Search Results (2,403)

Background: Obesity-related metabolic dysfunction includes adipose inflammation, hepatic steatosis, insulin resistance, dyslipidemia, and intestinal disturbances. Avenanthramides are oat-specific phenolic amides, and their contribution to metabolic responses to oat foods is difficult to attribute because beta-glucan and the wider oat matrix can affect the same endpoints. This narrative review examines their mechanisms, exposure biology, evidence attribution, and translational readiness. Methods: Cell, animal, pharmacokinetic, and human studies were organized by chemical definition and intervention format, including purified congeners, characterized foods, enriched matrices, and whole-oat products. Parent compounds, circulating metabolites, target tissues, and clinical outcomes were interpreted separately. Results: In cell and animal models, avenanthramides influence NF-κB-related inflammation, redox regulation, hepatic insulin signaling, glucose production, fatty-acid metabolism, and intestinal ecology. Human studies demonstrate dietary exposure to parent compounds and metabolites, while clinical evidence comes mainly from small enriched-food exercise studies. Among the studies identified and appraised in this narrative review, none established an avenanthramide-specific effect on adiposity, liver fat, insulin sensitivity, dyslipidemia, or other cardiometabolic outcomes. Conclusions: The current literature supports measurable exposure and candidate mechanisms; a validated anti-obesity effect requires targeted clinical trials. Next studies need stable, analytically defined preparations, metabolite-informed dose selection, matched food controls, and trials that link measured exposure with prespecified clinical outcomes. Full article

When a virtual power plant (VPP) participates in energy and reserve markets, day-ahead bids, reserve commitments, and real-time delivery share the same internal resource constraints, while aggregate models cannot readily trace internal responsibility allocation or identify local shortfalls. This study develops a fixed-responsibility partitioning framework for day-ahead bidding and real-time delivery. Fixed membership mappings are screened under a unified budget; resource-type-specific reserve certificates and sustained-delivery constraints are embedded in a finite-support Wasserstein distributionally robust optimization (WDRO) model; and hierarchical model predictive control executes the market commitments. The 365-day evaluation retains three non-dominated candidates, $\mathrm{K}\in \{6,7,8\}$, whose mean operational-fitness objective values are reduced by 25.5%–43.1% relative to the corresponding independent spectral-clustering baselines. In a common 30-day ablation study, detailed partition responsibilities increase mean daily adjusted operating profit by CNY 6442–8162 and reduce settlement deviation by 1.19–1.23 MW relative to two equivalent-responsibility rules. Here, adjusted operating profit is profit net of balancing-correction cost, settlement deviation is the schedule–settlement difference, and partition tracking error is the deviation between partition targets and aggregated resource response. The directions of these effects remain consistent across two independent 10-day windows, and hierarchical real-time coordination further reduces settlement deviation and partition tracking error. Public-aggregate-data replays show that the profit and deviation effects of WDRO relative to sample average approximation (SAA) vary with market settings and node-downscaled inputs. As an engineering extension, bounded contracted-capability factors, defined as multipliers on market-committable capability, increase mean daily adjusted operating profit by 6.00% in the 2024 holdout set, and attribution analysis indicates that most of this gain is associated with the average contracted-capability factor and released fast-response headroom. Under the tested settings, fixed-responsibility partitioning enables the continuous transfer of resource-type-specific day-ahead responsibilities into real-time resource control and makes the trade-offs among profit, delivery quality, and execution cost explicit. Full article

Farmland shelterbelts can provide broad microclimatic and production benefits, but these benefits may coexist with localized competition near the tree–crop interface. Their effects also vary with environmental conditions, shelterbelt attributes, and crop type. We searched Web of Science and China National Knowledge Infrastructure for field studies conducted in China and published between 1980 and 2023. A total of 120 studies were retained, providing 1377 treatment–control comparisons. Log response ratios and random-effects models were used to quantify shelterbelt effects on wind speed, summer air temperature, air relative humidity, crop yield, thousand-grain weight, and crop yield in study-defined edge zones. Subgroup analyses examined the moderating effects of mean annual precipitation, shelterbelt structure, main−belt spacing, shelterbelt height, stand age, orientation, and crop type. Shelterbelts reduced wind speed and summer air temperature by 35.80% and 4.01%, respectively, and increased air relative humidity by 13.45%. Crop yield and thousand−grain weight increased by 16.57% and 12.28%, respectively, whereas crop yield in study−defined edge zones decreased by 20.47%. Shelterbelt height and stand age significantly moderated microclimatic responses and edge-zone yield loss, while crop type significantly moderated crop yield and thousand−grain weight. These results demonstrate that broad protective and production benefits can coexist with localized near−tree yield penalties. The findings provide evidence for context−specific shelterbelt management and highlight the need to account for spatial variation in tree–crop interactions. Full article

