Abstract: Background: Regulatory frameworks such as the Belmont Report, the Common Rule, and the Declaration of Helsinki require informed consent to ensure participants understand a study’s purpose and can make voluntary decisions about their involvement. Regulations including the General Data Protection Regulation (Regulation (EU) 2016/679) further emphasise that consent must be freely given and revocable without disadvantage. Although informed consent forms (ICFs) are intended to be clear and accessible, they have become increasingly lengthy and complex. Large language models (LLMs) offer potential to navigate and interpret this complexity and have shown promise in biomedical information extraction tasks. However, their susceptibility to hallucinations limits reliability in high stakes settings. Retrieval augmented generation (RAG) can mitigate such errors. This study evaluates the integration of LLMs with RAG for reviewing data reuse language in ICFs and their ability to interpret complex textual structures. Methods: Firstly, we processed 438 ICFs from different trials, including multi-countries, languages and versions of ICFs. Using expertly curated prompts, we extracted information about data reuse using GPT-4.1. Comparing the LLM-generated data reuse outputs with human expert ground truth, we evaluated accuracy and the time required to extract information for each ICF. To further validate the workflow, we evaluated an independent set of 488 ICFs spanning additional trials, languages, and regions. For this cohort, we assessed the correctness of LLM outputs along with the quality of supporting evidence provided by the model. Results: Across 438 ICFs, the system achieved 81.6% accuracy, which increased to 90% in a subsequent evaluation of additional 488 ICFs after prompt optimisation. Using a RAG-based approach, the system accurately extracted data reuse information across multiple languages and identified nuanced international regulatory requirements. Conclusion: This approach has the potential to significantly alleviate administrative burdens by automating labour-intensive processes, while also generating insights that could inform the standardisation of ICF creation. Ultimately, these advancements may contribute to reduce the complexity of ICFs, thereby improving their readability and comprehensibility for participants.

Abstract: Groundwater quantification is essential for sustainable water resources management, yet it is often hampered by limited data availability and difficulties in measuring spring discharges. This study investigates three carbonate aquifers in Central Italy’s Abruzzo region: the Genzana–Greco, Morrone, and Marsicano mountains. The aim is to resolve uncertainties in spring attribution, and groundwater flow patterns using isotopic analyses combined with field surveys. The Genzana–Greco aquifer was examined to clarify the sources of the Acquachiara spring and the previously unreported Germina spring, assessing whether recharge occurs locally or from the carbonate massif. In the Morrone mountain aquifer, discharge gains along the Pescara River through the Gole di Popoli were quantified, and spring isotopic compositions were compared to the main basal spring Giardino to better define groundwater contributions. For the Marsicano mountain aquifer, the role of Lake Scanno in feeding the Villalago springs was investigated through isotopic analysis of inflows, downstream springs, and basal aquifer discharge points to constrain the hydrogeological water budget. Overall, the integration of isotopic tracers with hydrological measurements allowed a more precise characterization of aquifer recharge areas, mean residence times, and groundwater flow paths, improving the understanding of regional water resources in a complex carbonate setting.

Abstract: For every prime p and every integer a, the backward finite difference δp(a) := a^p − (a − 1)^p equals the cyclotomic binary form Φp(a, a − 1), where Φp(X, Y) is the homogenisation of the p-th cyclotomic polynomial, and hence equals the norm NQ(ζp)/Q(a − ζp(a − 1)). For p = 3 this specialises to the identity δ3(a) = NZ[ω](a − ω(a − 1)), where ω = e^(2πi/3), connecting the individual cubic finite difference obtained by differencing the classical sum formula of Nicomachus of Gerasa (~100 CE) with the Eisenstein norm that appears in Euler's factorisation of a^3 + b^3. We develop this identity in three directions: (a) General cyclotomic framework. For each prime p, every prime divisor q of δp(a) satisfies q ≡ 1 (mod p), imposing an arithmetic sieve whose density ~1/(p−1) grows increasingly severe with p. (b) Arithmetic density. The values {δ3(a)}a≥1 form a thin subfamily of the Löschian numbers (norms in Z[ω]), with counting function ~√(N/3) versus the Landau-Ramanujan asymptotic CN/√log N for all Löschian numbers up to N. (c) Three-language equivalence. For the cubic case we prove a precise equivalence among: (i) divisibility of δ3(a), (ii) multiplicative order modulo q, and (iii) splitting of q in Z[ω]. We also give an elementary proof of the base case 1 + b^3 = c^3 (no positive-integer solutions), and derive 3-adic constraints on any hypothetical solution to a^3 + b^3 = c^3 via the Lifting-the-Exponent Lemma, without invoking unique factorisation in Z[ω].

