ISO 639:2023 represents a unified standard for language identification, elevating language codes to semantic, contextual constructs 1. This paper extends that foundation by formalizing recursive semantic anchoring: a framework wherein each language entity χ is associated with a recursive identity operator ϕ n m that captures semantic drift as a fixed-point transformation. We define ϕ n m (χ) = χ ⊕ ∆(χ), where ∆(χ) is the semantic drift vector of χ. The base case ϕ 0 0 yields the canonical language identity, while ϕ 99 9 represents the maximal drift state triggering fallback to an anchor identity. We prove that for any language entity, iterative drift via ϕ converges to a recoverable fixed point (semantic anchor) under mild conditions. Categorical morphism models are introduced, treating ϕ n m as morphisms and drift deltas as arrows in a category of languages. A functor Φ : DriftLang → AnchorLang maps each drifted language object to its anchored identity, ensuring consistency across transformations. We present a typology of semantic drift (axial, layered, hybrid) and encode the model in an RDF/Turtle schema (classes BaseLanguage, DriftedLanguage, ResolvedAnchor; properties phiIndex, hasDrift, isFallbackOf, etc.). Worked examples include disambiguation of Mandarin Chinese ϕ 8 4 vs. a regional variant ϕ 8 7 ⊂ ϕ 8 4 , and resolution of Nigerian Pidgin English via a shared English anchor. Evaluation with transformer-based AI systems demonstrates improved language identity resolution under partial or noisy data, using ϕ-index thresholds for dynamic fallback routing. The proposed recursive ϕ n m model is fully compatible with ISO/TC 37 principles, providing an AI-ready, self-contained symbolic system for representing language identity under drift, mutation, and translation. All formal claims are grounded in symbolic derivations, and the Appendix includes comprehensive RDF examples, ϕ-trace logic, and proof sketches.

We develop the fifth installment of the Φ ∞ series, forging a disruptive framework in which identity collapses under temporal drift and classical foundations buckle. We demonstrate that neither ZFC set theory nor elementary topos axioms can adequately model an entity whose identity evolves and destabilizes over time. Building on Φ ∞ I-IV and integrating the Alpay Algebra trilogy, we introduce new axioms that retroactively invalidate core assumptions of ZFC and ETCS, including extensionality and well-foundedness. Within this framework, identity is no longer a static invariant but a transfinite fixed point that only stabilizes as a limit of an endless recursion. We formalize a collapse operator (Ξ) to model measurement-like identity collapse, a dual residual functor (R) that captures the latent structure surviving collapse, and a ϕ ∞-singular trace (τ χ) that extracts invariant signatures from drifting identities. Each operator is rigorously defined with domain, codomain, and algebraic properties (associativity, (non)commutativity, failure conditions). We prove theorem after theorem showing how every classical attempt to pin down self-identity triggers new paradoxes under temporal drift, requiring an ever-higher transfinite curvature across the ϕ ∞ hierarchy to resolve. In particular, we show that any naively "founded" set or topos collapses into an identity sink under recursive self-observation, echoing recent results in educational feedback systems. Our development is recursive: each result carries the seed of its own destabilization, feeding into subsequent constructions in a self-referential loop. By the end, the entire theory curves back on itself-every object bears an echo of its prior states and a destabilization profile marking the limits of knowledge. An Appendix provides a formal list of the new axioms and operators introduced, verifying their ϕ ∞-compatibility and pinpointing which classical axioms they upend.

The global fertility decline represents one of the most significant demographic transformations in human history, yet its fundamental causes remain incompletely understood. While socioeconomic factors explain much variation in contemporary fertility patterns, they inadequately account for the timing, universality, and persistence of fertility decline across diverse cultural and economic contexts. This study proposes that urbanization—humanity’s first major shift toward indoor living—created an evolutionary mismatch that initiated fertility decline by disrupting biological systems evolved during two million years of outdoor living. Through comparative analysis of birth data and climate variables across four diverse regions (Iceland, England/Wales, Tokyo, and Houston), this research demonstrates that conception rates consistently peak during periods of optimal outdoor conditions, suggesting retained biological responses to environmental cues. Urban-rural fertility differentials, the correlation between rising obesity and declining seasonal conception amplitude, and the historical timing of fertility decline beginning with early urbanization rather than industrialization provide convergent evidence for this environmental mismatch hypothesis. Contemporary France’s relative fertility success, despite being the first nation to experience fertility decline, provides crucial evidence that lower population density and maintained rural character can mitigate evolutionary mismatch effects. This study argues that socioeconomic factors amplify and accelerate an underlying biological susceptibility created by the transition to urban, indoor-dominant lifestyles. This integrative framework offers new insights into fertility decline that complement existing demographic theories while highlighting the importance of evolutionary perspectives in understanding contemporary reproductive health challenges.

