Search Results (34,442)

Tendon healing is often hindered by unresolved inflammation and dysregulated immune responses, highlighting the need for innovative regenerative strategies. This study developed an immune-informed platform by functionalizing validated 3D tendon-mimetic poly(lactide-co-glycolide) (PLGA) scaffolds with immunomodulatory conditioned media (CM), referred to as CMI_NF to emphasize its anti-inflammatory and immunomodulatory properties, derived from ovine amniotic epithelial stem cells (AECs), offering a potential cell-free therapeutic solution. Three functionalization methods were compared: physical adsorption, and hydrochloric acid (HCl) or sodium hydroxide (NaOH) pre-treatments. FT-IR spectroscopy and protein adsorption analyses identified NaOH as the most effective method, enhancing retention and release of Amphiregulin (AREG), an AEC key immunomodulatory protein. Kinetic studies revealed a sustained, controlled release of AREG over 7 days (d) from CM_INF-functionalized scaffolds (3D-CM_INF), preserving bioactivity. Functionally, 3D-CM_INF scaffolds significantly suppressed T-cell activation and peripheral blood mononuclear cell (PBMC) proliferation. The released CM from 3D-CM_INF (CM_R) exhibited time-dependent immunomodulatory effects: early T-cell inhibition (6–72 h) and delayed suppression of PBMC proliferation (48 h–7 d). Macrophage polarization analysis revealed a shift towards the pro-regenerative M2 phenotype, with increased expression of M2 over M1 markers in 3D-CM_INF-adherent cells. Flow cytometry confirmed a preferential induction of regulatory M2b macrophages alongside reductions in pro-inflammatory M1 and pro-fibrotic M2a subsets. These results demonstrate that 3D-CM_INF scaffolds can finely modulate immune responses, balancing inflammatory and reparative cues relevant to early tendon healing processes. This platform, integrating structural and immunomodulatory elements, presents a promising, cell-free, and translational immunoengineering strategy to control inflammation and support tendon repair. Full article

Research shows that structures are often over designed in reliability-based calculations compared to code requirements. To address the knowledge gap in applying Reliability Based Design Optimisation (RBDO) within Building Information Modelling (BIM), this paper presents a novel BIM-integrated RBDO system for highway structures aimed at reducing over design. The approach is aimed at optimising the system reliability index. This value is then applied to the BIM model of the structure as a direct safety metric describing the probability of failure. In addition, minimum robustness and redundancy indices can be derived using this approach to ensure overall compliance with structural design codes, (Eurocodes), yielding key BIM model safety metrics. The system reliability index was optimised by utilising target limit state reliability indices to derive system difference target limits. System element reliability indices were effectively increased or reduced by manipulating element resistance parameters. An optimisation algorithm was employed to ensure compliance with the minimum system difference target limits. A secondary verification was undertaken to ensure minimal element target reliability indices were not compromised. The system reliability-based case studies on one-span bridge structures demonstrated that optimisation resulted in an overall 15% reduction in design resistance compared with the Eurocodes design method. In addition to highlighting element overdesign, the balance between safety and economy is improved by yielding comprehensive structural system safety metrics as a safer approach than direct element reliability-based optimisation. Full article

The digital carbon footprint denotes the environmental impact generated by digital technologies throughout their lifecycle. Industry 4.0 manufacturing environments rely extensively on data processing, information storage, and artificial intelligence, thereby increasing energy demand and associated carbon emissions. These conditions have intensified interest in Green AI, particularly in applications such as predictive maintenance and collaborative human–machine systems. This research investigates determinants of behavioural intention to adopt Green AI through an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model tailored to Industry 4.0 and sustainability contexts. The framework incorporates performance expectancy, Industry 4.0 eligibility, technology influence, digital manufacturing competence, sustainability conditions, Green AI recognition, and green manufacturing concern. Data were obtained from an anonymous survey of 1003 Generation Z students enrolled in technical disciplines and preparing for manufacturing-oriented careers. Relationships among constructs were analysed using partial least squares structural equation modelling (PLS-SEM). The model demonstrates strong explanatory and predictive capability. Adoption intention is primarily associated with performance expectancy, Industry 4.0 eligibility, and digital manufacturing competence, while sustainability-oriented perceptions play a contextual rather than direct behavioural role. The study offers a domain-specific empirical extension of UTAUT within pre-workforce technical education rather than proposing a new acceptance theory. The findings reflect intention formation prior to labour-market entry and require validation in operational manufacturing settings before broader generalisation. Full article