Abstract: This study proposes SWEET-RL, a reinforcement learning framework for training LLM agents in multi-turn collaborative reasoning tasks involving human or agent partners. A step-wise critic is trained using intermediate evaluation signals derived from task progression rather than final answers. The method is evaluated on ColBench, consisting of 3,800 multi-turn collaboration sessions across software development and design tasks. SWEET-RL improves long-horizon task success rates by 24.3% and reduces dialogue-level error accumulation by 35.1%, demonstrating stronger robustness in extended collaborative interactions.

Abstract: A novel two–stage procedure for approximating solutions of nonlinear systems is introduced. The scheme employs two evaluations of the vector function F together with a single Jacobian computation, followed by the resolution of two linear subproblems that share an identical coefficient matrix. This structure reduces the computational burden and enhances the adaptability of the method with respect to existing alternatives. The design of the algorithm is motivated by criteria relating efficiency to the total number of functional evaluations, ensuring that the resulting strategy achieves the optimal convergence order permitted within this framework. A proof of the local convergence order is provided, and its accuracy is supported by a series of experiments on distinct nonlinear models, including problems arising from differential equations. The numerical evidence confirms that the developed technique reaches the theoretical convergence rate and performs favorably when compared with other methods of equal order. Moreover, we examine the dynamical features of the related parametric variant, offering additional understanding of its stability properties and iterative behavior.

Abstract: Enterprise architecture (EA) principles provide normative guidance for architectural evolution, yet validating whether EA models comply with such principles is typically performed manually and does not scale to continuous governance. This paper presents an ontology-based validation approach that enables automated compliance checking of ArchiMate models against EA principles. The approach (i) semantically lifts ArchiMate models into RDF/OWL as ontology instances grounded in ArchiMEO, (ii) structures natural-language principles using SBVR Structured English to reduce ambiguity and support traceability, (iii) enriches the resulting knowledge graph with inferred architectural relations through derivation rules, and (iv) operationalizes validation using SHACL constraints and SPARQL queries that produce explainable violation reports linked to concrete model elements. The approach is developed following Design Science Research and evaluated in three case studies (two real-world organizational settings and one controlled educational setting).The evaluation demonstrates that the approach supports repeatable execution of principle checks on evolving models, improves traceability of violations for architecture review and decision-making, and reduces manual effort by shifting substantial parts of compliance checking from human interpretation to automated constraint validation.

Abstract: Despite numerous studies on carbohydrate metabolism in gestational diabetes mellitus (GDM), the role of amino acid metabolic disturbances in the mother-fetus system remains insufficiently characterized, even though amino acids play a critical role in the develop-ment of fetal macrosomia (FM) and the programming of offspring metabolic health. This study included 62 mother–newborn dyads, stratified into clinical groups based on the presence of GDM and FM. Quantitative amino acid analysis was performed in maternal serum, umbilical cord serum, and amniotic fluid samples. Statistical analysis included Kruskal–Wallis, Mann–Whitney, chi-square tests, Spearman's correlation, and machine learning methods (Random Forest) with SHAP value calculation. Metabolic pathway analysis was conducted using MetaboAnalyst. Specific amino acid markers were identi-fied for each biological compartment. In maternal serum, GDM markers included glycine, 1-methylhistidine, γ-aminobutyric acid, lysine, and tryptophan, all showing significantly decreased levels. In cord blood, 11 amino acids exhibited reduced concentrations in GDM, including glutamine, glycine, asparagine, methionine, and proline. In amniotic fluid, GDM was associated with increased levels of lysine and 1-methylhistidine. In GDM complicated by FM, cord blood showed elevated lysine, proline, leucine, and al-lo-isoleucine, whereas amniotic fluid in this group was characterized by low homocitrul-line, asparagine, and lysine alongside high histidine levels. Correlation analysis revealed multiple associations between amino acids and clinical parameters, including an inverse correlation of fetal weight with homocitrulline and positive correlations with lysine and isoleucine. Metabolic pathway analysis indicated that GDM markers in maternal serum are associated with disturbances in biotin, glutamate, and carnitine metabolism, whereas cord blood markers implicated a broader spectrum of processes, including amino acid and purine metabolism. In amniotic fluid from GDM with FM, the methylhistidine me-tabolism pathway was additionally enriched, potentially reflecting specific alterations in neonatal muscle metabolism. GDM is accompanied by differential alterations in the amino acid profile across all investigated biological compartments, with the combination of GDM and FM characterized by unique metabolic signatures. The identified amino ac-ids may serve as potential biomarkers for early prediction of GDM and its complications, and offer prospects for targeted correction of metabolic disturbances.

