proposed to improve the mechanical properties of silt for use as subgrade fill material. The effect of EICP on the mechanical properties of silt, in terms of internal friction angle and shear strength, was examined through consolidated undrained (CU) triaxial shear tests. The results showed that, with the EICP technique involving non-fat milk powder, the mechanical behaviors of silts were significantly enhanced due to the improved bonding ability of the silt particles. Furthermore, an optimum content of non-fat milk powder of 6 g/L is proposed to increase the mechanical properties. Compared with EICP treatment alone, under the optimum condition of 6 g/L non-fat milk powder and 14 days of curing, the shear strength, cohesion, and internal friction angle increased by 44.1%, 51.86%, and 31.4%, respectively. Finally, microstructural analyses were conducted using Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) to provide insight into the mechanisms underlying the improvement of silt. The findings of this study can provide guidance for the application of silt improvement through the EICP technique involving non-fat milk powder. Full article

Consolidated bioprocessing (CBP) is difficult to monitor because enzyme production, lignocellulose degradation, sugar release, and fermentation occur simultaneously under sparse measurement, feedstock variability, and plant–model mismatch conditions. This study proposes a computational sensor-set design framework for digital-twin-assisted CBP monitoring. A five-state virtual plant, consisting of active biomass, cellulolytic enzyme activity, residual insoluble substrate, soluble sugar, and ethanol, was used to evaluate all 16 ethanol-mandatory measurement packages formed from ethanol, sugar, biomass, enzyme, and residual-substrate proxy channels. Candidate sensor sets were assessed using finite-difference output sensitivities, Fisher-information-based state-observability and parameter-identifiability analyses, eigenvalue and parameter-correlation diagnostics, and paired Monte Carlo unscented Kalman filter soft-sensing reconstruction. Within the tested five-state virtual-plant benchmark and with the specified excitation schedule, noise assumptions, burden indices, and scoring objective, ethanol-only sensing provided the weakest support for state-aware CBP digital-twin reconstruction. At a $6\mathrm{h}$ sampling interval, the state-observability log-pseudodeterminant increased from 4.18 with ethanol-only sensing to 8.56 after adding soluble sugar and to 16.42 with full-proxy monitoring. The ethanol–sugar–biomass–substrate package also gave strong reduced state-observability performance, with log-pseudodeterminants of 15.12, 13.76, and 12.51 at 6, 12, and $24\mathrm{h}$, respectively. Biomass and enzyme proxies contributed strongly to parameter learning, and the ethanol–sugar–biomass–enzyme package gave the strongest active parameter-identifiability performance, with log-pseudodeterminants of 10.82, 9.06, and 6.67 at 6, 12, and $24\mathrm{h}$, respectively. In the paired soft-sensing analysis, full-proxy monitoring reduced the mean latent-state RMSE from 1.1899 to 0.3756, followed by ethanol–biomass–enzyme–substrate with 0.3843 and ethanol–sugar–biomass–substrate with 0.4121. The primary aggregate ranking identified ethanol–sugar–biomass–substrate as the best overall package, with a sensor-value score of 0.8432 and a burden index of 7.0, followed by full-proxy monitoring with a score of 0.8173 and a burden index of 10.0. Robustness tests showed that ethanol–sugar–biomass–substrate remained top-ranked under uniform noise scaling, full UKF missingness, delay and bias stress test conditions, most scoring-weight scenarios, and all tested sensor-specific burden workflows. Full-proxy monitoring remained a close competitor under independent sensor-specific noise variation conditions and became top-ranked for some alternative operating trajectories. The proposed framework provides a simulation-based method for prioritizing informative measurement packages before implementing CBP digital twins in laboratory and pilot-plant settings. Full article

Heat-treatable aluminum alloys are widely used in aerospace and automotive industries for high-performance structural applications. However, their processing through conventional fusion-based additive manufacturing is limited by solidification-related defects, such as hot cracking, porosity, and elemental segregation. To overcome these limitations, friction-based additive manufacturing (FBAM) has emerged as a promising solid-state alternative. FBAM primarily includes friction stir additive manufacturing (FSAM), additive friction stir deposition (AFSD), friction screw extrusion additive manufacturing (FSEAM), and friction rolling additive manufacturing (FRAM), which differ in feedstock form and process configuration. In these processes, feed material is consolidated through frictional heat generated below the melting temperature, enabling the formation of refined equiaxed microstructures while minimizing solidification defects. Despite these advantages, significant challenges persist in processing heat-treatable aluminum alloys, particularly the 2xxx, 6xxx, and 7xxx series. These include non-uniform microstructure and mechanical properties along the build direction; precipitation instability; process-induced defects, such as tunnel formation; and mechanical properties that are often inferior to those of the corresponding base materials (BMs). Reported FBAM builds generally exhibit equiaxed ultrafine grains below 1 μm; however, the strength and microhardness of heat-treated alloy builds commonly remain around 70–75% of the corresponding BM. Following post-heat treatment, microhardness can be nearly fully recovered, whereas UTS typically reaches about 80–85% of BMs, often with an associated ductility reduction of nearly 50%. This review critically analyzes research reported over the past decade on FBAM processing of heat-treatable aluminum alloys, covering FSAM, AFSD, FSEAM, and FRAM. The key challenges related to microstructural evolution and mechanical performance are systematically discussed for each alloy series. Furthermore, mitigation strategies proposed in the literature, including process parameter optimization, in-process cooling, post-heat treatment, and nanoparticle reinforcement (e.g., SiC, TiC, Ni and ZrO₂), are evaluated. Finally, existing research gaps are identified, and future directions are proposed to support the development of robust, scalable, and high-performance FBAM processes for heat-treatable aluminum alloys. Full article

The genus Dracocephalum (Lamiaceae), comprising over 60 species predominantly distributed in Europe and Asia, has historically been used in traditional medicine and has recently attracted growing scientific interest due to its diverse pharmacological and phytochemical properties. Despite increasing pharmacological and phytochemical investigations, the antioxidant potential and related bioactivities of Dracocephalum species remain fragmented across individual studies, with limited efforts to comparatively integrate evidence on phytochemical diversity, antioxidant relevance, and pharmacological variability. Therefore, this review consolidates and critically evaluates current knowledge regarding the phytochemical diversity, antioxidant potential, and therapeutic applications of Dracocephalum species, emphasizing their bioactive compounds and antioxidant-driven mechanisms. Particular attention is given to polyphenolic and phenolic constituents—including flavonoids, phenolic acids, terpenoids, and volatile compounds, with rosmarinic acid, tilianin, luteolin derivatives, and apigenin derivatives identified as key contributors to biological activity. Unlike previous reviews, which primarily focused on isolated pharmacological effects or individual species, this study provides a comparative and integrative perspective by linking phytochemical composition with antioxidant-related activities and therapeutic implications across species. By synthesizing fragmented evidence and highlighting methodological advances in chromatography, metabolomics, and comparative analyses, this review identifies current knowledge gaps and outlines future perspectives for phytopharmaceutical, nutraceutical, and functional food applications. Full article