Abstract: Carbon losses from decomposition and erosion threaten intensive crop production systems. While conservation tillage enhances soil organic carbon (SOC), soil tex-ture-dependent responses and time-scales of soil quality change remain poorly understood. We addressed this gap using a dual time-scale design: 11 years of minimum tillage (MT) versus conventional ploughing (CT), followed by 5-year transitions to no-till (NT) in contrasting textures (loamy vs. silty clay) in NE Slovenia. In loamy soils, reduced tillage significantly increased SOC, dissolved organic carbon (DOC), permanganate oxidizable carbon (POX-C), particulate organic carbon (POC), and mineral-associated organic carbon (MAOC < 50 μm) in the 0-10 cm layer. In silty clay soils, high clay content provided baseline protection that masked tillage effects on bulk SOC, though POX-C and POC showed vertical stratification. MAOC in the fine fraction (< 20 μm) remained consistent (2.0-2.5%) across treatments and textures, except under CT in loamy soil (1.73%), indicating accelerated decomposition. Tillage intensity drove aggregate distribution: CT fragmented soil structure (fewer macroaggregates, higher Dm), while MT and NT promoted macroaggregate formation. Structural indices (MWD, GMD, Dm) correlated strongly with C fractions, confirming physical protection mechanisms. Our dual time-scale approach reveals labile C pools and aggregate recovery respond within 5 years of NT, while texture modulates response magnitude and detectability. Reducing tillage intensity consistently supports C preservation across textures, though lighter soils show faster, more pronounced responses.

Abstract: The Michelson–Morley experiment yielded a null result, indicating equal light travel times in the longitudinal and transverse arms of an interferometer, traditionally interpreted as evidence against a light-propagating medium. This paper re-examines this conclusion by postulating that space itself possesses elastic properties and constitutes the fundamental medium. Beginning with this premise and modeling matter as standing waves within this space-medium, we first demonstrate that the complete mathematical framework of Special Relativity—including Lorentz transformations, time dilation, and mass-energy equivalence—emerges naturally from the Doppler deformation of these wave patterns under motion. We then extend this wave-mechanical approach to gravity, showing that the Newtonian potential and inverse-square law can be interpreted as the gradient of a spatial deformation field, with gravitational interaction energy arising from the overlap of these deformations. We show that Special and General Relativity emerge as effective geometric descriptions of an underlying elastic dynamics of space, in which relativistic effects correspond to physical deformations of wave-based matter. This framework preserves all empirical predictions of relativity while providing a unified mechanical interpretation of inertia, gravitation, Equivalence Principle, and spacetime curvature.

Abstract: We present a rigorous derivation of two fundamental physical scales: the primal energy E0 = 2.916601 × 10^{-16} J = 1820.469 eV and the primal length l0 = lP = 1.616255 × 10^{-35} m (the Planck length). These quantities emerge uniquely from the arithmetic-geometric structure encoded in the zeros of the Riemann zeta function ζ(s). We demonstrate that E0 serves as the natural energy unit connecting quantum mechanics, gravitational physics, and number theory, while l0 establishes the fundamental length scale of spacetime geometry. The derivation employs: (1) the exact conformal transformation Φ(z) = α arcsinh(βz) + γ with αβγ = 2π connecting quantum spectra to zeta zeros; (2) combinatorial relations among the first four nontrivial zeros γ1, γ2, γ3, γ4; and (3) consistency conditions with established physical constants (CODATA 2018). The resulting framework provides a unified basis for understanding fundamental constants, predicts testable modifications to quantum and gravitational phenomena, and offers new insights into the geometric structure of reality at the Planck scale.