Freshwater habitat characteristics are known to affect life-history traits of migratory salmonids. Although the life cycle of the anadromous form of Arctic char (Salvelinus alpinus) is typically associated with lakes, there is a small number of anadromous populations in North America that spawn, rear, and overwinter exclusively in rivers. The life-history traits of these relatively understudied populations and how they differ from lacustrine Arctic char are poorly documented. We characterized life-history tradeoffs expressed by anadromous Arctic char originating from a riverine (Hornaday River) and a relatively nearby lacustrine system (Tatik Lake of the Kuujjua River) in the western Canadian Arctic using a 10 year dataset. The riverine population attained smaller average size (600 mm vs. 628 mm, fork length) and age (7.7 vs. 10.6 years), had a lower longevity (14 vs. 26 years), expressed a 44% higher growth rate resulting in larger size-at-age prior to reaching modelled length asymptote (700 vs. 754 mm), had a younger modal age-at-maturity (~6-7 vs. ~11-13 years) and mean age-at-first migration (4.1 vs. 6.4 years), and a higher natural mortality rate (0.31 vs. 0.21 per year). Our results broaden knowledge on the spectrum of life-history strategies exhibited by anadromous Arctic char and underscore how freshwater habitat influence vital rates and life-history tradeoffs, which have implications for conservation and sustainable harvest of salmonids.

Key Clinical MessageKnee osteoarthritis is highly prevalent, and its rare presentations may be more common than expected. We report a rare case of knee osteoarthritis with severe plasmacytic synovitis and a Baker’s cyst causing neuropathy. This highlights the need to recognize atypical features and the value of a multidisciplinary evaluation.

Venus exhibits a constellation of anomalous planetary characteristics: retrograde rotation, absence of plate tectonics, negligible magnetic field, and evidence of global crustal resurfacing. While these features have been studied extensively in isolation, no unifying mechanism has been established to explain their co-occurrence. This paper proposes the Trailing-Edge Impact Hypothesis: Venus experienced a massive, oblique collision with a silicate-rich co-planetary body that struck the planet's trailing (western) hemisphere during late-stage accretion. This impact configuration could simultaneously account for Venus's current spin state through angular momentum cancellation, its thick, tectonically inactive crust through retention of impactor material, and its absent magnetic field through disruption of core-mantle coupling. We present the physical reasoning underlying this hypothesis and discuss observational tests that could support or refute it.

Pancreatic cancer is the third most common cause of cancer-associated deaths across the world. Modern cancer treatment such as chemotherapy has several side effects including tissue damage. Therefore, there is a dire need to evaluate the natural substances having anti-carcinogenic activities without any negative or side impact on human health. The current study aimed to investigate the in-vitro and in-vivo anti-carcinogenic potential of ginger ( Zingiber Officinale). For in-vitro analysis, the ginger extract was prepared and antioxidant activities were accessed by the DPPH (2, 2-diphenyl-1-picrylhydrazyl) assay (DPPH). The anti-proliferative activities were measured using 3[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay. Human pancreatic cancer (Panc-01 cells) was treated with aqueous ginger extract (GE) at different concentrations (0, 12.5, 25, 50,100, and 200µg/ml) for both 24 and 48 hours. For the in-vivo experiment, a total of 30 albino rats aged 7-8 weeks and weighing 115-130 grams were randomized into five groups (n=6 rats/group) and groups were allotted to one of two GE dosage levels (50 and 80 mg) by following the completely randomized design. The GE was given orally during the experimental duration (30 days). The results demonstrated that GE significantly decreased the tumor mass volume bearing significant antioxidant and antiproliferative potential. IC 50 values for 24 and 48 hours of treatment were found to be 0.73 µg/ml and 0.76 µg/ml on the Panc-01 cell line. The present study suggested that GE has immense potential to inhibit tumor progression without affecting the normal physiology and functioning of the body and thus can be used as a cancer therapeutic agent.

