Abstract: We develop the strip-analytic sequel to the master-integral-transform program with entire kernels by replacing the discrete Taylor-spectrum model with a continuous spectral model on the dilation side. The central object is a Hardy-strip orbit kernel whose boundary representation induces a continuous dilation-convolution operator acting on the Fourier transform of a weighted signal. In this setting, the Abu-Ghuwaleh transform admits two complementary inversion mechanisms: Mellin contour inversion and contour-free Wiener--Mellin inversion. We prove exact factorization formulas on named weighted function spaces, derive branchwise Mellin diagonalization formulas, obtain inversion theorems under nonvanishing assumptions on the continuous symbol, and show that logarithmic coordinates convert the transform into an additive convolution equation. This yields a practical FFT-based inversion framework together with a stability bound on frequency windows away from zeros of the multiplier. We also prove an explicit injectivity-and-stability proposition for a resolvent-type kernel family with Gamma-type symbol. The paper is designed as the natural continuous-spectrum successor to the entire-kernel and finite-Laurent stages of the program.

Abstract: We present a geometric model in which each particle is associated with its own private spacetime manifold—a world-block—constructed from Fermi–Walker coordinates. The intrinsic spatial metric on each proper-time slice is treated as a dynamical field with a universal stiffness constant. This single assumption leads to a consistent model where self-gravity is repulsive and mutual gravity is attractive and exactly Newtonian. Newton’s constant emerges from the fundamental stiffness. The model provides a geometric derivation of the inverse-square law and suggests a connection to cosmology: the constant part of the strain field on large scales can be interpreted as a cosmological constant whose magnitude is set by the Hubble radius.

Abstract: Inclusive communication remains a critical challenge for individuals with hearing impairments, speech disorders, or multilingual barriers, particularly in educational and urban settings. This paper proposes a multimodal LLM framework that transforms auditory inputs such as noisy speech, accents, or sign language into coherent speech synthesis and written outputs, enabling seamless accessibility. Leveraging transformer-conformer architectures, our system fuses audio spectrograms, lip-reading visuals, and textual context via cross-modal attention mechanisms, achieving superior performance in real-time transcription (WER < 5% on diverse datasets) and voice cloning tailored to user prosody. Key innovations include adaptive noise suppression for hearing aid integration, ethical personalization to preserve speaker identity, and deployment on edge devices for low-latency applications like VR classrooms. Evaluations on benchmarks (e.g., LibriSpeech, VoxCeleb) and user trials with 50 participants (including seniors and hard-of-hearing students) demonstrate 30% improvements in comprehension accuracy and user satisfaction over baselines like Whisper and GPT-4V. By bridging auditory-to-text/speech gaps, this framework advances AI pedagogies for immersive learning, promotes equity in communication, and sets foundations for scalable IoT-enhanced inclusive tools. Future directions explore federated learning for privacy-preserving multilingual expansions.

Abstract: The incidence of furunculosis in juvenile Atlantic salmon, Salmo salar, has increased in recent years in Chile, with isolates of Aeromonas salmonicida being the primary cause. However, in some cases, molecular diagnostics failed to identify the etiological agent. We previously demonstrated that a proportion of undiagnosed cases was produced by a new A. salmonicida strain. In those cases where the pathogen remained unidentified, we isolated colonies with an A. salmonicida-like appearance. Subsequent phylogenetic analysis presented in this work grouped those A. salmonicida-like isolates within the Aeromonas piscicola clade. Whole genome sequencing confirmed the taxonomic affiliation, giving additional insights into virulence and antibiotic resistance markers. Indeed, one of the strains showed reduced susceptibility to oxytetracycline. Virulence potential was assessed by in vivo testing on S. salar, which resulted in disease with pathognomonic signs of furunculosis. Although the pathogen presents common antigens with A. salmonicida, the current vaccine triggered only a modest IgM response against A. piscicola in the field. Our results support the hypothesis that the incidence of furunculosis in Chile cannot be ascribed to the emergence of the new A. salmonicida strain, but may partially result from infections caused by A. piscicola strains which exhibit a comparable virulence level.