Temperate forests play a key role in biodiversity conservation, climate regulation, and the provision of ecosystem services. However, land-use changes and urban expansion have intensified landscape fragmentation processes, reducing ecological connectivity and ecosystem functionality. Despite the importance of community-owned forests in northern Mexico, evaluations of landscape configuration within these territories remain limited. This study compared land-use and land-cover patterns and fragmentation metrics in four community-managed ejidos in Durango, Mexico, using Landsat imagery from 2000 and 2020. Land-cover maps were produced through supervised classification with a Random Forest algorithm and validated using standard accuracy metrics. Landscape composition, configuration and connectivity were assessed at class and landscape levels using a set of spatial metrics calculated with FRAGSTATS. The results reveal contrasts among ejidos. Ciénega de los Caballos and Navajas show greater representation of secondary vegetation accompanied by changes in patches and edge densities. San retains a more cohesive configuration with comparatively higher aggregation and connectivity, whereas El Tunal y Anexos exhibit stronger subdivision and lower connectivity. These outcomes emphasize the value of spatial metrics for identifying differences in landscape structure between observation years and for supporting comparative assessment in community-managed forest territories. The study provides spatially explicit information that may assist territorial planning and forest management at this scale. Full article

Background/Objectives: Intranasal esketamine has emerged as an effective treatment for patients with treatment-resistant depression (TRD), providing rapid symptom relief when conventional antidepressant strategies fail. While its pharmacological efficacy has been demonstrated in randomized controlled trials, less attention has been paid to the organizational, relational, and multidisciplinary aspects that influence its real-world implementation and clinical effectiveness. While practical recommendations for intranasal esketamine services exist, an implementation-ready framework integrating psychiatry, nursing, and psychotherapy across treatment phases is still lacking. This narrative review synthesizes the clinical and real-world evidence and proposes a phase-based integration framework with explicit role delineation and measurable implementation/fidelity indicators. Methods: We conducted a narrative review informed by a structured literature search in major databases from inception to the most recent update. Search terms combined ‘esketamine’/‘Spravato’ with ‘treatment-resistant depression’, ‘nursing’, ‘psychotherapy’, ‘multidisciplinary’, and ‘implementation’. Outcomes prioritized in the synthesis included depressive symptom severity/response, relapse prevention, safety/tolerability, anhedonia, suicidality monitoring, functional outcomes, and patient-reported experience/retention. Based on this evidence, an integrated, phase-based multidisciplinary framework for esketamine treatment was developed. Results: Available evidence supports the efficacy of intranasal esketamine in reducing depressive symptoms in TRD, with growing real-world data confirming its effectiveness and safety. Beyond global symptom improvement, studies highlight benefits on clinically relevant domains such as anhedonia and suicidality trajectories, as well as meaningful patient-reported outcomes. However, the complexity of esketamine delivery requires structured clinical pathways. The proposed model delineates complementary roles for medical supervision, nursing care, and psychotherapy across pre-treatment assessment, induction and session delivery, post-session integration, and maintenance phases, emphasizing safety, continuity of care, and patient-centred monitoring. Conclusions: Intranasal esketamine represents not only a pharmacological innovation but also a treatment that necessitates an integrated multidisciplinary approach. A structured phase-based multidisciplinary approach may support safer, more acceptable delivery of intranasal esketamine and potentially improve retention and patient experience; however, prospective implementation and comparative studies are needed to evaluate clinical effectiveness, feasibility, and cost-effectiveness. Full article

Green businesses represent a strategy for coordinating production with conservation in the Colombian Amazon; however, their consolidation continues to be limited by deficiencies in knowledge management and in the coordination of capacities for innovation. The objective of this study was to identify the relationships between capital, dynamic capabilities, and innovative performance in Amazonian green companies, using multivariate analysis. The results showed that knowledge-related capabilities (acquisition, transformation, and information management) are the factors that most strongly influence innovation. Pearson’s correlations confirmed positive associations between these variables and innovative performance. In the structural model, absorptive capacity emerged as the central axis of the system (β = 0.911; p < 0.001; R² = 0.83). We conclude that strengthening absorption capacity and organizational learning are the most important variables for improving innovation and sustainability in Amazonian green businesses. These findings provide robust evidence to inform the design of public policies in Science, Technology, and Innovation (STI) with a differentiated territorial approach, aimed at strengthening capacities, developing financing schemes for sustainable innovation, and consolidating multi-actor territorial governance structures, which are essential to foster resilient bioeconomy ecosystems in the Colombian Amazon. Full article