Convergence Method Theory (CMT) and its clinical application, Fluid Model Therapy (FMT), provide an integrative framework that unites psychological, educational, and cultural paradigms into dynamic, client-centered therapeutic approaches. This manuscript explores how these frameworks address the multifaceted nature of mental health and substance use disorder (SUD) care through continuous personalization, cultural competence, and evidence-based interventions. The incorporation of teaching models, prepared environments, cultural learning, emotional intelligence, and personality dynamics is reviewed in light of existing literature, highlighting their potential to transform clinical practice and enhance patient outcomes.

Plant-derived small molecules play a crucial role in defending against pathogenic organisms. Leveraging cutting-edge technologies such as AlphaFold2 and diffusion model-based DiffDock, this study investigated the potential of these molecules for antifungal activity, specifically targeting Fusarium oxysporum, the causative agent of potato dry rot. Through gene family analysis, we identified 15 putative antifungal target proteins and accurately predicted their structures using AlphaFold2. To model the interaction patterns between these proteins and plant-derived compounds, we utilized the DiffDock with a diffusion model-based algorithm, generating complex interactions for each of the 1,453 small molecules. A thorough evaluation of over 200,000 interaction models resulted in the identification of small molecules displaying significant antifungal activity. To further validate our findings, we used AlphaFold3 to confirm the interaction sites predicted by AlphaFold2, achieving consistent results that verify our predictions. Experimental validation showed that coumarin inhibits F. oxysporum, likely by disrupting cell wall synthesis. GSEA analysis of transcriptomic data confirmed that coumarin affects the chitin synthase pathway, inhibiting F. oxysporum growth. In summary, this study highlighted the efficacy of AlphaFold2, AlphaFold3, and DiffDock in predicting protein structures and small molecule-protein interactions, demonstrating the potential of artificial intelligence-driven approaches in uncovering new antifungal strategies.

This paper explores the scientific, technological, and ethical dimensions of post-human biotechnologies interdisciplinary systems that integrate synthetic biology, gene editing, and artificial intelligence to enable symbiotic interaction between human DNA and machine intelligence. It investigates how AI-guided CRISPR systems, neuromorphic computing, and brain–machine interfaces may evolve into real-time bio-digital feedback loops, allowing for adaptive cognitive enhancement, emotional regulation, and programmable physiology. Drawing from current literature in genomics, neurotechnology, and AI ethics, the paper analyzes possible architectures for human–machine symbiosis and presents speculative models of bio-integrated consciousness. Emphasis is placed on the concept of “bio-cybernetic continuity,” where identity persists despite augmentation. Ethical challenges such as autonomy, consent, inequality, and post-human governance are critically examined. This study is intended for interdisciplinary audiences interested in future-oriented biotechnology, including researchers, philosophers, policy analysts, and emerging technologists. While speculative in nature, the work is grounded in current trends and aims to provoke dialogue about the limits of human enhancement and the responsibilities that come with designing sentient systems.

Soil salinization is a major constraint on global agricultural development, particularly in arid regions such as Xinjiang, where it severely limits crop growth. Cyperus esculentus, a mildly salt-tolerant oilseed crop with both economic and ecological value, continues to face significant challenges in cultivation under highly saline soil conditions. Although previous studies have proposed biological approaches to mitigate salinity stress, their effects on the photosynthetic performance of C. esculentus have not been fully evaluated. To address this gap, this study examined two biological strategies: bio-amendments and intercropping with salt-tolerant plants to assess their impacts on soil physicochemical properties and the functional traits of C. esculentus in heavy salinized soils. The results demonstrated that microbial agents and humic acid directly improved the inter-root environment of C. esculentus by reducing soil pH and increasing the content of effective nitrogen and phosphorus, thereby promoting the synthesis of leaf chlorophyll a and leaf nitrogen accumulation. Intercropping with salt-tolerant plants improved the growth environment by absorbing excess soil salts and secreting organic acids and beneficial microorganisms, which enhanced the function of photosystem II and promoted photosynthetic electron transport. Additionally, nutrient uptake by C. esculentus was facilitated through competitive interactions with the root system of saline companion plants. Both bio-amendment and intercropping treatments significantly increased biomass accumulation. However, the alleviation of salinity stress occurred distinct mechanisms: bio-amendments maintained physiological homeostasis, while intercropping promoted a synergistic adjustment of morphological and photosynthetic traits. These findings provide valuable insights into the adaptation mechanisms of biological interventions under saline conditions and offer practical guidance for the successful cultivation of C. esculentus in the saline soils of Xinjiang.