Abstract: S. Tomé and Principe (STP) islands have been studied in recent years for their wide range of medicinal plants which exhibit several biological activities of great medicinal interest for some diseases. Experimental planning for optimization of several parameters was carried out by a full factorial of two levels of three factors for secondary metabolite extraction from Rauvolfia caffra leaves by using water and hexane at 25 and 40 ºC and 200 rpm for 0 and 5 days of incubation/extraction. The best conditions for highest extraction of phenolic compounds (i.e 89.90 moles gallic acid equivalent/g leaves)) was obtained at 25ºC, in H20 and 5 days of incubation. Several phytochemical assays were performed for characterization of these plant extracts and the highest levels of TFC, DPPH and Reducing power were obtained with aqueous plant extraction at 25ºC and for 5 days of incubation whereas leaves extraction with water at 40º C for 5 days of incubation revealed highest levels of ABTS scavenging activity. The levels of SOD and superoxide radical scavenging activities were highest with plant extraction with hexane at 25 and 40ºC for 5 days of incubation, respectively. The present report consists of a novel and intrinsic synchronous fluorescence and phosphorescence characterization of secondary metabolites from this plant extract. Intrinsic and non-destructive synchronous fluorescence was carried out in the range of 250 to 750 nm with a Δλ range of 5–30 nm which exhibited peaks at 320, 530, 550, 590, 650, 675, 690, 700, 710 nm in hexane plant extracts whereas aqueous extracts revealed only peaks at 382, 430, 460 and 530 nm. On the other hand, intrinsic and non-destructive synchronous phosphorescence was also performed which exhibited peaks at 430, 500 and 540 nm in aqueous extracts whereas hexane extracts revealed peaks at 320, 530, 560, 655, 675, 690 and 710 nm, respectively. 3-D spectra of secondary metabolites confirmed the peaks at 290, 320, 345, 400, 490 and 675 nm in plant extracts. FTIR spectroscopy was selected to investigate the structural properties of secondary metabolites in these plant extracts. Therefore, the present work describes a novel characterization of secondary metabolites by a non-destructive and intrinsic synchronous fluorescence techniques for plant extracts.

Abstract: Background: The standard cosmological model provides an excellent phenomenological description of the Universe. Motivated by persistent cosmological tensions, particularly in the Hubble constant (H0), this study proposes and tests the Gibbs Energy Redistribution Theory (GERT) as a thermodynamically grounded alternative to the expansion history model. Our central hypothesis is that a dynamical expansion history derived from fundamental thermodynamic principles empirically alleviates cosmological tensions, including the Hubble tension. At this stage, it provides a more physically coherent description of cosmic evolution, interpreting effects traditionally attributed to ad hoc dark components as emergent thermodynamic manifestations. Methods: We introduce a phenomenological, thermodynamically motivated model, the Gibbs Energy Redistribution Theory (GERT), in which the effective contributions of the matter- and lambda-like sectors are promoted to smooth, density-controlled functions, yielding a dynamical expansion history H(z) within the Friedmann Equation framework. We compared the resulting H(z) predictions with cosmic microwave background (CMB) shift-parameter constraints, baryon acoustic oscillation (BAO) distance measurements, and Type Ia supernova data. The analysis pipeline used standard open source scientific Python tools. Results: For the baseline implementation (the minimal-parameter reference fit described in the Methods), we obtained an excellent global fit (degrees of freedom (dof): χ2/dof ≈ 0.99) against CMB shift-parameter constraints, BAO distance measurements, and Type Ia supernova data, and inferred H0 ≈ 72.5 km s−1 Mpc−1, consistent with local determinations (e.g., SH0ES project). We quantified the deviations from the standard model in the diagnostic plots of H(z) and distance moduli. Conclusions: The framework yields concrete, testable predictions for late time expansion behavior, offering a physically coherent and causal narrative for cosmic evolution, and can be further constrained by future low-redshift probes.