The unified expression of the mixed, dynamic and scattered navigation situation information in complex port area environments in a computable mathematical model is the foundation for ships to achieve intelligence and unmanned capability. Existing studies remain insufficient in terms of characterizing complex navigation situations involving multiple interacting factors, such as ship attributes, dynamic encounter relationships, spatial constraints, environmental conditions and navigation rules. To address this issue, a mathematical expression method for navigation situations is proposed. The ship interest perception area is first defined and discretized to characterize the directional anisotropy of surrounding situation constraints. Then, the ship interaction field, encounter conflict field, and navigation restriction field are constructed and integrated through normalization and weighted coupling. Environmental impacts, navigation-rule compliance, direction weights, and direction consistency are further incorporated to map the comprehensive situation constraint distribution into a virtual guidance direction, and a computable relationship between situation space and short-term behavioral preference space is established. Finally, the model is calibrated and validated using real ship data. The results demonstrate that the proposed model can effectively characterize directional multi-source constraints in typical complex port scenarios and generate directional preferences that are reasonably consistent with actual short-term ship motion, providing a structured information basis for navigation situation understanding and upper-level autonomous decision-making of unmanned ships. Full article

Project experience is distributed across individuals, project artifacts, team interactions, and organizational arrangements, making its transfer across project and temporal boundaries a multilevel systems challenge. Although after-action reviews, debriefs, retrospectives, postmortems, project reviews, and lessons-learned practices provide organized means of learning from experience, the interdependent components, transformation processes, and feedback relationships through which they generate reusable experiential knowledge remain insufficiently explained. This study systematically reviewed 106 English-language scholarly publications selected from 4157 records retrieved from the Web of Science Core Collection and Scopus. The evidence was synthesized through functional classification of evidence, typological analysis, thematic synthesis, and systems-oriented interpretive synthesis. The review establishes a common analytical domain for structured review practices based on four defining attributes and identifies four ideal-type configurations distinguished by their primary triggering mechanisms and knowledge boundaries. Across these configurations, four interconnected clusters of key cognitive tasks transform project experience materials into a shared interpretive foundation, reusable experiential knowledge, and a basis for future action. These transformations constitute a multilevel feedback architecture comprising short within-project and long cross-project loops, but may break down at five points under task–cognitive, social–political, and organizational–technological conditions. This study reframes structured review practices as a multilevel socio-technical learning system that connects actors, evidence, cognitive processes, knowledge artifacts, organizational uptake, and feedback from subsequent action. It thereby provides a systems-oriented conceptual basis for the design and diagnosis of structured reviews and for future research on human–AI support in project-based organizations. Full article

Existing watermarking methods for copyright protection of OpenDRIVE high-definition maps have difficulty balancing robustness and geometric accuracy. This study proposes a geometry-constrained robust watermarking algorithm that exploits the parametric representation of OpenDRIVE. From a symmetry perspective, the signed curvature–length feature used by the geometric carriers is invariant under translation, rotation, and ideal positive uniform scaling. This transformation invariance contributes to stable watermark extraction when the map’s global position, orientation, or scale is changed. A multidimensional carrier pool comprising geometric shapes and road attributes is constructed, and absolute quantization index modulation enables orthogonally decoupled embedding across carrier types. Levenberg–Marquardt optimization and topology-aware chain correction are further used to preserve geometric continuity and topological consistency. Experiments show that the algorithm maintains visual imperceptibility and file-size stability while remaining robust to geometric transformations, cropping, and format sanitization. Scenario simulations conducted in esmini revealed no evident degradation of road smoothness in the test scenarios defined in this study, indicating that the algorithm satisfied the map usability criteria under the experimental conditions. Full article