Abstract: Background: Bipolar disorder (BD) exhibits high heritability and substantial genetic overlap with schizophrenia and major depressive disorder (MDD), yet its core pathophysiological pathways remain debated. While glutamatergic dysregulation and synaptic plasticity have been emphasized, emerging evidence from schizophrenia highlights excessive synaptic pruning. We conducted a multi-method genetic analysis to competitively test pruning versus glutamatergic/plasticity hypotheses in the latest European-ancestry BD GWAS, with parallel replication in MDD for cross-disorder comparison.Methods: Using summary statistics from a large BD GWAS (effective N ≈ 137,097) and a trans-ancestry MDD GWAS (European subsample effective N ≈ 829,250), we applied: (1) MAGMA for gene-based and competitive gene-set testing with custom pruning (shortened/expanded/specific) and glutamatergic sets (original/expanded) plus controls; (2) stratified LD score regression for partitioned heritability enrichment; (3) S-PrediXcan transcriptome-wide association in six brain tissues; and (4) two-sample Mendelian randomization with neuroplasticity proxies (e.g., educational attainment). Overlap removal enabled independence assessment; directional TWAS and MR provided functional/causal insights.Results: In BD, pruning pathways dominated across methods: expanded/specific pruning sets were Bonferroni-significant in MAGMA (p = 1.14 × 10⁻⁴/7.00 × 10⁻⁴) and showed strong LDSC enrichment (p = 4.16 × 10⁻³⁸/3.77 × 10⁻¹²), persisting independently of glutamatergic overlap. TWAS revealed activation-skewed pruning (higher predicted expression in microglial/autophagy activators) with modest glutamatergic signals. MR indicated genetically proxied higher educational attainment causally increases BD risk (IVW OR = 1.403, p = 6.69 × 10⁻⁵). In MDD, pruning was robust in heritability (LDSC p < 10⁻⁹⁰) but mediated/non-enriched in expression (TWAS p > 0.7), with glutamatergic TWAS signals (p = 0.007); education was protective (OR ≈ 0.72).Conclusion: Synaptic pruning emerges as the primary, independent pathway in BD—activation-skewed and amplified by cognitive reserve into episodic instability—distinguishing it from MDD's mediated pruning deficits with protective reserve. These findings reframe BD toward neuroimmune-pruning models, with implications for targeted therapeutics and cross-disorder nosology.

Abstract: Traditional paradigms of nation-building and state-building have dominated political theory and international policy for decades, yet their explanatory and prescriptive power remains limited in postcolonial and conflict-affected contexts. Recurrent instability, institutional fragility, and governance failure are often interpreted as operational deficiencies, yet this article contends that the root cause is primarily epistemological. Existing frameworks fragment political life into discrete domains—institutions, identity, legitimacy—while remaining anchored in Westphalian assumptions that fail to capture the dynamic, adaptive nature of political communities.This article introduces Nationology, a novel transdisciplinary science dedicated to the study of nations as living, adaptive systems whose persistence depends on regenerative processes rather than mere stabilization. Nationology integrates insights from political theory, comparative constitutionalism, postcolonial scholarship, and systems science to provide a unified analytical framework encompassing institutions, collective meaning, historical memory, leadership intelligence, and legitimacy. Using the Democratic Republic of the Congo as a paradigmatic case of systemic complexity, the article demonstrates why conventional paradigms systematically misread patterns of persistence, fragility, and renewal.The study concludes that the future of political order relies not on institutional replication alone but on a community’s capacity to regenerate meaning, legitimacy, and collective coherence under systemic strain. Nationology thus offers a transformative lens for political theory, global constitutionalism, and the science of sustainable political communities.

Abstract: Multiphoton endomicroscopy (MPEM) has recently become a key development in optical biomedical diagnostics, providing histologically relevant in vivo images that are eliminating both the need for tissue damage during biopsy sampling and the need for dye injections. Due to its ability to visualize structures at the epithelial, extracellular matrix, and subcellular levels, MPEM offers a promising diagnostic method for precancerous conditions and early forms of gastrointestinal (GI) cancer. The high specificity of multiphoton signals—the two-photon fluorescence response of endogenous fluorophores (NADH, FAD), the second-harmonic generation signal from collagen, and others—makes this method a promising alternative to both traditional histology and confocal endoscopy, enabling real-time assessment of metabolic status, intestinal epithelial cell status, and stromal remodeling. Despite the promising prospects of multiphoton microscopy, its practical implementation is progressing extremely slowly. The main factors here include the difficulty of delivering ultrashort pulses with high peak power, which is necessary for multiphoton excitation (MPE), and obtaining these pulses at the required wavelengths to activate the autofluorescence mechanism. One of the most promising solutions is the use of specialized multimode optical fibers that can both induce the beam self-cleaning (BSC), which allows for the formation of a stable beam profile close to the fundamental mode, and significantly broaden the optical spectrum, which can ultimately cover the entire region of interest. This review presents the biophysical foundations of multiphoton microscopy of GI tissue, existing endoscopic architectures for MPE, and analyzes the potential for using novel nonlinear effects in multimode optical fibers, such as the BSC effect and supercontinuum generation. It is concluded that the use of optical fibers in which the listed effects are realized in the tracts of multiphoton endomicroscopes can become a key step in the creation of a new generation of high-resolution instruments for the early detection of malignant neoplasms of the GI tract.