Abstract:

Background: Mesh implantation is the standard of care in hernia repair. However, penetrating suture fixation may contribute to chronic pain and tissue irritation. This pilot study evaluates the feasibility of a hybrid fixation technique using a biodegradable UV-curable adhesive biomaterial in inguinal hernia repair.Methods: Ten male patients (20-40 years) with unilateral inguinal hernia underwent open repair and were allocated into two groups (n = 5 each): hybrid fixation approach (part of the mesh was secured conventionally and the remaining portion was stabilized with an experimental adhesive UV-curable biomaterial within 3 minutes) and conventional mesh fixation. Pain (VAS) and patient-reported outcomes (CCS, EuraHS QoL, SF-36) were assessed at day 1, day 8, 6 weeks, 12 months, and 24 months. Ultrasonography and thermography were analysed when available as exploratory assessments.Results: The adhesive-assisted partial self-stabilization reduced operative time compared with conventional fixation (52.0 ± 3.1 vs 60.2 ± 3.7 min). Postoperative pain (VAS) in the hybrid group decreased from 2.6 ± 0.55 on day 1 to 0.8 ± 0.84 on day 8, with complete resolution by 6 weeks. Foreign-body sensation (CCS) decreased from day 1 to 6 weeks in both groups (hybrid: 54.08% to 30.38%, control: 65.32% to 36.57%). No intraoperative complications and no hernia recurrences were observed during the 24-month follow-up. Overall SF-36 scores increased from 77.8 preoperatively to 92.4 at 24 months. Conclusions: In this pilot cohort, hybrid fixation using the UV-curable adhesive was feasible and was associated with shorter operative time, with no intraoperative complications and no recurrences observed during follow-up. Further studies of hybrid mesh fixation on larger cohorts are warranted.

Abstract: Reliable aboveground biomass (AGB) estimates for woody crops are required for carbon accounting and MRV; however, it remains unclear how LiDAR modality and sampling geometry influence plot-scale and tree-scale AGB predictions in intensively managed orchards. We benchmarked four LiDAR modalities across three Mediterranean woody-crop sites in Córdoba (Spain), IFAPA, Doña María, and Villaseca using open national airborne laser scanning (PNOA/ALS), Riegl ALS, unmanned laser scanning (ULS), and mobile laser scanning (MLS). The field inventory used 58 fixed-area plots (20×50 m; 0.1 ha) collected in December 2024-January 2025 (1,867 trees) and species-specific allometries based on D2r to derive tree and plot AGB; carbon was computed using wood carbon fractions (0.445 olive; 0.457 almond) and CO2e via IPCC conversion. Plot-level LiDAR metrics (e.g., mean height, p95, maximum height, and cover proxies) were extracted from normalized point clouds and modeled with Random Forest, XGBoost, and an ensemble under an 80/20 train-test split. Mean field AGB differed among sites (33.89, 30.94 and 12.76 Mg ha−1 for Villaseca, Doña María, and IFAPA). In the provided summaries, XGBoost achieved the lowest errors at IFAPA (RMSE = 0.400 Mg ha−1; R2 = 0.994) and Villaseca (RMSE = 0.872 Mg ha−1; R2 = 0.995), whereas PNOA was competitive at Doña María (RMSE = 0.725 Mg ha−1; R2 = 0.994). The results support cross-platform LiDAR for orchard AGB mapping and identify conditions under which open national LiDAR can enable scalable MRV. In addition, we evaluated TreeQSM-based quantitative structure models (QSMs) as an independent tree-level 3D reconstruction approach and examined their site-dependent agreement with field inventory estimates.

Abstract: The triangle finding problem is a cornerstone of complex network analysis, serving as the primitive for computing clustering coefficients and transitivity. This paper presents \texttt{Aegypti}, a practical algorithm for triangle detection and enumeration in undirected graphs. By combining a descending degree-ordered vertex-iterator with a hybrid strategy that adapts to graph density, \texttt{Aegypti} achieves a worst-case runtime of $\mathcal{O}(m^{3/2})$ for full enumeration, which matches the bound established by Chiba and Nishizeki for arboricity-based listing algorithms. For the detection variant ($\texttt{first\_triangle}=\text{True}$), we prove that sorting by non-increasing degree enables early termination in $\mathcal{O}(n\log n + d_{\max}^2)$ worst-case time when the maximum-degree vertex participates in a triangle, where the quadratic factor in $d_{\max}$ reduces to $\mathcal{O}(d_{\max}/C(v_{\max}))$ in expectation when the local clustering coefficient $C(v_{\max}) > 0$. Experiments on complement graphs of DIMACS maximum-clique benchmark instances confirm that detection terminates sub-millisecond on the majority of instances, while the matrix-multiplication baseline requires substantially more time on the same inputs.