Background/Objectives: Unexplained infertility (UI) is defined by the absence of detectable abnormality on standard evaluation, which raises the possibility that the causative defect lies at the level of intracellular signaling rather than at the level of gamete number or hormone concentration. The PI3K/Akt pathway governs primordial follicle activation, granulosa cell survival, and the acquisition of oocyte competence, but AKT2 transcript abundance in the somatic follicular compartment has not been characterized clinically in UI. We compared cumulus/granulosa cell AKT2 transcript levels and follicular fluid Akt and phospho-Akt (Ser473) protein levels between women with UI and women undergoing intracytoplasmic sperm injection (ICSI) for isolated male factor infertility.  Methods: This was a prospective case–control study of 128 women (64 UI, 64 male factor) aged 23–35 years, all stimulated with a GnRH antagonist protocol and recruited December 2020–May 2021. AKT2 expression in cumulus/granulosa cells recovered at denudation was quantified using RT-qPCR (ΔΔCt, GAPDH reference). Total Akt and phospho-Akt (Ser473) were measured in follicular fluid using ELISA and normalized to the number of oocytes retrieved. Oocyte maturation, fertilization, day 3 embryo quality, and day 5 blastocyst quality were assessed using Alpha/ESHRE Istanbul consensus criteria. Correlation analyses were exploratory and reported with Benjamini–Hochberg false discovery rate (FDR) adjustment. Results: Baseline characteristics, including age, body mass index, antral follicle count, AMH, FSH, LH, oocytes retrieved, and duration of infertility, were comparable between groups. Granulosa cell AKT2 ΔCt was higher in the UI group (3.46 ± 1.47 versus 2.68 ± 1.18; p = 0.001), corresponding to a 1.72-fold lower AKT2 transcript level (ΔΔCt 0.78; Cohen’s d = 0.59); the difference persisted after adjustment for age, body mass index, AMH, basal estradiol levels, and previous IVF attempts (adjusted ΔCt difference 0.74, 95% CI 0.25–1.24; p = 0.004). Follicular fluid total Akt (11.55 ± 4.08 versus 11.75 ± 3.60 relative units; p = 0.78) and phospho-Akt (21.05 ± 7.14 versus 19.81 ± 7.24; p = 0.34) did not differ, nor did values normalized per oocyte. Oocyte maturation rate (0.72 ± 0.25 versus 0.76 ± 0.18), fertilization rate (44.6 ± 29.5% versus 42.2 ± 25.6%), day 3 good-quality embryo rate (25.0 ± 25.8% versus 26.6 ± 23.8%), and good-quality blastocyst rate (30.2 ± 25.8% versus 20.5 ± 18.5%) were all comparable. Of 24 exploratory correlations, only two survived FDR adjustment. Both correlations were in the male factor comparison group and both involved the small blastocyst subgroup: total Akt per oocyte (ρ = 0.738) and phospho-Akt per oocyte (ρ = 0.728) versus good-quality blastocyst rate (n = 17; FDR p = 0.011). AKT2 ΔCt did not correlate with any embryological endpoint in either group. Conclusions: Cumulus and granulosa cell AKT2 mRNA was reduced approximately 1.7-fold in women with unexplained infertility, despite indistinguishable ovarian reserve, ovarian response, and embryological performance and despite unchanged follicular fluid Akt protein. Because the comparison group consisted of women from couples undergoing ICSI for male factor infertility rather than women of proven fertility, the difference cannot be attributed specifically to unexplained infertility, and the findings describe transcript abundance rather than pathway activity. Confirmation against a fertile comparison group, with protein-level assessment in the same cells and clinical pregnancy endpoints, is required. Full article

Purpose: Early detection of glottic cancer is essential for better outcomes, but current diagnostic methods remain largely invasive, highlighting the need for reliable non-invasive alternatives. Acoustic voice signals offer a non-invasive screening input, but their clinical value depends on whether signal-processing features and learned models can distinguish malignancy from acoustically similar benign lesions rather than merely separate pathological from healthy voices. Despite growing research on acoustic analysis combined with machine learning (ML) techniques, no systematic synthesis of this evidence currently exists. Therefore, the present review aimed to identify acoustic features that differentiate early glottic malignancies from both benign vocal fold lesions and normal vocal function using various ML techniques. Method: Following PRISMA 2020 guidelines, a comprehensive literature search was conducted across Scopus, EBSCO, Ovid (Embase), and PubMed databases through November 2025. Eighteen studies met inclusion criteria, and PROBAST was used for quality appraisal of included studies. Data extraction focused on acoustic feature categories, ML techniques, classification performance metrics, and validation strategies. Results: Nine acoustic feature categories emerged, with cepstral coefficients (particularly MFCCs) most prevalent across 55.6% of studies. Binary pathological-versus-normal classification achieved consistently high accuracy (96–98.3%) across both traditional machine learning and deep learning approaches. However, malignant-versus-benign discrimination demonstrated substantially lower performance (81–87.88% accuracy, AUC 0.631–0.91), with voice-only models proving insufficient. Multimodal models incorporating clinical variables or laryngoscopic images achieved higher performance, but their results cannot be attributed to voice features alone. All 17 prediction studies were judged at high overall risk of bias, predominantly because of small effective sample sizes, model-selection optimism, possible data leakage, and limited independent validation. Conclusions: ML can detect broad voice pathology, but current evidence is insufficient to support stand-alone acoustic screening for early glottic cancer. Future studies require clearly defined cancer-specific targets, patient-level analysis, standardized acquisition, nested model development, calibration, and independent multicentervalidation. Full article