Given the lack of integrated, cross-cutting approaches in urban Quality of Life measures, a new framework is proposed here that draws upon a city-level index co-created under the Quality of Life Initiative implemented by UN-Habitat. Using a conceptual narrative review with a systematic structure, themes relevant to the urban context were clustered into three areas or ‘lenses’ through which decision-making in development and policy might be viewed, namely: Structural (i.e., adequacy, affordability, objective safety), Fairness (i.e., equity, inclusion, opportunity), and Perception (i.e., belonging, perceived safety, meaning and purpose). In support of creating sustainable communities, structural foundations and needs, such as housing, transport, food, and infrastructure, typically need to be addressed first. These structural realities are then filtered through a fairness lens—who benefits, who participates, and who is left behind? Finally, the filtered urban experience culminates in perception-level outcomes in terms of how people feel, connect, and find meaning in their urban experience. While presented sequentially in the framework, this is not prescriptive. Cities may start with any one lens dependent upon the context of the sustainable development challenge they are seeking to address while still recognizing the dynamic tensions among the lenses. The power of the framework lies in moving beyond siloed thinking to examine interconnections and intersectionality. To explore the potential practical application of the framework it was applied to three key urban Quality of Life challenges, namely, informality, migration, and sustainability. The framework is offered as an adaptable tool for policymakers and practitioners to support the design of more equitable, inclusive, and meaningful urban development interventions that support delivery of the Sustainable Development Goals and the global agenda to leave no one behind. Full article

In molecular communication via diffusion (MCvD) uplinks where multiple nano-sensors report concurrently to a fusion center (FC), the long channel memory and the near–far imbalance jointly create strong multiple access interference (MAI) coupled with residual inter-symbol/inter-chip effects. This paper studies an oversampling-enabled time-domain reception for an uplink molecular code-division multiple-access (MoCDMA) system employing bipolar molecular signalling. By exploiting intra-chip oversampling at the FC, three linear detectors following the principles of maximum ratio combining (MRC), zero-forcing (ZF), and minimum mean-square error (MMSE) are developed and further enhanced through a feedback-assisted interference subtraction (FAIS) scheme that combines single-tap ISI feedback equalization with near-to-far successive MAI subtraction. Owing to the complementary structure of bipolar molecular emissions, the signal-dependent counting noise corresponding to the two molecule types can be jointly modeled in a symmetric and information-independent manner to support unified linear detection and FAIS processing. Numerical results demonstrate that oversampling effectively improves detection reliability, while increasing the molecular emission budget alone is insufficient to mitigate near–far effects. Moreover, FAIS provides significant performance gains, particularly for far NSs. Full article

This study examines how artificial intelligence (AI) contributes to contemporary processes of authenticity evaluation by functioning as a multimodal diagnostic cue in consumer decision-making. Drawing on survey data collected from 468 visitors at Terra Madre Salone del Gusto in Turin, Italy, the study tests a structural model comprising five latent constructs: Authenticity Trust, Perceived AI Usefulness and Diagnosticity, Multimodal Value, User Engagement, and Behavioural Intentions. The findings indicate that heritage-based and institutional authenticity cues remain foundational in consumers’ evaluations, but are increasingly associated with interaction with AI-supported information perceived as credible and diagnostically informative. Multimodal inputs—particularly the integration of textual, visual, and auditory narratives—are positively associated with perceived multimodal value and user engagement within AI-supported evaluation. Experiential enjoyment during interaction with the AI system is positively associated with behavioural intentions to adopt AI-supported evaluation tools, while behavioural intentions encompass both adoption readiness and a stated willingness to pay a premium for products perceived as authentic. Although the use of a convenience sample limits generalisability, the results highlight the broader potential of multimodal AI systems to enhance perceived diagnostic clarity and evaluative confidence in complex cultural and consumer environments. Conceptually, the study advances the notion of augmented authenticity, defined as a hybrid evaluative process in which tradition-based trust mechanisms are interpreted in relation to perceived AI diagnosticity and multimodal coherence. By situating AI within culturally embedded processes of meaning-making rather than purely instrumental evaluation, the findings contribute to interdisciplinary debates on technology-supported trust processes, consumer judgement, and the societal implications of AI-supported decision-making. Full article