Serious allergic reactions are increasing globally. Within this context, fatal anaphylaxis from hazelnut allergies is a critical public health concern. Hazelnuts, which are a common ingredient of many foods, contain many proteins that cause severe allergic reactions. Hazelnuts from all of the major commercial growing locations worldwide contained Spirosoma pollinicola sp proteins. This endotoxin-producing bacterium is linked to the allergenicity of hazelnut pollen. We were unable to remove the contamination by S. pollinicola proteins, showing that that this bacterium is a seed endosymbiont. Comparative proteomics revealed significant variations in the allergenic protein composition of nuts that correlated with patient immune responses. Hazelnuts from provenances 17 and 18 exhibited, lower levels of key antigens, particularly Cor a 9 and Cor a 14, highlighting their potential as candidates for genetic modification to mitigate allergenicity. Moreover, Spirosoma protein persistence may influence hazelnut allergenicity and the patient immune response.

Accurate prediction of fatigue crack growth life of gas turbine blades under out-of-phase thermo-mechanical fatigue loading is of significance for safeguarding its structural integrity. In this study, a finite element analysis framework, integrating ANSYS and FRANC3D for joint simulation, is proposed to tackle the issue of residual stress-driven crack propagation in the “hot spot” of the turbine blade. Initially, a sequential thermal-structural coupling analysis of crack-free blade is conducted in ANSYS to accurately quantifies residual stresses induced by creep relaxation during thermal cycling. Subsequently, semi-elliptical initial cracks with specific width-to-depth ratios are introduced in the regions of large residual stresses, and the crack propagation process is numerically simulated based on linear elastic fracture mechanics and the Paris model using FRANC3D. It is discovered that the width-to-depth ratio of initial crack significantly influences the fatigue crack growth prediction life, 23.86% reduction in lifetime at compared to . Moreover, a critical crack depth of approximately 12 mm is obtained when rapid unstable fracture occurs. The research provides a vital theoretical foundation and technical support for the fatigue life prediction and structural optimization of gas turbine blades, thereby contributing to the enhancement of the safety and reliability of gas turbine operations.

Austenitic stainless steel 316H is considered a promising structural material for lead-bismuth-cooled fast reactors (LFRs), owing to its superior high-temperature mechanical properties, creep resistance, and radiation tolerance. This study systematically investigates the creep-fatigue-oxidation (CFO) behavior of 316H stainless steel in oxygen-saturated lead-bismuth eutectic (LBE) at 550–600 °C, with an emphasis on the coupled influence of environmental exposure and holding time during cyclic loading. Results reveal that under short holding times (<300 s), the fatigue life in LBE is significantly degraded, with a reduction by a factor of 5 to 10 compared to that in air. This degradation is primarily attributed to premature crack initiation and accelerated propagation caused by unstable oxide films and the ingress of LBE. As the holding time increases (>300 s), the damage evolution transitions from transgranular to intergranular, accompanied by the formation of a dense and protective duplex oxide layer that effectively mitigates further degradation. Microstructural and compositional analyses confirm that the oxide layer acts as a diffusion barrier, retarding LBE penetration and contributing to fatigue life recovery. The results highlight the complex interactions between creep, fatigue, and oxidation, and offer insight into CFO mechanisms under realistic service conditions, thereby providing a basis for life assessment and material selection in LFRs systems.