Integrating Wire Arc Additive Manufacturing (WAAM) into the Selective Paste Intrusion (SPI) process enables the fully additive fabrication of reinforced concrete structures with complex geometries. Previous investigations have demonstrated that the thermal impact of the WAAM process can adversely affect the SPI process. Thus, dedicated cooling strategies are required. One proposed approach increases the vertical distance between the welding point and the particle bed by introducing a defined vertical protrusion of the reinforcement bar. This configuration may give rise to shadowing effects, here understood as a process-induced disturbance of material deposition in the vicinity of the protruding bar. Two distinct manifestations are considered in parallel. The first is a geometrically projected shadowed region within the particle bed, depending on bar diameter and inclination. The second is a layer-wise modification of the contact zone along the lower half of the bar surface within the bond length, largely independent of inclination. To isolate the geometric component from thermal effects, the present study focuses on controlled reinforcement configurations with constant vertical protrusion. Two hypotheses are tested: bond decreases with increasing bar diameter (H1), and, at constant diameter, with decreasing inclination angle (H2), the latter being the signature of the projected shadow. To assess these effects, reinforcement bars with a constant vertical protrusion of 40 mm and varying inclination angles were embedded into the particle bed, and concrete specimens were produced above them using the SPI process. Bar diameters of 8 $\mathrm{m}$$\mathrm{m}$, 16 $\mathrm{m}$$\mathrm{m}$, and 25 $\mathrm{m}$$\mathrm{m}$ and inclination angles from 0° to 90° in 15° increments were investigated systematically. Bond strength was determined using push-through tests derived from RILEM RC6, and the bond response was evaluated against both a quantitative measure of the projected shadowed area and a process-based indicator of the affected contact zone. The bar diameter dominates the bond response, most pronounced at the developed-interlock and capacity levels. The inclination angle produces no monotonic trend from 0° to 90°, and individual angle contrasts remain largely within the experimental scatter. The projected shadowed area cannot consistently explain the observed behaviour and is at most a secondary factor, whereas the layer-wise contact-zone disturbance along the lower bar surface is the most probable interpretation of the data. The findings identify shadowing as a boundary condition for reinforcement integration in SPI: the observed bond reduction at the developed-interlock and capacity levels is attributed to the layer-wise contact-zone disturbance rather than to the projected shadowed area, an attribution that remains a hypothesis until the contact zone has been verified directly. Full article

Idiopathic pulmonary fibrosis (IPF), hypersensitivity pneumonitis (HP), and systemic sclerosis-associated interstitial lung disease (SSc-ILD) share the same structural outcome: extracellular matrix (ECM) deposition. Whether this shared endpoint reflects shared or distinct molecular programs remains unresolved. Differential expression results from four GEO datasets representing IPF, HP, non-IPF ILD, and SSc-ILD were intersected with the 1027-gene human matrisome masterlist and classified by threshold-defined disease preference. All four diseases shared a 21-gene upregulated matrisome core, and the matrisome fraction rose with cross-disease sharing, from 4.3% of single-disease upregulated genes to 45.7% of genes upregulated in all four (significant Cochran–Armitage trend), and the enrichment persisted when any single cohort was removed. Apparent disease preference was largely attributable to unequal statistical power: of 29 genes measurable in all four datasets, 24 showed a concordant sub-threshold effect in at least one comparator disease. Category composition of the threshold-defined signatures did not differ significantly between diseases, and the exploratory pathway panel is reported within diseases only, because significance scales with cohort size. In a within-cohort comparison of IPF with chronic HP in GSE150910, with platform, cohort, and control population held constant, matrisome genes were over-represented among the 2732 genes separating the two diseases, and 205 matrisome genes distinguished them. Fibrosing ILDs share a cross-cohort ECM core, and the apparent disease preference of the remaining signatures largely reflects differences in statistical power between cohorts. Disease-preferential matrisome expression is nonetheless detectable when disease and study are not confounded, so the limitation lies in threshold-based cross-study intersection rather than in the matrisome compartment itself. Full article

