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The human microbiome influences health and disease through diverse biochemical and functional outputs (e.g., enzymes, structural proteins, metabolites, and other cellular components) that affect nearly every aspect of human physiology. Metatranscriptomics (MT), an unbiased RNA sequencing approach, is a high-throughput and high-content method that quantifies both gut microbial taxonomy and active biochemical functions. Because microbial community composition and gene expression are dynamic, understanding temporal variation in the gut metatranscriptome across multiple time scales is essential. Here, we report the temporal dynamics of gut microbiome species and functions using a large cohort (n = 6157) with a clinically validated stool MT test. We quantified microbiome stability from hours to years and assessed taxonomic and functional resilience to major luminal perturbations, such as colonoscopy bowel preparation. Longitudinal analyses of samples collected within the same day, and across days, weeks, months, and years, revealed consistently high stability in both composition and gene expression within a single day and, importantly, across an approximate six-month period. Among individuals reporting stable diets and no antibiotic exposure, taxonomic and functional profiles remained stable for up to three years. Following colonoscopy preparation, our preliminary study of the microbiome demonstrated strong resilience, returning to its pre-procedure state within one week. Overall, these findings demonstrate that the gut microbiome is generally stable over a six-month time frame, with longer-term changes occurring gradually. These findings support the robustness of stool-based MT profiling for species-level and pathway-resolved functional analysis in longitudinal research and health applications. Full article

This study presents a focused review of digital storytelling research in industrial heritage using a bounded Scopus-indexed corpus covering the period from 2011 to February 2026. It examines whether regeneration-relevant interpretive claims in urban renewal contexts are supported by traceable research structures. As post-industrial landscapes undergo restoration and urban redevelopment, digital storytelling is frequently used to frame issues of memory, responsibility, and heritage legitimacy; however, the evidentiary basis of such claims remains insufficiently scrutinized. Adopting an outcome-traceability perspective, the study evaluates whether interpretation-related outcomes are supported by traceable links between mechanisms, constructs, measurement approaches, and evaluation design. A two-stage synthesis is conducted: Stage 1 provides a bibliometric profile of the Scopus-indexed corpus, revealing a fragmented publication landscape dominated by conference papers and prototype-oriented studies, while Stage 2 audits evidence chains across the screened analytical studies to assess whether commonly cited mechanisms, such as narrative meaning-making, affective engagement, and interactive exploration, are operationalised into explicit constructs and measurable indicators. Findings suggest that reported outcomes most frequently concentrate on immediate experiential responses, while higher-level outcomes such as awareness, attitudes, and learning are less consistently supported by robust evaluation designs. The study identifies recurring traceability gaps and outlines priorities for improving evidentiary consistency and comparability in industrial heritage digital storytelling research. Full article

The present paper is aimed at studying the convergence of the Yamabe flow in the case of noncompact solitons. The more specified example of locally conformally flat noncompact solitons is addressed with the aim to newly analyse the qualities of the Ricci scalar. The particular case of noncompact pseudo-Riemannian solitons is studied; moreover, in the instances of Schwarzschild and Generalized-Schwarzschild geometries, rescalings of spherically symmetric weights are performed. For this purpose, new results are achieved as far as the considered structures are concerned. The Myers Theorem is upgraded as the new Myers paradigm of spacetime-dimensional manifolds, where the Einstein Field Equations can now be taken into account. In particular, the Myers Theorems are studied here as far as their new implementation in General Relativity Theory is concerned. As a first important result, the Myers mean curvature is found to coincide with the Ricci scalar in General Relativity Theory, where the 4-position of the observer, from which the 4-velocity 4-vector is calculated from, is taken as that of the observer solidal with the reference frame of the photon. The following results are also of relevance. In more detail, the umbilicity conditions are applied. At a further step, the role of the umbilicity conditions in GR after the Myers Theorems are studied for weighted manifolds and specific new implications of weighted manifolds are developed. The description of the weighted Schwarzschild manifolds and that of the weighted Generalized-Schwarzschild manifolds are newly studied as follows: as a new finding, the Birkhoff Theorem is newly reconciled with the rotational ansatz of the metrised solitons, and the comparison with the previous results about the Brendle non-metrised solitons is accomplished with the outcome stressing the new roles of the new rescalings of the metric tensor with respect to the previous known results of the scaling of the metric tensor of the non-metrised solitons. In the present framework, these procedures allow one to prove the reconciliation of the EFEs with the Yamabe flow. The flow on the tipping lightcones is newly written. The umbilicity condition is studied in General Relativity after the upgrade of the Myers Theorems as far as the sectional curvatures are concerned; as a result, the Calabi–Bernstein description is implemented in General Relativity, as well as the Chen–Yau requirements, and the cases of weighted manifolds are taken into account. More specifically, the equal-time 2-dimensional space surfaces are studied analytically, onto which the weighted General-Relativistic solitons which satisfy the Einstein field equations after the Yamabe flow are projected due to the rotational ansatz. As an accessory introductory result, the class of Wu non-metrised solitons are proven to be discarded in several aspects of the Wu description as the conditions provided after the work of Wu are not compatible with metrisation. Full article