Abstract: The adoption of digital twins has revolutionized industrial process simulation, monitoring, and control effectiveness. However, practical implementations of digital twins are hindered by substantial challenges, including extended development time, diminishing model accuracy, and restricted interactive capabilities. Addressing these critical issues, this paper proposes a comprehensive digital twin development framework that integrates digital twin identification, real-time model updating, and advanced process control. The proposed approach first identifies the offline digital twin model through the sparse identification of nonlinear dynamics algorithm, reducing the digital twin development time while maintaining model fidelity. Then, the identified model is updated by the extended Kalman filter to mitigate the problem of diminishing accuracy. Finally, incorporating the latest updated model into the model predictive control facilitates the control inputs optimization and enhances the interactive capacity of digital twins. Through one industrial case study and two simulation examples, the advantages of the proposed algorithm are demonstrated.

Abstract: Filter cake (or cachaza), a residue generated in the artisanal production of panela, represents an under-explored source of renewable energy in the Ecuadorian Amazon. Valorizing filter cake could reduce the use of solid biomass and emissions associated with traditional combustion. Our objective was to determine the energy potential of the biogas obtained and its contribution to the sustainability of the panela (unrefined cane sugar) production system. A sequential procedure was applied that included the physicochemical characterization of filter cake, feed flow modeling, and stoichiometric simulation under mesophilic conditions. The anaerobic digestion of filter cake with the optimal Composition 6 generated up to 1,736.40 m³·day⁻¹ of biogas with 40.7% methane and a calorific value of 14,350 kJ·m⁻³. This was enough to replace 1.24 t·day⁻¹ of wood or 2.38 t·day⁻¹ of bagasse in the production system. This represents an annual saving of 631.08 t of solid biomass, equivalent to conserving 3.63 ha·year⁻¹ of the Amazon rainforest. The TRACI analysis showed impacts on climate change (17.40 kg CO₂ eq/m³) and acidification (0.00516 kg SO₂ eq/m³), attributable to unburned methane and residual H₂S. Meanwhile, the social assessment using the OHSP indicator showed high risks in terms of handling filter cake and cleaning the digestate.

Abstract: In the seismic design of reinforced concrete moment-resisting frame (RC MRF) structures equipped with steel damper columns (SDCs), design criteria should consider both peak responses (e.g., story drift) and cumulative responses (e.g., cumulative strain energy of damper panels in SDCs). These response measures are associated with two energy-based seismic intensity parameters: the maximum momentary input energy governing peak responses and the cumulative input energy governing cumulative responses. The relationship between these parameters depends on the characteristics of the ground motions. This study proposes an energy-based limit curve for RC MRFs with SDCs using the two seismic intensity parameters. Incremental critical pseudo-multi impulse analyses (ICPMIAs) are performed for three eight-story RC MRFs with SDCs considering various numbers of pulsive inputs. For each analysis, the input intensity is incrementally increased until predefined limit-state criteria are reached. The limit curve is constructed by connecting the equivalent velocity pairs corresponding to the two energy-based seismic intensity parameters at the limit states. The applicability of the proposed limit curve is examined through nonlinear time-history analyses (NTHAs) using recorded ground motions, including the mainshock–aftershock sequence of the 2011 off the Pacific coast of Tohoku Earthquake and the foreshock–mainshock sequence of the 2016 Kumamoto Earthquake. The results indicate that (a) considering a range of 2 to 32 pulsive inputs in ICPMIA is sufficient to cover the NTHA results examined in this study; (b) most NTHA cases satisfying the limit-state criteria are located within the proposed limit curve, whereas cases exceeding the criteria are located outside the curve; and (c) the consideration of earthquake sequences tends to result in a larger number of cases exceeding the limit-state criteria compared with single-earthquake scenarios.