Pancreatic ductal adenocarcinoma (PDAC) resists checkpoint blockades outside uncommon molecularly selected populations. This narrative review relates clinical combination studies to four overlapping resistance mechanisms: deficient antigenicity, presentation and priming; restricted effector-cell access; suppressive myeloid and regulatory-cell programs; and T-cell dysfunction. The grouping is an organizing heuristic, not a validated treatment-selection algorithm. A source audit through 5 September 2026 reconciled a nonexhaustive inventory of 85 supplied study/cohort entries and relevant additional reports; 84 inventory entries remain in the synthesis after the exclusion of 1 trial. Trial design, endpoint success, component attribution and pharmacodynamic evidence were assessed separately. PA.7 and CISPD3 did not improve their primary survival endpoints when checkpoint blockade was added to chemotherapy. Positive or apparently favorable findings require design-specific interpretation: NASCA changed several components, KG4/2015 pooled randomized and nonrandomized controls, and early vaccine signals have not established a routine benefit. POLAR did not meet its co-primary activity criteria; preliminary SWOG S2001 results did not demonstrate benefits from adding pembrolizumab to olaparib. dMMR/MSI-H remains an established tumor-agnostic selection biomarker, while exploratory PA.7 and tissue-state signatures require independent validation. Human immune changes, immunogenicity and target engagement should not be equated with clinical efficacy. Future trials should test defined component contributions, appropriate pharmacodynamic hypotheses and patient-reported outcomes, with sampling adapted to disease setting and feasibility. Full article

Velocity distributions in curved open-channel flows exhibit strong three-dimensionality and nonlinear behavior, posing challenges to both accurate prediction and physical interpretation. Using measured velocity data from nine discharge–water-depth combinations in a laboratory 180° open-channel bend, this study developed an integrated eXtreme Gradient Boosting (XGBoost)–SHapley Additive exPlanations (SHAP) framework, with multiple linear regression (MLR), random forest (RF), and a back-propagation neural network (BPNN) used for comparison. Leave-one-condition-out cross-validation was used to evaluate the predictive accuracy and stability of the four models. A stratified sampling strategy was then adopted to construct the training dataset, allowing information from all flow regimes to contribute to robust parameter calibration; the two data-partitioning strategies yielded broadly comparable predictive performance. Using models trained with stratified sampling, multidimensional model evaluation was further conducted using global statistical metrics, segment-wise predictive performance, held-out extreme-condition tests, and measured–predicted agreement, among other criteria, with XGBoost consistently showing the best performance. Multilevel SHAP analyses quantified global feature importance, pairwise interactions, streamwise variations in feature contributions, SHAP–PDP dependence relationships, and condition-specific attribution. The SHAP results indicate a two-level attribution structure in the model: hydraulic variables jointly define the global velocity baseline, and their contribution signs can switch between positive and negative. Spatial variables characterize cross-sectional velocity redistribution. Strong discharge–depth interaction is associated with width-to-depth-ratio-dependent adjustment of the bend flow field. The proposed framework establishes a complete experiment-driven prediction–mechanism interpretation workflow for sharply curved open-channel flow and provides new quantitative insight into model-represented multifactor hydrodynamic interactions in open-channel bends. Full article

Due to the widespread deployment of large-scale satellite constellations, Spatial Information Networks (SINs) exhibit increasingly high-order node and service coupling characteristics, rendering them vulnerable to node removal and cascading failures. Traditional graph-theoretic models fail to capture the inherent multi-node cooperative relationships within SINs, while conventional centrality metrics overlook service coupling features and cross-community propagation risks, leading to inaccurate key node identification. To address these issues, this paper proposes a key node mining method based on soft community partition and hypergraph interweaving degree. The method first constructs a hypernetwork to characterize the high-order associations among three types of services—communication, remote sensing, and navigation. Second, a probabilistic generative model, Hypergraph-MT, is introduced to detect overlapping communities and capture the multi-role attributes of satellites. Finally, the Interweaving Degree (IW) and its derived Bridge Score (IWBS) are defined to quantify node importance from two dimensions: load capacity and cross-community connectivity. Experimental results demonstrate that, compared with degree centrality and betweenness centrality, the proposed method increases the service interruption rate from 27.4% to 64.8% under a 5% removal ratio, and the service efficiency loss is elevated by more than 60%. In comparison with pure interweaving degree removal, IWBS triggers deeper cascading removal at a 30% removal ratio, reduces the removal cost by 8.9%, and improves the input–output ratio by 8.2% under high-intensity removal. Moreover, the algorithm exhibits linear scalability and strong robustness to parameter variations. The proposed method significantly enhances the accuracy and efficiency of key node identification in SINs, providing theoretical support for constellation deployment optimization and priority protection decision-making. Full article