Scalable production of interactive 3D assets is a key requirement for XR-based applications, yet the functional integration of GenAI-generated assets into game engines remains challenging for non-expert users. This article proposes and validates a Prompt-to-Trigger workflow that links GenAI-based asset ideation and generation with the implementation of basic interactive behaviors (triggers) in accessible XR platforms. The study adopted a qualitative and exploratory approach, using systematic observation throughout a two-stage development process. This process included an initial phase where 3D assets were generated and refined using tools such as Tripo AI and Meshy, followed by an optimization stage to ensure compatibility with Blender and XR environments like A-Frame and Godot, and subsequently, the creation of AI-powered activation scripts. The results show that GenAI’s current 3D outputs frequently exhibit topological inconsistencies and rigging errors that compromise performance and real-time interoperability, requiring cleanup and optimization before deployment. The Prompt-to-Trigger workflow formalizes this bridge, positioning AI assistance as a functional layer for iterative logic generation. The resulting model provides non-expert creators with structured, actionable framework to prototype complex XR experiences for applied domains like education and multimedia communication. Full article

Achieving urban climate neutrality and interim mitigation targets requires rapid demand-side emission reductions, yet current user-centred interventions remain fragmented, are often concentrated on low-impact actions, and rarely provide a traceable basis for comparing outcomes, validity conditions, and equity implications across contexts. This paper reframes demand-side mitigation as a design problem of “use infrastructures”: integrated configurations of communication, product-technology, services, interaction, and governance that make low-carbon choices practicable within everyday routines. We introduce the Design Evidence Link (DEL) as a traceability device supporting ex ante configuration (selection and orchestration of levers) and ex post verification (monitoring, attribution of outcomes, and trade-off control). Through a design-led comparative analysis of nine international cases in high-impact sectors (household energy, ground mobility, food systems, and circular economy/materials), we derive and consolidate a shared extraction and coding protocol that links determinants (barriers and enablers) to design requirements and decision-grade metrics (carbon impact, adoption, continuity, and equity), explicitly qualifying uncertainty and evidence levels. Cross-case results show that effective interventions rely less on isolated information and more on coordinated action packages that reduce cognitive and economic frictions, enhance data credibility through standards and accountability, and embed follow-up mechanisms that support behavioural continuity. DEL also surfaces recurring validity conditions and failure modes (digital exclusion, trust erosion, rebound, and lock-in), translating them into operational criteria for policy and design. Compared with behaviour-change or theory-of-change framings, DEL focuses on the observable orchestration of integrated conditions of use and on the explicit grading of evidence. It should therefore be read as a structured analytical–operational framework for ex ante and ex post assessment, whose transferability remains conditional on source quality, contextual prerequisites, and the limits of the selected cases. Full article

The integration of vertical greenery systems (VGSs) into existing reinforced concrete (RC) buildings raises questions regarding interface kinematics and the permanent displacement of soil-retaining elements under seismic excitation. This study experimentally investigates the residual displacement of façade-mounted living walls and rooftop planter pods anchored to a deficient RC frame under shake table excitation. A 1:3 scale reinforced concrete frame was tested in two distinct phases: initially as a deficient, unretrofitted structure (Phase A), and subsequently as a retrofitted system integrated with vertical greenery elements (Phase B). High-precision terrestrial laser scanning (TLS) was employed before and after successive seismic excitation stages to generate dense three-dimensional point clouds. Cloud-to-cloud comparison techniques were used to quantify global structural displacement and local kinematic behavior of greenery components, while results were validated against conventional displacement sensors. The RC frame exhibited millimeter-scale permanent displacements consistent with draw-wire measurements. In contrast, planter pods demonstrated configuration-dependent behavior, including up to 8 cm translational sliding and rotational responses reaching 13° under repeated excitation, whereas living wall panels remained stable. Notably, a 95% reduction in point cloud density reproduced global deformation patterns with an RMSE of 3.03 mm and quantified peak displacements with only ~2% deviation from full-resolution results. The findings demonstrate the capability of TLS-based monitoring to detect differential kinematic behavior of integrated VGSs, while highlighting the variability in performance of friction-based rooftop anchorage utilizing different robust planter pod fixing systems. Full article