Abstract: Automatic modulation classification (AMC) is a core capability for spectrum monitoring, adaptive receivers, and electronic support. Most radio-frequency machine learning (RFML) studies train multi-class classifiers on benchmark datasets that contain a single modulation per recording at baseband. In operational settings, however, the objective is often to detect only a small set of signals of interest, making large multi-class models unnecessarily expensive to train and deploy. This paper investigates an alternative workflow based on targeted binary transformer detectors and evaluates their robustness under practical RF complications. Using the RadioML 2018.01A dataset, we construct binary detection tasks with BPSK as the signal of interest and introduce three increasingly realistic conditions: (i) center-frequency shifts away from baseband, (ii) sampling-rate mismatches via decimation and interpolation, and (iii) multi-signal mixtures where modulations co-occur either in frequency (simultaneous transmissions) or in time (temporal concatenation). The results show that baseband-trained detectors do not generalize to center-frequency-shifted signals, and multi-signal interference can cause complete detection failure unless explicitly modeled during training. We investigate early-exit transformer inference to reduce computation on high-confidence examples, showing it maintains (and occasionally improves) detection performance. We also evaluate inter-modulation transfer learning and intra-modulation adaptation from baseband to mixed- and multi-signal scenarios.

Abstract:

Rust, caused by Puccinia arachidis, is one among the most destructive fungal diseases constraining global groundnut (Arachis hypogaea L.) production. While the development of disease-resistant varieties stands as the most effective approach to preventing substantial yield losses, the genetic mechanisms underlying resistance to rust is not yet well understood, emphasizing the necessity for further detailed research. In this study, 184 accessions from the ICRISAT groundnut mini-core collection were evaluated for rust resistance at Dharwad, India, across multiple seasons, as well as in Vietnam for one season. Whole-genome resequencing-based genome-wide association study (GWAS) identified five highly significant marker trait associations (MTAs) for rust resistance (p = 5.22 × 10-13 to 7.21 × 10-08). Among these, two robust rust-associated kompetitive allele specific PCR (KASP) markers, snpAH00607 at chromosome Ah01 and snpAH00609 at chromosome Ah17, were validated across diverse set of breeding and pre-breeding lines. These markers were linked to candidate genes encoding sterol C4-methyl oxidase 1-2, implicated in brassinosteroid-mediated salicylic acid signalling, and MYB transcription factor known to be associated with defense responses. The identified SNPs, validated markers, and candidate genes will serve as important resources for marker-assisted breeding of rust disease resistant groundnut varieties.

Abstract: This article aims to contribute to a relatively understudied area of financial development, namely, the internal dispersion of trading activity. The focus is not on overall financial development measures such as total market capitalization and liquidity but rather on trading diversification, defined as the proportion of trading volume contributed by firms outside the VTX, representing the top ten most frequently traded firms. The article uses data from the World Bank’s Global Financial Development Database. The sample is constructed as a balanced panel of 23 countries over the period 2002-2021, starting with a sample of 38 countries. The article uses four key explanatory variables, namely, relative size of deposit-taking banks (DBS), remittance inflows (REM), market capitalization excluding the top ten firms (MCX), and outstanding international public debt (IPU). The article uses a combination of panel econometrics, hierarchical clustering, and machine learning methods. The econometric results show that a diversified financial system structure and remittance inflows are strongly, positively related to overall and less concentrated trading activity, while bank dominance and reliance on international public debt are related to more concentrated trading activity. The clustering results show significant cross-country heterogeneity and a core-periphery structure. The machine learning results show that, using all models, equity market structure is again found to be the most important explanatory variable, with external financial flows being important as well. The article concludes that equity market structure is key to understanding internal dispersion, with important policy implications.