This paper presents two fundamental principles that redefine the nature of reality: electromagnetic phenomena are two-dimensional and follow the Cauchy distribution; and there exists a non-integer variable dimensionality of spaces. Based on these principles, the study proposes a theoretical foundation for understanding massless electromagnetic fields and their interaction with matter. Four specific, cost-effective zones of verification and falsification are presented, all accessible with standard laboratory equipment: (1) a reverse slit experiment examining the shadow from a thin object; (2) optimization of single-mode optical fiber transmission; (3) enhancement of astronomical images through Cauchy kernel processing; and (4) modification of satellite communication systems and antenna designs. The central experimental question investigates whether light propagation follows the Cauchy distribution (compatible with exact two-dimensionality D=2.0 of massless electromagnetic fields) rather than the traditionally expected sinc² function. The proposed concept of variable dimensionality explains the nature of mass as a dimensional effect arising only when deviating from the critical point D=2.0, offers a new interpretation of the relationship $E=mc^2$, and reveals the deep meaning of time through information asymmetry and synchronization mechanisms. This framework resolves fundamental contradictions in modern physics and has revolutionary implications for quantum mechanics, relativity theory, and cosmology, potentially eliminating the need for concepts such as dark energy and inflationary cosmology. Further mathematical development demonstrates how the timeless Schrödinger equation emerges naturally as an optimization problem in Fourier space for systems with dimensionality D=2-$\epsilon$, providing a novel interpretation of quantum phenomena as projections between spaces of different dimensionality. A significant advancement in the paper is establishing a deep connection between the proposed principles and Roy Frieden's Extreme Physical Information (EPI) principle, showing how both approaches mutually reinforce each other. The paper demonstrates that at D=2, the Cauchy distribution emerges naturally as the informationally optimal distribution within EPI framework, while deviations from D=2 create precisely the dimensional-dependent Planck's constant previously discovered by Yang et al. This unification of information principles and dimensionality provides a comprehensive information-geometric framework for understanding physical reality. The work draws historical connections to the original ideas of Hendrik and Ludwig Lorentz, showing how these concepts, misinterpreted by subsequent generations, contained keys to understanding the fundamental structure of reality.

Introduction: This national study aimed to assess the incidence and respiratory morbidity in children with esophageal atresia (EA). Methods: We conducted a national population-based cohort study from 1998 to 2018 using the National Patient Registry to identify children with EA and calculated the annual incidence. Respiratory morbidity was evaluated through healthcare utilization and prescribed therapy. A case-control analysis linked to the Prescription Registry compared lung disease management in EA patients to age-matched children with asthma, and a healthy control group. Results: The incidence of EA remained stable at 2.5 cases per 10.000 births, with a 20-year mortality rate of 4%. Children with EA exhibited significantly higher antibiotic use, with an average of 8.5 prescriptions per year, compared to 2.8 in the asthma group and 2.3 in the healthy controls. Use of beta-2 agonists was similar between the EA and asthma group, with 2.6 and 2.4 prescriptions per year, respectively. Inhaled corticosteroid (ICS) use was also elevated in children with EA, averaging 2.8 prescriptions per year, approaching the 3.3 prescriptions per year observed in children with asthma. Children with EA also had significantly more healthcare contacts, which were not solely related to esophageal complications. Conclusion: Although the incidence of EA has remained stable, children with EA experience higher respiratory morbidity in early life compared to peers with asthma or those without chronic illness. This disparity diminishes with age, particularly during adolescence.

Introduction Respiratory Syncytial Virus (RSV) is the leading cause of lower respiratory tract infections (LRTIs) in children. In 2024, the monoclonal antibody nirsevimab became available in Italy for all newborns during their first RSV season. Aim To evaluate whether there were changes in the circulation of respiratory viruses among hospitalized children under five years of age with viral LRTI. Secondarily, whether the introduction of nirsevimab influenced the hospitalization rate. Methods A retrospective study was conducted, comparing two epidemic seasons: pre-nirsevimab (2023–2024) and post-nirsevimab (2024–2025).All children under five years of age hospitalized for viral LRTIs were included and divided in bronchiolitis and “other-LRTIs”. All hospitalized patients underwent nasopharyngeal swab testing using multiplex-PCR for respiratory viruses’ detection. Results A total of 278 patients were enrolled. RSV circulation decreased in the post-nirsevimab season, both in the bronchiolitis and LRTI groups, although it remained the main cause of infections. In the post-nirsevimab season, detections of influenza virus and bocavirus increased in the bronchiolitis cohort (p-values 0.02 and 0.01), while human metapneumovirus and coronaviruses were more frequently identified in children with LRTIs (p-values 0.08 and 0.03). Regarding infants with bronchiolitis, we showed a 59% reduction in hospitalizations rate (both in paediatric ward and paediatric intensive care) ( p-value < 0.001). Children hospitalized for bronchiolitis were older than the previous season (p < 0.001). No differences were observed in the hospitalization rate among infants with viral LRTI. Conclusions Following nirsevimab introduction, circulation of non-RSV respiratory viruses increased, while hospitalizations and ICU admissions for bronchiolitis significantly decreased.