Abstract: Hybrid rocket technologies are gaining recognition as eco-friendly alternatives to traditional propulsion systems. Utah State University's Propulsion Research Laboratory has developed a High-Performance Green Hybrid Propulsion (HPGHP) technology, leveraging 3D-printed ABS fuel for reliable, low-energy ignition. Among tested materials, only ABS shows suitable electrical-breakdown properties for arc ignition. Unfortunately, due to the proprietary formulations in commercial ABS blends, and its limited use as a rocket-propellant, related composition and combustion data are limited. This study uses spectroscopic evaluation and bomb calorimetry to estimate material compositions, enthalpies of formation, and combustion energies for multiple commercially available 3-D print feed stock ABS types, finding minimal differences amongst the samples tested. Based on these test results, “representative” ABS properties including chemical formula, mean molecular weight, enthalpy of formation, and Higher Heating Value, is recommended. Follow-on tests with 5 alternative, commonly used, 3D-printable thermoplastic feed stocks demonstrate that ABS has significantly higher energy content. This result supports ABS’s advantages and utility as a conveniently fabricated hybrid rocket fuel.

Abstract: Spatial data quality (SDQ) is commonly assessed through technical verification. However, empirical evidence demonstrates that perceived data quality often diverges from objectively measured quality due to cognitive, institutional, and lifecycle-related factors. This paper proposes a multi-layered SDQ framework that integrates technical admissibility, process and lifecycle stewardship, visual and interpretive diagnostics, and governance indicators to enable holistic quality assessment within a socio-technical system. Rather than treating quality elements in isolation, the framework supports the diagnosis of emergent quality states and associated risk patterns. The framework is demonstrated through two empirical cases: validation of planned land use data using the OPIAvalid toolkit, and semantic conflation of multiple digital elevation models (DEMs) with heterogeneous lineage. Results show that governance failures, specification misuse, and degradation of lineage can undermine trust and decision-making even when datasets formally comply with ISO-based indicators. Visual spatial forensics and lineage-aware integration proved essential for detecting undocumented methodological shortcuts and restoring justified trust in authoritative data. Artificial intelligence is positioned as a diagnostic and explanatory support, assisting in anomaly detection, prioritization, and communication of quality risks, while deterministic validation and expert judgment remain mandatory. Overall, the framework shifts SDQ management from isolated technical validation toward lifecycle-oriented, transparent, and sustainable data governance.

Abstract: We present a mathematically rigorous formulation of the Fundamental Speed Theory (FST), a vector-tensor theory of gravity featuring a dimensionless vector field

Abstract: The Hodgkin-Huxley (HH) model has dominated quantitative neuroscience since 1952. Its authors explicitly acknowledged its phenomenological character and called for a deeper mechanistic account. We propose that this account is the IMH model of nerve conduction. The model rests on three biophysical foundations: (1) the polyelectrolyte gel framework of Ling, in which intracellular K⁺ is adsorbed on protein sites and the resting ionic distribution is a thermodynamically stable Donnan equilibrium requiring no metabolic pump [6,7]; (2) the Hofmeister ion series, which governs differential adsorption of K⁺ versus Na⁺ [8]; and (3) the hydraulic wave equation for a fluid-filled elastic tube, which predicts conduction velocity from myelin elastic modulus rather than sodium channel density. In this framework, the action potential is a coupled ionic-hydraulic phase transition propagating as a pressure wave in the periaxonal space. Electrical events are causally secondary—the electromagnetic shadow of the hydraulic wave, not its cause. We demonstrate that the model resolves a 75-year-old anomaly identified but left unexplained by Huxley and Stämpfli in 1949 [10]: positive current enters a node before the membrane potential reaches its maximum, a relation the authors themselves described as “impossible in a system of resistances and capacities.” We present eight falsifiable predictions distinguishing the IMH model from HH, covering myelin mechanics, mechanoreceptor adaptation, terminal arborisation geometry as the physical substrate of the Umwelt, motor tremor as hydraulic interference, and the temporal basis of conscious perception.