Abstract: The present essay introduces and develops the concept of Homo constellatus as a new anthropological and metaphysical archetype, emerging from the visionary corpus of Theodor-Nicolae Carp – specifically in The Conquest from Within and the Incoming Platonic Revolution, Birthing Homo constellatus: From the Humans Who Know Everything to the Humans Who Connect Everything and Andromeda as Archetype: The Neurodiverse as the First-Called in a Post-Neurotypical Cosmology. Situated at the intersection of neurodiversity, symbolic anthropology, cosmopoetics and Platonic theology, Homo constellatus represents not a technocratic leap in cognitive performance, but a metaphysical transfiguration of the human being. It signals an evolutionary milestone defined not by biology or machinery, but by communion, emotional depth and the recovery of sacred symbolic consciousness. This emerging figure is metaphorically birthed through intellectual exile and metamorphic suffering. It is not a successor by gene but by soul: the one who integrates fragmentation into communion, rationality into sacred symbol, and loneliness into ontological design. Moreover, the present manuscript proposes the emergence of a new literary current called Axiological Cosmopoetics following two major “waves” in the history of European literary discourse (Classicism and Modern Romanticism), and it has as its core theme a poetic restoration of order and harmony in the Universal realm, and Homo constellatus appears to be the central archetype of such a new current. Axiological Cosmopoetics is transdisciplinary in nature and integrates axiology (value-theory) with cosmopoetic symbolism, drawing on literary theory, philosophy of art, religious and secular philosophy, as well as cultural myth, to articulate ethically ordered imaginaries of human reintegration, particularly amid times of post-traumatic restoration. The emergence of Homo constellatus signals a shift in consciousness marked by an integrative tendency: a gravitational impulse toward reconstellation. Rather than dissolving difference or imposing uniformity, this archetype seeks to reposition disparate elements within a wider field of meaning, drawing fragmentation toward coherence without erasing plurality. Its movement is not centrifugal but centripetal – not toward collapse into sameness, but toward relational alignment. In this sense, reconstellation describes a reordering of perception: domains once held in tension – reason and reverence, structure and fluidity, individuality and communion – are gradually perceived as dynamically interrelated. The archetype does not force convergence; it inclines toward integration. Like a system approaching a higher-order equilibrium, Homo constellatus orients consciousness toward patterns of deeper resonance, where complexity is neither denied nor absolutized, but harmonized within an ever-expanding constellation of meaning. Through references to sacred geometries – such as Gabriel’s Horn and Brâncuși’s Column of Infinity – Carp envisions Homo constellatus as a being who lives in harmony with the poetic architecture of the cosmos. Drawing on Eastern Orthodox theology, Platonic intimacy, and neurodivergent phenomenology, the essay reframes suffering as sacred gestation and neurodivergence as prophetic sensitivity. The new human archetype of Homo constellatus challenges existing anthropocentric and ableist paradigms by revealing that emotional resonance, symbolic intelligence, and spiritual wholeness are not byproducts of evolution, but its very telos. In dialogue with these literary and philosophical works, Elegy of Mine Exile serves as a lyrical-theological meditation on sacred alienation. This elegy does not mourn exile as punishment – it reclaims exile as consecration. The speaker, likened to a prophetic voice or even to the Ambassador of the Morning Star himself, is rejected by the world not because he is broken – but because he burns too brightly. By distinguishing between the fall of Christ as the true Morning Star – through humility – and the fall of Lucifer through pride, the study describes the speaker’s descent is both sacrificial and revelatory: he suffers not to disappear, but to transmute. Through metaphors of collapse and rising, the poem places spiritual alienation in direct dialogue with divine gestation – turning mourning into Morning. The expanded version of Elegy of Mine Exile amplifies this vision by incorporating ecological, theological, and anthropological dimensions. The soul’s descent is reimagined as the fermentation of the New Eden; cosmic orphanhood becomes an archetypal human condition; and the emergence of Homo constellatus is framed as both elemental fusion and divine inheritance. The eschatological arc of the poem culminates in a nuptial invocation – where divine breath, moral resuscitation, and relational transfiguration give birth to a new co-creative covenant. Suffering becomes not merely transformative, but luminous: the seedbed for Edenic restoration and planetary rebirth. Further expanding this vision, the literary commentary Luceafărul: The Morning Star, Neurodivergence, and the Birth of Homo constellatus interprets Mihai Eminescu’s Hyperion not merely as a tragic figure of cosmic distance, but as a neurodivergent archetype whose refusal of worldly assimilation prefigures Homo constellatus. Hyperion’s vertical longing, divine remoteness, and emotional clarity are re-read as prophetic attributes – illuminating how divine exile is inseparable from metaphysical fidelity. Crucially, the symbolism of the Morning Star – also known as the Evening Star – reveals a prophetic paradox: those who were unseen will become luminous. In eschatological terms, these hidden figures will not only come to light, but