This work is axiomatic and structural in nature and is not intended as a phenomenological physical theory, but as a framework clarifying minimal informational primitives from which geometric and dynamical descriptions may emerge. We present a background-independent framework in which physical geometry, interaction-like forces, and spacetime arise as effective descriptions of constrained relational information rather than as fundamental entities. The only primitive structure is a network of degrees of freedom linked by admissible informational relations, each subject to quantifiable constraints on accessibility or flow. The motivation is to identify whether a single minimal relational primitive can account jointly for the emergence of geometry, forces, and spacetime, without presupposing a manifold, fields, or fundamental interactions. The framework is formalized using weighted relational graphs in which constraint weights encode limitations on information flow between degrees of freedom. Effective geometry is defined operationally through minimal constraint cost along relational paths, yielding an emergent metric without assuming spatial embedding. Relational evolution is modeled via a minimal configuration-space dynamics defined by local rewrite moves, and a statistical description is introduced through an informational action that governs coarse-grained response rather than serving as a fundamental dynamical law. Curvature-like observables are defined using transport-based comparisons of local accessibility structure. Within this setting, metric structure emerges from constrained relational accessibility, while curvature-like behavior arises from heterogeneity in constraint structure. Effective forces appear as entropic or informational action gradients with respect to coarse-grained control parameters that modulate relational constraints, and are interpreted as emergent responses rather than primitive interactions. A finite worked example explicitly demonstrates the emergence of nontrivial distance, curvature proxies, and an effective force via geodesic switching under constraint variation, without assuming fundamental spacetime, fields, or particles. The results support an interpretation in which geometry, forces, and spacetime are representational features of constrained information flow rather than fundamental elements of physical law. The framework clarifies conceptual distinctions and points of compatibility with existing approaches to emergent spacetime, and it outlines qualitative expectations for regimes in which smooth geometric descriptions are expected to break down. The work delineates the scope and limits of geometric description without proposing a complete phenomenological theory. Full article

Polymer-based insulation materials are widely used to enhance the energy efficiency of buildings; however, their growing application raises concerns related to resource use and end-of-life management. Rigid polyurethane (PUR) foams are key core materials in structural insulated panels due to their favorable thermal and mechanical performance, yet their life cycle environmental impacts—particularly at end-of-life—remain insufficiently quantified. In this study, a cradle-to-grave life cycle assessment (LCA) of PUR-based insulation used in structural insulated panel systems is conducted in accordance with ISO 14040/44 and EN 15804 standards. The assessment is performed using Sphera LCA software (version: GaBi 10.5) and the CML 2016 impact assessment method. Formulation-level variations in rigid PUR foams, including changes in methylene diphenyl diisocyanate content and pentane blowing agent ratio, are explicitly incorporated to evaluate their influence on key environmental impact categories. The results indicate that increasing pentane content leads to higher global warming potential, while this effect may be mitigated or intensified by concurrent changes in diisocyanate content and foam density in fully formulated systems. Three end-of-life scenarios—landfilling, incineration with energy recovery, and mechanical recycling—are analyzed. The findings provide material-level, decision-relevant insights that support environmentally informed formulation strategies and contribute to the development of more circular polymer-based insulation solutions for the built environment. Full article

Plastic shrinkage and self-desiccation, along with the associated early-age cracking, are still among the most important factors that influence long-term performance of concrete structures, including durability. Superabsorbent polymers (SAPs) have been widely researched for application in concrete to mitigate shrinkage through facilitating effective internal curing by releasing water into the mixture to promote continuous hydration of cement. The acoustic emission (AE) monitoring technique, due to its high sensitivity, has proven very effective in tracking the process of water release by SAPs in concrete during early-stage curing. Typically, AE parameters such as cumulative activity, amplitude and energy are utilized to characterize the kinetics of curing processes. While these parameters indicate well the internal activity of SAPs in time, they do not offer information on the precise location of the active sources within the material’s volume, leaving a crucial gap in the understanding of the ongoing microstructural changes caused by internal water distribution and cement hydration. In this sense, AE event source localization can offer information about the active zones of water hydration activity in the material 3D domain, allowing detection of their evolution during concrete curing. Meanwhile, Acoustic Emission Tomography (AET) computes ultrasonic velocity distributions in different periods of monitoring, which are governed by acoustic characteristics of the concrete mixtures, to visualize material stiffness development spatially and temporally. This level of insight is particularly important for SAP concrete, where uniformity of internal water curing is essential for ensuring long-term durability and material soundness. By visualizing how the hydration sources evolve in real time, these methods offer an effective, non-destructive, and cost-effective solution for early-age concrete quality control, which would be challenging to achieve through other techniques. Full article