Abstract: The accuracy of financing demand prediction has a direct impact on the return on investment and risk exposure in fintech investment and asset allocation. Nevertheless, the real world financial transaction data often displays significant nonstationary features — for example, cyclical fluctuations, event shocks, and short-term anomalies — which make the traditional forecasting approach unstable in the real investment scenarios. This study builds a data set that includes 34 reproducible variables — including daily financing requirements, transaction peaks, capital occupation duration, and risk exposure levels — on the basis of 180 consecutive days of investment and operating data from a leading financial services firm. It systematically compares ARIMA, Prophet, Random Forest, and XGBoost models for financing demand forecasting. Empirical results show that XGBoost maintains a low forecast error (MAPE of 8.2%) in the case of market fluctuations and unusual events, which reduces the average error by about 22% in comparison with the baseline model. Based on these results, a model is built to analyze the effect of forecast errors on the stability of investment returns and the efficiency of capital turnover. Results show that keeping the forecast error under 10% significantly reduces the risk of capital misallocation in times of high volatility, while at the same time improving the stability of overall investment returns. This study provides a reusable model workflow and engineering reference for the establishment of the investment allocation and risk management system of the financial institutions.

Abstract: Contemporarybiocomputingoftenapproachesbrainorganoidsasallopoieticsub-strates for logical processing, neglecting the existential imperatives that drive biolog-ical cognition. This paper proposes a fundamental paradigm shift from AllopoieticComputing toward Autopoietic Computing, grounding the emergence of sentiencein the thermodynamic necessity of survival. By integrating the Mortal Computingparadigm, where computational software is physically indissociable from its degrad-able biological hardware, with the causal hierarchy of consciousness proposed byBennett et al., we investigate the theoretical and computational feasibility of sen-tience as a recursive strategy for energy optimization. We developed and analyzeda high fidelity digital twin of an Autopoietic Chamber using the Brian2 simulator,implementing a virtual metabolism where neural activity directly regulates nutrientaccess. Our simulation results demonstrate a clear progression from the entropiccollapse of reactive matter, Stage 0, to the stabilization of phenomenal, Stage 1, so-cial, Stage 2, and narrative, Stage 3, functional identities. These findings provide apredictive proof of concept indicating that each higher order of consciousness acts asa thermodynamic filter, minimizing metabolic dissipation through increasingly com-plex causal modeling. We argue that sentience is not a byproduct of complexity buta necessary compromise with thermodynamic economy, providing a new empiricaland computational roadmap for the science of consciousness and the developmentof mortal, sentient artificial agents.

Abstract: We introduce a Resonance--Particle Classification Framework (RPCF) that attempts to bring some order to the correspondence between the vibrational modes of strings and the particle content of the Standard Model. Building upon earlier work connecting hypercomplex manifold geometry with particle genesis via chiral permutation cycles and upon a detailed study of Calabi--Yau compactifications with Euler number $\chi = \pm 6$ that reproduces three net chiral generations, the present manuscript develops a unified classification in which closed-string, open-string, and Ramond--sector modes are mapped, respectively, to the gravitational sector, gauge bosons, and fermionic matter of the Standard Model. We introduce a hierarchical labelling scheme based on mode number, boundary condition, and symmetry representation, and we show how Calabi--Yau topology constrains the degeneracy of these resonances to yield exactly three particle families. The Atiyah--Singer index theorem and its cohomological refinements are used to quantify generation multiplicity, while the Standard Model gauge group $\SU(3)\times\SU(2)\times\mathrm{U}(1)$ is recovered from appropriate bundle holonomy choices on the compactification manifold. We further discuss composite resonance interference as a pathway toward an effective description of hadronic states. It must be stressed at the outset that this work is a conceptual proposal, not a completed derivation. Exact vibration--particle correspondences are not established here; they remain a genuine open problem. The analysis is intended to illuminate structural patterns and suggest productive research directions, not to assert a confirmed physical identification.