also sound the alarm of a nearing apocalyptic threshold, becoming the sensitive instruments of revelation before the advent of the Adversary of the Icons of the Universe on Earth (deemed as anti-Universal Messiah in religious discourse). The poem Behold, the human communing with the Stars continues this metaphysical arc, giving lyrical voice to the full manifestation of Homo constellatus. In this cosmic hymn, suffering culminates in stellar transformation; exile gives way to supernova; and the fallen Morning Star becomes the harbinger of the Eternal Morning. The New Eden is not a return, but a convergence – symbolized by the reassembled Pangaea and the fusion of past and future into infinity. Through mythopoetic eschatology, the poem celebrates a spiritual anthropology rooted not in control, but in communion – marking the fulfillment of a cosmic gestation first conceived in exile. It stands as the poetic benediction of this archetype's emergence. The model proposed here extends into geology and astronomy, as it displays a planetary cartography: the Alpine-Himalayan mountain system as observed in geography, is interpreted as the spinal cord of the “Old, Neurotypical World,” while the Rocky-Andean chain represents the backbone of a “New, Neurodiverse World.” These two continental bodies – much like the approaching collision of the Milky Way and Andromeda as hinted in astronomy – are destined not for destruction, but for synthesis. Their eventual convergence is envisioned as a tectonic, civilizational, and spiritual transformation – an emergence of a post-neurotypical world, one capable of holding both structure and fluidity, reason and reverence. Finally, the invocation of the Morning Star – held in tension between Christ’s descent and Lucifer’s fall in Christianity – serves as a theological fulcrum for this cosmopoetic vision. By distinguishing between the one who chose humility and the one who chose pride, the poem and its accompanying commentary avoid conflating rebellion with brilliance. Christ’s descent becomes the archetype of divine communion, while Lucifer’s fall reveals the tragic consequence of light divorced from love. This distinction safeguards the eschatological hope at the heart of Homo constellatus: that the radiant ones misunderstood by the world are not deviant, but divine harbingers of a healed cosmology – symbols not of rebellion, but of redemptive luminosity. This essay articulates the philosophical, theological, and societal implications of Homo constellatus across multiple domains: from education to sacred urbanism, from intimacy to symbolic linguistics, from planetary ethics to liturgical cosmology. It proposes that the future of humanity lies not in transcending our nature through technology, but in transfiguring it through love, meaning, and communion. Through its interdisciplinary method and poetic form, this work positions Homo constellatus as a necessary archetype for healing a fragmented world, initiating a planetary renaissance grounded in reverent complexity, emotional literacy, and the sacred rhythm of becoming. In its expanded formulation, the Homo constellatus framework now extends beyond symbolic anthropology into trauma-informed civic imagination. Concepts such as Urban Wombs, graduated relational housing, Touch Plazas, lullaby infrastructures, and platonic intimacy literacy are rearticulated not as utopian communal fantasies, but as phased, ethically scaffolded prototypes. These trauma-informed urban prototypes may incorporate calibrated biophilic design within dense metropolitan contexts, integrating natural light and ecological elements as regulatory supports for psychological stability rather than as aesthetic idealism. These models prioritise sovereignty, consent, and psychological pacing, especially in contexts involving survivors of violence and crime, including domestic abuse, coercive control, assault and trafficking. Platonic intimacy is therefore repositioned not as universal remedy, but as a regulated and optional dimension within broader recovery ecosystems where autonomy precedes affection and safeguarding precedes proximity. By embedding strict ethical guardrails – continuous consent, trauma-informed facilitation, independent oversight, and tiered participation structures – the vision of Homo constellatus matures from prophetic archetype into disciplined compassion. The new human is no longer defined solely by sacred exile, but by the capacity to design environments where relational safety becomes infrastructural. In this development, communion ceases to be abstract aspiration and becomes civic architecture. The eschatological horizon remains luminous, yet it is tempered by legal, psychological, and cultural accountability. Thus, Homo constellatus evolves from metaphysical figure into socially responsible archetype: radiance integrated with restraint, transcendence integrated with trauma-awareness, and love integrated with law. Ultimately, the literary and philosophical vision of Homo constellatus does not remain a theoretical construct, but emerges as a liturgical anthropology – a life-form shaped by presence, patience, and symbolic resonance. Its birth reframes neurodivergence as divine invitation, demanding structural repentance in education, theology, and care. It invites a post-neurotypical civilization to reorient itself not around efficiency, but reverence. Though rooted in Orthodox theology and European literary myth, its archetypal signature is transcultural: it echoes the bodhisattva, the qalandar, the wounded healer – universal figures of radiant exile and sacred return. Thus, this vision does not end in abstraction, but in enactment: the return of the human soul to the cosmic choir – not as soloist, but as constellation.