SARS-CoV-2 is the etiological agent responsible for COVID-19. While most research has focused on structural proteins, the accessory protein Open Reading Frame 8 (ORF8) has attracted attention for its role in immune evasion and the induction of a cytokine storm. Although the exact mechanisms underlying viral pathogenicity remain to be elucidated, oxidative stress has been proposed as a key contributing factor. In this study, we evaluated the effect of intranasal administration of ORF8 on arterial blood pressure and the antioxidant system in different organs of male BALB/c mice at 2- or 8 weeks post-administration. A significant increase in blood pressure and renal total antioxidant capacity was observed in the 8-week group, and decreased catalase activity in the prefrontal cortex was observed in the 2-week group. These findings suggest that ORF8 may contribute to long-term renal alterations and potentially to mechanism relevant to cognitive dysfunction associated with COVID-19. Full article

Cultural and natural heritage are increasingly framed as components of territorial governance rather than isolated conservation elements; yet, a structural gap persists between their strategic recognition in planning documents and their measurable integration into statutory land-use systems that guide spatial decision-making. This gap is particularly pronounced in protected areas, where ecological integrity, cultural and symbolic values, tourism functions, and socio-economic expectations converge within environmentally sensitive landscapes. This study develops and empirically applies a compatibility-based analytical framework that embeds Multi-Criteria Decision Analysis (MCDA) within the statutory spatial planning system of Kozara National Park. The framework combines (i) institutional analysis of legally binding planning instruments, (ii) zoning-aligned analytical units derived from the Special-Purpose Spatial Plan and Management Plan, and (iii) a weighted multi-criteria model incorporating ecological integrity, cultural–historical significance, tourism and recreation capacity under controlled use, and socio-economic feasibility. Climate-related disturbance exposure is incorporated as a planning-relevant modifier of ecological compatibility. Composite compatibility scores under the baseline configuration range from 2.55 to 3.85 across analytical units. Rank correlation analysis suggests a high degree of structural consistency across both alternative weighting configurations relative to the baseline scenario (Spearman’s ρ ≈ 0.90), with only limited rank reordering observed, primarily between the two highest-ranked analytical units. Dispersed low-intensity recreational configurations demonstrate the highest structural robustness, whereas infrastructure-intensive zones exhibit management-dependent compatibility. The findings show how spatial planning in protected areas can operationalize compatibility as a measurable decision-support principle without substituting statutory zoning logic. Full article

Underground infrastructure systems are typically managed as discrete technical assets rather than as integrated, adaptive systems. This paper develops the Body Underground framework, a structured biological analogy that synthesizes prior clinical and epidemiological metaphors into a multiscale conceptual model linking materials, facilities, networks, and governance. Building on Little’s clinical framing of infrastructure health and Bardet and Little’s epidemiological analysis of network failure clustering, the framework extends biological interpretation to anatomical, physiological, and homeostatic scales. The approach maps structural, hydraulic, sensing, protective, and regulatory functions to functional equivalents in living systems using explicit criteria of feedback, regulation, and measurability. The central objective of the study is to determine whether biological regulatory concepts—particularly homeostasis and hierarchical organization—can provide a coherent interpretive structure for understanding infrastructure health across material, facility, network, and governance scales. The resulting framework reframes resilience as dynamic regulatory balance rather than static robustness alone. It clarifies the methodological basis for constructing biological–infrastructure analogies, identifies measurable “vital signs” for infrastructure health, and outlines pathways toward operational translation through integrated monitoring and governance feedback. While conceptual in nature, the framework provides a structured synthesis linking material science, infrastructure engineering, systems resilience theory, and policy coordination. By organizing resilience concepts through cross-scale regulatory logic, the Body Underground model offers a coherent structure for integrating monitoring, diagnosis, and governance in the proactive management of underground infrastructure systems. Full article