Abstract: Although chimeric antigen receptor T-cell therapy (CAR-T) has shown substantial efficacy in haematological malignancies, its application to solid tumours remains limited by antigenic heterogeneity, poor effector-cell infiltration, and an immunosuppressive tumour microenvironment. This study aimed to develop a mathematical model of the spatiotemporal dynamics of a solid tumour under CAR-T cell therapy, incorporating the main determinants of therapeutic resistance. We propose a reaction–diffusion model formulated as a system of partial differential equations describing functional and exhausted CAR-T cells, antigen-positive and antigen-negative tumour subpopulations, and chemokine, immunosuppressive, and hypoxic fields. The model was analysed using steady-state analysis and numerical simulations based on a finite-difference scheme. The simulations showed that therapeutic outcome is governed by the combined effects of CAR-T cell infiltration, functional exhaustion, and tumour antigen escape. The model reproduced partial tumour regression followed by persistence of a residual tumour population, the emergence of an antigen-negative component under therapeutic pressure, and reduced treatment efficacy under more strongly immunosuppressive and hypoxic microenvironmental conditions. Repeated simulated CAR-T-cell administration improved tumour control, albeit with diminishing returns. Overall, the proposed model provides a useful framework for analysing resistance mechanisms and optimising CAR-T cell therapy protocols for solid tumours.

Abstract: Linear measurements are used on radiographs for various purposes, such as measuring lengths in endodontics, analysing bone loss in perio-dontal disease and making age determinations in forensic dentistry. The purpose of this study was to analyse the accuracy of periapical radio-graphs for the measurement of the contact point to the crest of the bone compared to the actual measurements of a dried skull. A dried skull had lead squares measuring 1 x 1mm attached to the contact point and the bone crest. Each site was radiographed using a parallel technique with a Rinn holder. The radiographs were taken perpendicularly to the tooth and repeated at 10° and 20° horizontal angulations. The results showed that variation in the angle of the radiograph had a significant effect on the resulting measurements, F (1.7, 26.9) = 218.265, p < 0.001. The results from this study indicate that when measuring the contact point to the crest of the bone, a shift of 20° from the perpendicular of the tooth has a significant effect on the radiograph measurement and the actual meas-urement of the contact point to the crest of the bone on the actual skull.

Abstract:

Nova Scotia, a province on Canada’s Atlantic coast, has proposed Wind West, a plan to initiate the province’s offshore wind industry. A regional offshore wind report identified eight potential development areas (PDAs), of which four were chosen. The areas were selected to avoid ecologically significant and conflict-of-use areas; however, no consideration was given to tropical cyclones (TCs) and hurricanes (intense tropical cyclones). This paper evaluates the effects of climate change and TCs on offshore wind turbines sighted on Nova Scotia’s continental shelf by analysing historical TC track data to assess the intensity and frequency of extreme wind and wave events on the continental shelf. Correlations between SSTs and extreme weather events were also examined. The findings show no clear long-term trends in TC intensity or frequency in the selected areas, although there is a clear upward trend in sea-surface temperatures (SSTs) since 1950. No strong correlation between rising SSTs and increased storm intensity or frequency within the available datasets were found, though similar studies suggest that these variables have some correlation on aggregate. While climate change is causing conditions for hurricanes to become favorable along the Scotian Shelf, current TC data shows no clear correlation with increasing intensity and frequency over time. The results are affected by the quality of the data. High uncertainty, spatial resolution, and temporal resolution leave large portions of TC tracks unmeasured. Uncertainty associated with pre- and post-1950 data makes conclusions from the results difficult. We propose a measuring buoy in each of the four selected potential development areas cost C$200,000 to develop and C$35,000 to maintain. Each buoy would have a representative radius of 50km, slightly larger than that of each of the four wind energy zones. The additional data collected would allow developers to pick appropriate design standards based on available environmental data and could additionally be used for climate change research. Currently, Nova Scotia faces many limitations developing its offshore; supplying accurate data to assess the risk from extreme weather events to offshore wind turbines is one of the first steps to ensuring success.