Abstract: Turnout locomotor activity is a potentially informative indicator of health and welfare in older horses, yet objective field data in seniors remain limited. We examined whether a brief turnout recording could detect associations between chronological age and locomotor activity in senior horses under routine conditions. In this single-site observational study, 28 senior Selle Français horses (17–35 years) contributed 122 paddock sessions (2 h each), with total distance and mean speed quantified using a Polar Team Pro sensor. Associations with age were assessed using linear mixed-effects models adjusted for temperature and precipitation. Age was decomposed into between-horse and within-horse components. Log-transformed total distance was negatively associated with age (β = −0.062 per year, 95% CI −0.094 to −0.032; P < 0.001), driven by the between-horse component (β = −0.063; q = 0.003), with no within-horse association (P = 0.75). Mean speed showed a similar pattern, with a significant between-horse association (β = −0.060; q = 0.003) and no within-horse effect (P = 0.87). These findings suggest that brief paddock actimetry may help characterize between-horse heterogeneity and support group-level welfare monitoring. Larger multi-site cohorts with denser follow-up and external validation are needed before individual trajectories or clinical interpretation can be established.

Abstract: Refactoring is essential for developing maintainable software. Using Large Language Models in software engineering is widespread, but compared to well-established domains such as code generation, reliable refactoring is still relatively underexplored. In this paper, we perform a broad analysis on the refactoring capabilities of small open-weight language models (SLMs) by evaluating 12 models on 3,453 Python programs. Our study focuses on the two defining aspects of refactoring: behavior preservation and code quality improvement. We evaluate these properties using unit tests and various code metrics. Across models ranging from 0.5B to 8B parameters, most models improve code quality. Larger models are more reliable, as they preserve behavior more consistently. Reasoning models often make more significant changes while refactoring. Allowing models to generate reasoning traces improves performance, but only for models larger than 4B. For smaller models, reasoning in fact reduces refactoring reliability. The difficulty of the underlying task affects refactoring performance, with more complex tasks associated with higher failure rates. Our results indicate that current open SLMs can support refactoring tasks, especially larger ones with reasoning capabilities, but they are best used with human oversight.

Abstract: This paper presents a practical implementation of relative primary radiation thermometry (RPRT) together with MultiFixRadSoft, an open-source software package developed in accordance with the Mise-en-Pratique for the kelvin (MeP-K) for realization of the thermodynamic temperature scale and uncertainty evaluation under the new definition of the kelvin. The software enables realization of temperature scales using ITS-90 metal fixed points as well as metal–carbon and metal–carbide–carbon eutectic high-temperature fixed points (HTFPs) for both radiation thermometers and radiometers. It incorporates automated routines for melting-plateau analysis, including determination of the point of inflection, liquidus point, and melting range, together with correction modules for size-of-source effect, detector nonlinearity, emissivity, and temperature-drop. Validation is demonstrated through experimental realization using six fixed points (Cu, Fe–C, Co–C, Pd–C, Ru–C, and WC–C) and a linear radiation thermometer. The software also supports ITS-90 extrapolation procedures and flexible calibration schemes (n = 1 to n ≥ 3), with automated Sakuma–Hattori fitting and full uncertainty propagation compliant with MeP-K requirements. Results show excellent agreement with manual analyses and published data, confirming the correctness of the implemented algorithms. By integrating data processing, scale realization, and uncertainty analysis within a unified and transparent framework, MultiFixRadSoft provides a robust and accessible tool for traceable radiometric thermometry, supporting emerging NMIs and industrial laboratories while promoting wider adoption of primary thermodynamic temperature realization methods.

Abstract: Chronic kidney disease (CKD) represents an escalating global health burden, fundamentally altering morbidity and mortality trajectories across the world, particularly as it advances into end-stage renal disease (ESRD). Beyond the primary decline in renal filtration and excretion, a wide spectrum of endocrine and metabolic derangements frequently accompanies kidney failure, with thyroid dysfunction emerging as a critical complication. The current study was designed to rigorously evaluate the nuanced association between thyroid hormone dynamics—specifically thyrotropin (TSH), triiodothyronine (T3), and thyroxine (T4)—and renal status in three distinct cohorts: individuals with suspected thyroid issues but normal renal function (NP), non-dialysis kidney patients (NDKP), and patients undergoing maintenance hemodialysis (DP). Data were collected from a clinical setting in Bangladesh, involving 161 subjects. The results demonstrated that patients in the DP cohort exhibited slightly elevated thyroid hormone levels relative to those in the NDKP cohort. Specifically, within the subgroups of patients exhibiting normal or sub-reference hormonal levels, dialysis patients maintained higher concentrations than their non-dialysis counterparts. Demographic stratification further revealed that males, females, and individuals younger than 45 years were more likely to demonstrate restorative hormonal profiles in the DP group than in the NDKP group. These collective outcomes suggest that renal replacement therapy, specifically hemodialysis, may serve to stabilize or improve thyroid function in ESRD patients by potentially mitigating the suppressive effects of uremic toxins and normalizing homeostatic feedback loops.