The ubiquitous tick, the relentless flow, the arrow's unwavering trajectory-for eons, humanity has wrestled with the enigma of time, often perceiving it as an immutable, fundamental constant woven into the very fabric of existence. Yet, this paper posits a radical departure from such entrenched dogma. Time, in its profoundest essence, is not a bedrock of reality, a primeval given. Instead, it is unveiled as an emergent phenomenon, a magnificent orchestration born from the intricate dance of layered recursion. This is not a mere process; it is the structural genesis, ceaselessly generating the very sensation and experience of temporality across the boundless spectrum of physical and biological scales, from the subatomic tremor to the cosmic pulse. This theoretical framework proposes a revolutionary model: time as the self-organizing tempo of nested cycles. Imagine the universe not as marching through a pre-ordained temporal dimension, but rather as a symphony of interconnected rhythms, each cycle nested within another, creating a dynamic, evolving cadence. This perspective offers a unifying interpretation, a singular lens through which to perceive the temporal manifestations within the disparate realms of theoretical physics, grand cosmology, and introspective philosophy. From the silent voids of the cosmos, pregnant with unformed potential, to the luminous filaments that thread galaxies, from the ephemeral shudder of an atom to the majestic, enduring sweep of planetary orbits-time, in this grand narrative, is not the elusive stream that passes us by. No, in a revelation both simple and profound, time is not what dissipates into the past; time is what recurs. It is the perpetual echo, the ceaseless return, the unfolding iteration of existence itself.

Monkeypox, transmitted primarily through close contact and zoonotic spillover, poses significant public health concerns and economic burdens in affected regions. In order to explore the transmission mechanism of this disease, we construct a dynamic transmission model across risk groups, and simulated different control measures in high-risk (MSM) and low-risk populations. The existence and stability of disease-free and endemic equilibria of the system are analyzed, which are totally determined by the basic reproduction number. Using the MCMC algorithm, we fit the model to mpox case data from the US, Germany, Spain, and the UK. The results indicate that the UK exhibits the highest transmission rate, while the US demonstrates the lowest. Spain and Germany show higher modification parameters for low-risk populations, contrasting with the UK’s minimal value. These model outputs align closely with observed national mpox prevalence rates. Numerical simulations reveal that enhancing awareness among low-risk populations and reducing the modification parameter for individuals with low-risk forces of infection should be prioritized through intervention strategies. Implementing control measures aimed at high-risk groups (MSM), is also crucial in reducing overall infection rates.

Four-dimensional (4D) printing, an evolution of additive manufacturing (AM), integrates stimuli-responsive materials like thermal-induced shape memory polymers (TSMPs) to enable programmable, time-dependent transformations in structures. This review systematically examines recent advancements in TSMPs, 4D printing technologies, and fabrication strategies, emphasizing their interdisciplinary convergence and applications. TSMPs, with their unique phase-separated microstructures, modulus disparity, and tailorable recovery behaviors, form the foundation of 4D-printed systems, enabling innovations in aerospace, healthcare, and soft robotics [1–3, 33–45]. Key printing methods—including fused deposition modeling (FDM), direct ink writing (DIW), PolyJet, stereolithography (SLA), and digital light processing (DLP)—are analyzed for their strengths and limitations. FDM dominates due to cost-effectiveness but faces challenges in resolution and anisotropy [88, 91–93], while SLA and DLP offer high precision and speed but require material optimization [105, 111–115]. Advanced fabrication strategies, such as localized TSMP printing, composite reinforcement with carbon nanotubes or Fe 3O 4 particles, and sacrificial mold templating, expand design possibilities for multi-functional and multi-scale structures [117–120, 140–144]. Despite progress, challenges persist, including environmental sensitivity of TSMPs, interlayer bonding in AM, and dynamic modeling of non-equilibrium thermal responses [74, 77, 146]. Future directions focus on multi-responsive materials, machine learning-driven constitutive models, and sustainable bio-based formulations to address scalability and cyclic durability [31, 77, 147–149]. By bridging material science, computational modeling, and advanced manufacturing, this work provides a roadmap for harnessing 4D-printed TSMPs in real-world applications, from self-deploying biomedical devices to adaptive aerospace systems [28, 85, 137].