Abstract: This study examines the dynamics of sustainability transitions in the EU-27 during the period 2015-2024, focusing on the role of different stakeholders and the emergence of distinct convergence patterns in sustainability performance. The theoretical framework integrates sustainability transition theory, stakeholder governance, and the literature on convergence and club convergence, interpreted through the socio-technical multi-level perspective and the concept of institutional lock-in. A test model is developed based on four stakeholder-specific indices: the Government Sustainability Index (GSI), Environmental Sustainability Index (ESI), Population Sustainability Index (PSI), and Business Sustainability Index (BSI), complemented by a Composite Sustainability Index (CSI). The indices are constructed using min–max normalization of harmonized data from Eurostat, the European Environment Agency, and the Sustainable Development Report. The empirical analysis combines K-means clustering, compound annual growth rate (CAGR) calculations, and correlation analysis, complemented by a robustness module testing alternative weighting schemes, z-score normalization, and ±10% variations in index components. The results reveal four relatively stable sustainability tiers among EU member states, an S-curve-type relationship between initial sustainability tiers and subsequent growth, and a consistent hierarchy in stakeholder response speeds (ESI &gt; GSI &gt; PSI). A clear structural slowdown after 2019 is also observed. The main findings remain robust across alternative methodological specifications. The study contributes to the quantitative integration of the multi-level perspective on sustainability transitions into a stakeholder-based composite index framework for cross-country analysis within the European Union.

Abstract:

Objective: Bevacizumab (BEV) and Olaparib (OLA) have demonstrated clinical efficacy as maintenance therapies for first platinum-sensitive recurrent ovarian cancer. However, direct comparisons between these agents independent of homologous recombination deficiency (HRD) and BRCA status, remain limited and the clinical validity of OLA dose reduction has not yet been confirmed. This study aimed to compare the efficacy and safety of BEV, standard-dose OLA, and dose-reduced OLA as maintenance therapy and to evaluate the clinical utility of OLA dose reduction. Methods: This retrospective multicenter study included 101 patients with first platinum-sensitive recurrent ovarian, fallopian tube, or primary peritoneal cancer who received maintenance therapy after achieving a response to chemotherapy. Patients were classified into three groups: BEV (n = 34), standard-dose OLA (n = 31), and dose-reduced OLA (n = 36). The primary endpoint was progression-free survival (PFS), and secondary endpoints included overall survival (OS) and adverse events. Survival outcomes were evaluated using Kaplan–Meier analysis and Cox proportional hazards models. Results: Median PFS was 16 months in the BEV group, 16 months in the standard-dose OLA group, and 24 months in the dose-reduced OLA group, with significantly longer PFS in the dose-reduced OLA group (p < 0.001). In the multivariate Cox analysis, treatment remained an independent prognostic factor for PFS (HR 0.67, 95% CI 0.46–0.96, p = 0.030). Median OS was 44, 45, and 64 months, respectively, with no significant differences among groups; PFI ≥12 months was the only independent prognostic factor for OS. Grade ≥3 hematologic toxicities were more frequent in the OLA groups but were manageable. Conclusions: Dose-reduced OLA was associated with prolonged PFS while maintaining manageable toxicity, supporting its clinical validity as a maintenance option independent of HRD and BRCA status.

Abstract: This study examines whether international food price dynamics provide a reliable signal of undernourishment and human development outcomes relevant to the attainment of SDG 2 (Zero Hunger) by 2030. We apply wavelet coherence analysis to the FAO Food Price Index and the prevalence of undernourishment (SDG Indicator 2.1.1) over 2001–2023, testing statistical significance against an AR(1) red-noise null hypothesis. Hybrid ARIMA–Random Forest models generate probabilistic price forecasts through 2030. Despite strong raw coherence (R² ≈ 0.77), only 7.8% of time–frequency cells achieve statistical significance, indicating that apparent co-movement largely reflects autocorrelation rather than substantive dependence. Where significant coherence emerges, it concentrates at medium-run horizons (3–6 years), consistent with undernourishment as a habitual dietary adequacy measure linked to sustained affordability pressures affecting health, productivity, and human capital formation. Rolling correlation analysis reveals a regime shift around 2012—from negative to positive correlation—coinciding with a slowdown in progress toward reducing hunger. Price forecasts exhibit rapidly widening confidence intervals (by ±131 index points by 2030), underscoring fundamental limits to predictability. These findings caution against mechanistic inferences from global price indices to hunger and human development outcomes, redirecting policy emphasis toward domestic transmission channels and nutrition-sensitive safety nets.