Titanium dioxide (TiO₂) has evolved from a conventional photocatalyst into a sophisticated nano-platform that bridges environmental sustainability and biomedicine. This paper proposes a unified interfacial redox design framework that links the electronic-structure engineering of the TiO₂ with the spatial control of its reactive oxygen species (ROS). In the environmental sector, we highlight advances in photocatalytic detoxification, such as the cleavage of organophosphates via Ag-modified TiO₂, driven by doping and metal–support interactions. In the biomedical domain, TiO₂ is framed as an active bio-interface capable of coordinative protein binding. We specifically examine the “moonlighting” protein dihydrolipoamide dehydrogenase (DLDH) as a model for stable, oriented biofunctionalization. By integrating RGD-targeting motifs, these hybrid systems enable integrin-directed, localized photodynamic effects. We further address critical toxicological considerations, emphasizing that TiO₂ behavior is context-dependent and governed by particle size, crystallinity, and surface state. By synthesizing insights from catalysis and redox biology, this manuscript outlines principles for the rational design of safer, application-specific TiO₂ technologies. This convergence supports a transition from non-selective oxidation toward predictable, spatially confined redox outcomes in both complex environmental matrices and physiological systems. This review outlines key mechanistic insights and proposes design principles for controlled and context-dependent TiO₂ activity. Full article

This study investigates the seismic performance and behavior factors of reinforced concrete (RC) frames, focusing on the significant influence of masonry infill walls. While standard design codes like ACI-318, CSA-A23.3, and TBDY-2018 provide framework provisions, the structural contribution of infill walls is often neglected, leading to potential discrepancies between design assumptions and actual seismic response. The research employs a dual analytical approach, Nonlinear Static Pushover Analysis and Nonlinear Time History Analysis (NTHA), using ETABS 22 software. Four distinct structural configurations—Bare Frame (BF), Fully Infilled Frame (FIF), Partially Infilled Frame (PIF), and Soft Story Frame (SSF)—are evaluated to determine their overstrength, ductility reduction and response modification factors. The masonry infill walls are modeled using the equivalent diagonal strut method, accounting for their non-isotropic and brittle nature through parabolic stress–strain relationships. A core component of the study is the assessment of structural damage through a time-dependent Damage Index (DI), calculated by correlating displacement demands from NTHA with yield and ultimate displacements derived from idealized bilinear capacity curves. The findings highlight how the configuration of infill walls—specifically vertical and plan irregularities—modifies lateral stiffness, natural periods, and failure modes. The study concludes that accounting for the interaction between the RC frame and infill walls is critical for accurate seismic assessment, as these elements can transition failure mechanisms from ductile to brittle modes. Full article

Background: Occult lymph node metastasis (LNM) occurs in 30–80% of patients with clinically node-negative papillary thyroid carcinoma (cN0-PTC), partly owing to the limited sensitivity of current preoperative nodal assessment, and may contribute to postoperative recurrence. Conventional sentinel lymph node (SLN) biopsy, typically performed with a single tracer, has limited reliability for detecting occult metastatic nodes, which can result in either overtreatment or undertreatment with lymph node dissection. We aimed to develop a highly accurate multimodal prediction framework to accurately identify second-echelon lymph node metastasis (SeLNM) and non-sentinel lymph node metastasis (NsLNM). Methods: We prospectively enrolled 301 patients with cN0-PTC between April and October 2024, of whom 131 met the inclusion criteria. Intraoperatively, a dual-tracer technique combining carbon nanoparticles and indocyanine green was applied, and near-infrared imaging was used to record the entire SLN visualization process in real time. For each case, a 3 min video clip (150 frames) was captured. Two senior surgeons delineated regions of interest to generate 19,650 mask images. A total of 2048 spatial features and 20 temporal features were extracted, combined with 32 clinical variables, including demographics, ultrasound characteristics, and gene mutation status. Nine deep learning models were developed and evaluated using 10-fold cross-validation. Model performance was quantified using receiver operating characteristic curves, decision curve analysis curves, calibration curves, precision–recall curves, learning curves, and 12 metrics. Statistical comparisons were performed using the DeLong test, and models were further evaluated using a probability-based ranking approach. Shapley Additive Explanations (SHAP) analysis was applied to interpret key predictive features. The primary outcomes were SeLNM and NsLNM, defined based on postoperative histopathology. Results: The Long Short-Term Memory (LSTM) + Transformer model showed the best performance for both prediction tasks, with stable AUCs across training and testing (SeLNM: 0.980/0.982; NsLNM: 0.986/0.983). In the testing set, the model reached the same accuracy for both outcomes (94.7%) and showed strong sensitivity/specificity for SeLNM (94.7%/94.6%) and NsLNM (96.4%/91.5%). SHAP analysis indicated that time-series fluorescence flow features were the most influential predictors, followed by spatial structural features and SLN status. Conclusions: Dual-tracer SLN mapping with deep learning demonstrated encouraging intraoperative prediction of lymph node metastasis with interpretable features in this single-center cohort. Independent multicenter validation and prospective outcome studies are needed before considering clinical adoption. Full article