The Stochastic Configuration Network (SCN) is a universal approximator that stochastically configures the input weights and biases of hidden nodes under a supervised mechanism. This paper extends the original SCN to improve the learning efficiency by optimizing the configuration of hidden node parameters and expanding the training dataset with unlabeled data. Firstly, Randomly configuring hidden nodes parameters introduces uncertainty and does not achieve optimal values. To address this limitation, this paper introduces an improved Pelican Optimization Algorithm (IPOA) to enhance its global optimization capability, which is then applied to optimize the hidden nodes configuration. This improvement boosts network learning efficiency and results in a more lightweight structure. To address the challenge of limited labeled data for fully supervised SCN models, a semi-supervised learning approach is employed, using a small amount of labeled data to classify unlabeled data. Finally, the improved SCN (ISCN) algorithm is applied to a real-world industrial process for predicting the setpoint of coal mill outlet temperature in power system. Simulation results and real-world power plant applications demonstrate that the ISCN achieves faster convergence and improved generalization ability compared to the original SCN.

Implementing solutions to change the climate requires-PADDING innovative approaches to address the increasing "adaptation deficit gap." The existing evidence of their effectiveness, innovation types, scalability, and equity implications remains fragmented. The study uses Metaanalysis to synthesize empirical literature globally through 418 peer-reviewed studies using PRISMA 2020 protocols published from 2010 to 2023. The three objectives are: first, measuring comparative effectiveness of technological, institutional, behavioral, and ecosystem-based adaptation innovation; second, identifying contextual moderators of success; third, evaluating equity outcomes using the PROGRESS-Plus framework. The findings suggest hybrid approaches with institutional and behavioral components rely on other actors and yield higher resilience returns (Hedge's g = 1.24, 95% CI [1.07-1.41]). Outperforming technological solutions by 39% (p<0.001). Additionally, ecosystem-based approaches figure as the most cost-effective ($127 per resilience unit compared to $412 for technological interventions). Nonetheless, these approaches remain critically underfunded. Success of innovations hinges on contextual barriers to successinstitutional innovations do not succeed below $2500 GDP per capita (OR=0.24), equitable outcomes if more than 40 percent of the decision-making women and integrate indigenous knowledge (β = 0.52, p = 0.003). The research also indicates that 73% of technological implementations suffer from elite capture and 22% are at risk of maladaptation due to lacking socio-ecological feedback considerations. These findings emphasize the acute need to shift adaptation finance and governance toward polycentric, justice-based frameworks. In this regard, the study suggests three actionable pathways: Creating Innovation Broker Authorities aimed at policy-silo busting; enforcing equity-weighted financing that give the greatest priority to pre-codesigned hybrid innovations; and adaptation dashboards that monitor achieve PROGRESS-Plus equity threshold levels-shifting to strengthening evidentiary bases for transforming adaptation innovation from incremental modifications into changes that build systemic resilience.

E-mail: ramos.hernandez.lr@bine.mx

In colorectal cancer (CRC) precursor lesions can be missed during screening due to ambiguity, limited depth sensitivity, or obscured by colonic folds. Optical coherence tomography (OCT) with automated detection may enhance accuracy. OCT imaging was performed on polyps and polyp fragments (300 patients). En face projections were then annotated. In processing, depth was then encoded in color to generate en face OCT projections. The projections were used to train an ensemble network based on malignant potential. The area under the curve (AUC) for the detection of malignant potential of all polyps was 0.90, for diminutive (<5 mm) the AUC was 0.88. Indicating a high degree of accuracy for classification of malignant potential ex vivo. Should results hold in vivo, this algorithm would meet the ASGE’s NPV PIVI criteria, which could allow clinical utilization of OCT for lower colon ‘diagnose and leave’ and/or ‘resect and discard’ strategies for diminutive colon polyps.