Abstract: The origin of life on prebiotic Earth is one of science’s greatest mysteries. Traditional approaches to the search for answers often rely on isolated universe models that fail to account for the open, far-from-equilibrium conditions of natural systems. Such limitations might be hindering progress in understanding the thermodynamic processes that drive the emergence of life. This theoretical study presents the second installment in a series exploring a thermodynamic theory of heat transformation and its role in the development of prebiotic Earth. Building on the foundational concepts introduced in Part I, this work focuses on the dissipation of heat through chemical systems, examining chemical dissipative structures (CDSs) and their ability to store and release energy through endothermic and exothermic reactions. By modeling CDSs as heat engines, the paper investigates the interplay between entropy, order, and complexity, revealing how energy storage and transformation drive the generation of complexity. The analysis extends to the networking of gravitational dissipative structures (GDSs) covered in Part I and CDSs, demonstrating how these networks facilitate the transfer of stored energy and contribute to the development and growth of prebiotic chemosystems. The findings suggest that the dominance of endothermic synthesis reactions in CDSs plays a critical role in the generation of complexity, resilience, and mutualism, ultimately shaping the conditions for the emergence of life. This work provides a novel perspective on the thermodynamic underpinnings of prebiotic evolution, offering insights into the relationship between energy, information, and the development of complex systems.

Abstract: Rheumatoid arthritis (RA) is traditionally diagnosed once clinical joint swelling becomes apparent. However, many patients report non-localized stiffness in very early stage then preceding overt synovitis. The transitional processes linking systemic autoimmunity to localized joint inflammation remain incompletely conceptualized. This study proposed a conceptual stage-dependent transition model distinguishing a reversible inflammatory phase from a structurally consolidated phase. Tenosynovitis and joint ultrasound gray scale (GS)-negative/Power Doppler (PD)-positive synovitis were conceptualized as reversible states, whereas GS synovial hypertrophy was hypothesized to represent local immune consolidation. In this framework, “threshold” denoted a conceptual transition point rather than a fixed numerical value, at which gradual inflammatory amplification results in qualitative transition from reversible immune activation to structurally stabilized inflammation (Figure 1). A minimal dynamic representation was introduced to illustrate the theoretical plausibility of threshold-like behavior (Figure 2). Based on this model, we proposed a conceptual algorithm for ultra-early, time-limited intervention prior to structural consolidation (Figure 3). This study was hypothesis-generating and aims to provide a theoretical basis for reconsidering intervention timing in RA.

Abstract: The Cosmic Microwave Background Radiation (CMBR) harbours a cold spot in the southern celestial hemisphere — the so-called Eridanus Supervoid — whose anomalous temperature depression of ∼ 70 μK and spatial extent of roughly 300 Mpc at redshift z ≈ 1 resist explanation within a purely Gaussian, single-universe framework. In this work we develop a self-consistent theoretical programme that interprets this cold spot as a relic imprint of a conjugate parallel universe that shared a common inflationary epoch with our own before separating under a spontaneous symmetry-breaking transition. Our formalism is built upon three interlocking pillars. First, we introduce a two-dimensional imaginary time topology in which the temporal coordinate is promoted from a one-dimensional real line R¹ to a pair of complex curves C¹ and C² embedded in the R³ manifold. The two curves carry opposite orientation angles of ±2πi, yielding an affine parameter of π for the coupled system. Second, we derive the entanglement entropy of the universe pair by treating each universe as a quantum object with an imaginary-time Ket vector; the Von Neumann entropy of the resulting density matrix links macroscopic cosmological observables to quantum information-theoretic quantities. Third, we embed the birth and separation of the twin universes within Perelman’s Ricci-flow surgery framework, identifying the blow-up of a curvature singularity as the topological mechanism responsible for the universal split. In addition, the paper addresses the holomorphic structure of pre- and post-Big Bang time, the non-Gaussian cosmic-texture signatures of the cold spot, a simulation-based glitch matrix, Jacobi-field analysis of the junction conditions, and the phenomenological implications for the Mandela effect, déjà vu, and related confabulation phenomena. The paper concludes with a probabilistic treatment of conjugate-universe counting within a landscape of 10⁵⁰⁰ vacua and a omprehensive statistical analysis supporting the twin-universe conjecture.