Background: Pediatric thrombosis (PT) is a rare clinical entity manifesting from neonatal life to adolescence with possibly severe clinical complications and increasing prevalence in the last decade. Its pathogenesis has been attributed to a multitude of factors, all of which share stress and inflammation as a common denominator. Although stress-induced inflammation, marked by the upregulation of proinflammatory interleukins, such as IL-1β, creates a prothrombotic environment, its relation with thrombosis remains incompletely defined, especially in the context of PT, which differs substantially from adult thrombosis. Here, we aimed to epigenetically explore the potential link between PT and stress-induced inflammation through a combinatorial approach. Methods: Initially, we bioinformatically identified candidate stress-specific miRNAs in childhood, followed by subsequent experimental assessment in serum samples of PT patients and healthy controls in relation to subjectively perceived stress levels and the functional +3953C/T genetic polymorphism of the IL1B gene, which affects the circulating levels of the proinflammatory and stress-induced interleukin 1beta (IL-1β). Results: The bioinformatic analysis identified miR-34a-5p as the most stress-specific candidate microRNA in childhood, exhibiting the highest gene-target coverage (80.6%) of the developed panel of adversity-related genes, but is also known to regulate IL1B expression. The expression of serum miR-34a-5p was not significantly influenced by subjectively perceived stress; however, its expression was significantly reduced in the presence of the T allele of the functional +3953C/T polymorphism of its target gene, IL1B, associated with increased levels of the stress-induced proinflammatory and simultaneously prothrombotic IL-1β cytokine (FC:0.57; p = 0.024). Conclusions: The observed downregulation of miR-34a-5p in the presence of the IL-1β-increasing T allele possibly indicates a dynamic regulatory relationship, which, alongside its previously established long-term downregulation in PT, renders miR-34a-5p a promising candidate molecule for bridging the biological processes of stress-associated inflammation and thrombosis. In addition, its bioinformatically yielded candidate stress-specific role holds great potential for the non-invasive evaluation of adversity-related stress in childhood. Full article

This paper reports the Sophimatic Multi-Agent System (MAS), the first integrated operational implementation of the six-phase Sophimatics framework: a three-tier containerised prototype (React/FastAPI/MySQL, ~25,000 lines of code) with an agent catalog of 1300+ Digital Twin-inspired LLM personas, a three-mode selection architecture, and per-agent weight disclosure. The pipeline executes the six Sophimatics phases, including STℂNN complex-time processing ($T = t_{real}+ i·t_{imag}\in \mathbb{C}$), whose instance here is untrained and excluded from empirical claims, and human-in-the-loop feedback bounded at three iterations. Agents are selected automatically by a five-step expertise-vector rule, manually via a hierarchical picker, or semi-automatically via slot-based proposals. Two instrumentation indices are reported: the Lexical Grounding Index τ (fraction of response tokens whose stems occur in the source documents) and, as an internal diagnostic of the feedback loop, the Feedback Alignment Index A. Three single-session use cases on public corpora are reported (Zoom and Coca-Cola 10-Ks, GDPR). Mean τ is 0.73 and mean A is 0.80. Expert ratings differ from single-agent baselines by +2.2 to +2.8 points on quality and +4.2 to +4.3 on coverage metrics; both raters were affiliated with the authors’ research group. The protocol for the validation of the grounding index against human judgement is specified in full, with its conditions, sample size and decision criteria, so that it is testable ahead of that work. A compute-matched and random-agent comparison over 27 sessions separates the observed difference into a component attributable to heterogeneous personas and one attributable to expertise-based selection. Measured end-to-end latency scales close to linearly with the number of activated agents, with a small fixed per-session overhead (R² = 0.996 for a two-parameter fit against N = 1–16). Together, the empirical use cases document the end-to-end operation of the pipeline, while the specified protocols define the controlled validation that remains to be carried out. The current evidence remains preliminary and does not establish general superiority over simpler architectures. Full article