Malaria in pregnancy remains a major driver of poor maternal and neonatal health outcomes in sub-Saharan Africa. For decades, intermittent preventive treatment in pregnancy (IPTp), with sulphadoxine-pyrimethamine (SP), has mitigated malaria-associated health risks, but concerns have been raised regarding accumulated Plasmodium falciparum dihydrofolate reductase (dhfr) and dihydropteroate synthase (dhps) mutations on the efficacy of SP. Western Kenya, including Busia County, is a high malaria transmission setting where molecular surveillance of dhfr and dhps mutations remains limited. This study assessed the prevalence and haplotype structure of dhfr and dhps mutations in P. falciparum isolates from Busia County, Kenya. A total of 66 samples of P. falciparum isolates collected from patients attending Matayos Sub-County Hospital between November 2024 and January 2025 were analysed. PCR amplification and Sanger sequencing targeted dhfr codons C50R, N51I, C59R, S108N/T, I164L, and dhps codons I431V, S436A/F, A437G, K540E, A581G, and A613S/T to determine mutation frequencies, haplotypes, and combined dhps and dhfr haplotype profiles. High frequencies of dhfr and dhps mutations were observed across the parasite isolates. The most common dhfr substitutions included N51I (85.2%) and C59R (75.4%), while S108N (32.8%) and S108T (19.7%) were detected at lower frequencies. Dhfr haplotypes identified included N51I + C59R, N51I + C59R + S108N, and a N51I + C59R + S108T + I164L variant. The I164L mutation was detected at a frequency of 18.0% and was observed exclusively on a non-canonical S108T background (19.7%). Dhps haplotypes were dominated by A437G (92.3%), K540E (40%) alone, and the A437G + K540E double mutant. Combined dhfr and dhps haplotype analyses revealed circulation of classical dhfr triple-mutant (N51I + C59R + S108N) backgrounds with dhps A437G. Quintuple haplotypes (dhfr N51I + C59R + S108T + I164L with dhps A437G) and rare complex haplotypes incorporating both I164L and K540E or I164L and S436F were also detected. These findings indicate the persistence and circulation of both canonical and non-canonical dhfr and dhps haplotypes in P. falciparum isolates from Busia County. This study highlights the need for continuous molecular and phenotypic surveillance to clarify the functional and epidemiological significance of parasites carrying S108T and I164L mutations, and to inform IPT policy. Full article

Introduction: Rapid and reliable neurovascular imaging is critical for time-sensitive diagnosis in acute cerebrovascular disorders, yet conventional magnetic resonance imaging (MRI) workflows remain constrained by acquisition speed, motion sensitivity, and limited integration of physiological context. We introduce the Intelligent Neurovascular Imaging Engine (INIE), a sensor-informed, topology-aware framework that jointly optimizes accelerated data acquisition, physics-grounded reconstruction, and cross-scale physiological consistency. Methods: INIE combines adaptive sampling, structured low-rank (Hankel) priors, and topology-preserving objectives with multimodal physiological sensors and scanner telemetry, enabling phase-consistent gating and confidence-weighted reconstruction under realistic operating conditions. The framework was evaluated using synthetic phantoms, a translational porcine stroke recanalization model with repeated measures, and retrospective human datasets. Across $N_{\mathrm{runs}}=120$ acquisition–reconstruction runs derived from $N_{\mathrm{animals}}=18$ pigs with animal-level train/validation/test separation, performance was assessed using image quality, topological fidelity, and cross-modal consistency metrics. Multiple-comparison control was performed using Bonferroni/Holm–Bonferroni procedures. Results: INIE achieved acquisition acceleration exceeding 70% while maintaining high reconstruction fidelity (PSNR $\approx 35$–36 dB, SSIM $\approx 0.90$–0.92). Topology-aware analysis showed an approximately twofold reduction in Betti number deviation relative to baseline accelerated methods. Cross-modal validation in a PET subset demonstrated strong agreement between MRI-derived perfusion parameters and metabolic markers (Pearson $r\approx 0.9$). INIE improved large-vessel occlusion detection accuracy to approximately 93% and reduced automated time-to-decision to under three minutes. Conclusions: These results indicate that sensor-informed, topology-aware, closed-loop imaging improves the reliability and physiological consistency of accelerated neurovascular MRI and supports faster, more robust decision-making in acute cerebrovascular imaging workflows. Full article

The Neuroaesthetics-informed approach to the urban environment examines how the sensory properties of buildings, streets, and public spaces are processed by the human brain, and how this processing affects health, well-being, and behavior. Drawing on neuroscience, psychology, and architectural research, it examines how attributes such as organized visual complexity, fractal structure, materiality, color, light, scale, and spatial configuration shape perceptual fluency, stress regulation, affective states, cognition, and even influence social interaction in cities. The literature discussed was identified through targeted searches of peer-reviewed journals in neuroscience, psychology, architecture, urban design and public health, with emphasis on studies examining perceptual processing, affective responses, psychophysiological indicators, and health-related proxies in relation to environmental form, as opposed to general environmental health work. Practical applications are discussed. Full article