Background: Understanding how logistics structure affects fiscal performance and exposure to disruption is critical in import-dependent economies. This study examines the concentration of Ecuador’s import logistics system using customs revenue as an operational–fiscal proxy. Methods: The analysis uses 2023–2024 customs revenue data to evaluate modal and territorial concentration through the Herfindahl–Hirschman Index (HHI). Scenario-based stress tests are applied to assess sensitivity to redistribution and disruption shocks. Results: Results reveal a high dependence on maritime transport and a dominant customs district, with the Guayaquil–Maritime node accounting for most revenue. HHI values confirm strong concentration patterns. Scenario analysis shows that even moderate disruptions in dominant nodes generate disproportionate fiscal impacts, while limited modal diversification slightly reduces vulnerability. Conclusions: The findings indicate that logistics concentration constitutes a structural source of fiscal exposure. The study contributes by framing customs revenue as an integrated proxy linking logistics structure and vulnerability. However, results should be interpreted cautiously due to the short-term dataset, static analysis, and absence of behavioral responses. Full article

Compared to DVB-S2, DVB-S2X features a more intricate signaling structure. These signaling fields are employed not only in standard frames but are also frequently utilized within superframe structures. While rapid synchronization and decoding of these fields are critical, utilizing brute-force search methods incurs prohibitive computational costs. Therefore, this paper proposes a Joint Maximum Likelihood (JML) detection model tailored for the Fast Walsh–Hadamard Transform (FWHT). This approach allows for simultaneous synchronization and decoding while reducing number of real addition operations per codeword by approximately 15 times compared to brute-force methods. Consequently, the proposed architecture provides a highly efficient solution applicable to DVB-S2X and backward compatible with DVB-S2. Full article

This study provides a comprehensive evaluation of six volatility forecasting models applied to twelve dominant and less dominant cryptocurrencies across multiple time horizons using high-frequency intraday data. The exponential generalized autoregressive conditional heteroskedastic (EGARCH), integrated GARCH (IGARCH), standard GARCH, GJR-GARCH, lagged realized volatility (LRE), and heterogeneous autoregressive (HAR) models are systematically compared using 5 min computed return data from September 2018 to September 2020. Our analysis encompasses three forecast horizons (1-day, 7-day, and 30-day) to assess model performance under varying temporal constraints. Through univariate Mincer–Zarnowitz regressions, encompassing tests, and out-of-sample evaluation using root mean squared error (RMSE) and quasi-likelihood loss (QLIKE) functions, we identify significant performance heterogeneity across models and cryptocurrencies. The HAR model exhibits stronger predictive accuracy at short horizons, while EGARCH exhibits relatively stronger performance at longer horizons, although overall explanatory power declines as forecast horizon increases. Importantly, no single model consistently provides optimal forecasts across all cryptocurrencies. Consistent with prior evidence suggesting model performance varies across assets. Encompassing regressions reveal that combining HAR with EGARCH specifications significantly enhances explanatory power across all temporal frames. Out-of-sample Diebold–Mariano tests indicate that HAR generates the lowest forecast errors for most cryptocurrencies, though EGARCH performs exceptionally well for high-market-capitalization assets. These findings provide regime-conditional insights into horizon- and asset-specific volatility dynamics during the pre-institutionalization phase of cryptocurrency markets. The study contributes to emerging literature by incorporating less-dominant cryptocurrencies and offering robust empirical evidence on the asymmetric and persistent volatility characteristics unique to digital asset markets. These findings should be interpreted within the context of the 2018–2020 sample period, representing a pre-institutionalized phase of cryptocurrency markets, and may not fully generalize to structurally different market regimes characterized by increased institutional participation and regulatory development. Full article