Abstract: Deep and middle-layer tight sandstone reservoirs represent an emerging frontier in oil and gas exploration and development. Significant breakthroughs have recently been achieved in the northern deepwater region of the Qiongdongnan Basin, particularly within the Oligocene Lingshui Formation in the Baodao Depression. However, the petrophysical characteristics of these tight sandstone reservoirs and the controlling factors influencing sweet spot development remain poorly understood. This study integrates comprehensive datasets—including thin section petrography, cathodoluminescence, scanning electron microscopy (SEM), X-ray diffraction (XRD), and conventional reservoir property analyses—to systematically investigate the reservoir characteristics and key controls on sweet spot formation in the third member of the Lingshui Formation along the northern slope of the Baodao Depression. A pore evolution model for sweet spot reservoir development is subsequently proposed. The results indicate that: 1) The tight sandstones are predominantly lithic feldspathic quartzarenite, feldspathic quartzarenite, and feldspathic litharenite, with primary pore types including feldspar dissolution pores, moldic pores, and residual intergranular pores. 2) Among these, feldspathic quartzarenite and lithic feldspathic quartzarenite exhibit superior reservoir quality and constitute the main sweet spots; high quartz and feldspar content coupled with low lithic fragment abundance are critical compositional controls on sweet spot formation in deep to middle-depth settings. 3) Grain size demonstrates a positive correlation with reservoir physical properties. Compaction has led to porosity reduction by 22.0%~28.0%, establishing the fundamental basis for reservoir tightness. 4) Dissolution processes play a pivotal role in enhancing reservoir quality. Secondary porosity zones developed at depths of 3800~3950 m and 4100~4400 m due to dissolution significantly improve porosity and permeability. Conversely, during the late stage of mesodiagenesis (Stage B), extensive carbonate cementation contributes to further reservoir compaction. This research provides a theoretical foundation for the evaluation and prediction of sweet spot reservoirs in deepwater tight sandstone systems in the South China Sea, offering guidance for hydrocarbon exploration, field development planning, and the selection of favorable drilling targets. Furthermore, it advances the understanding of the formation mechanisms and evolutionary pathways of different types of sweet spots in deep and middle-layer tight sandstone reservoirs.

Abstract: Dental radiography is an essential component of modern dental practice, and its use has increased with the wider availability of panoramic imaging and cone-beam computed tomography (CBCT). Dental radiographic equipment is commonly described by manufacturers as emitting relatively low radiation doses, which has contributed to a widespread perception of safety in routine dental practice. Although occupational radiation exposure in dentistry is generally considered low, most published studies and radiation protection guidelines are based on dental clinics located in conventional healthcare buildings with appropriate structural shielding. In contrast, many industrial organizations, such as those in the petroleum, energy, and mining sectors, operate permanent medical and dental clinics within facilities constructed using lightweight or artificial wall materials, where radiation protection measures may be limited or inconsistently applied. This narrative review examines occupational radiation exposure in dental clinics operating within industrial facilities characterized by non-standard architectural designs, with particular attention to potential effects on thyroid health. The thyroid gland is highly sensitive to ionizing radiation, and long-term low-dose exposure, especially in confined spaces with inadequate shielding, may represent an underestimated occupational risk. Available evidence on occupational radiation doses in dental practice, scatter radiation associated with CBCT, biological mechanisms of thyroid radiosensitivity, and current radiation protection recommendations is reviewed and discussed. By addressing an under-recognized occupational setting, this review highlights important gaps in radiation safety related to architectural design, regulatory oversight, and dose monitoring in industrial dental clinics. The findings support the need for improved assessment of structural shielding, routine use of personal dosimetry, and targeted radiation safety training to better protect dental healthcare workers and other personnel working in proximity to dental imaging areas in these environments.

Abstract: We show that quantum phase estimation (QPE) resolution is a linear rescaling of the spectral gap of a unitary operator, making the correlation between these two quantities athematically guaranteed. Using this observation, we demonstrate that spectral properties alone can reliably predict quantum algorithm performance without executing full circuit simulations. Through analysis of 400 randomly generated two-qubit unitaries and six standard quantum gates, we confirm that the spectral gap and QPEresolution exhibit a perfect Pearson correlation (r = 1.0000, p < 10⁻⁸), a relationship that persists across diverse gate families and extends to three-qubit systems. Building on this foundation, weintroduce four novel spectral metrics and develop a machine learning framework that predicts algorithmic performance with 99.48% accuracy while achieving thousand-fold speedups over traditional simulation. Statistical validation includes bootstrap confidence intervals and Bonferroni correction for multiple comparisons. These results establish spectral analysis as an efficient and generalizable approach to quantum gate characterization, with immediate applications in gate library optimization, quantum compiler design, and algorithm–hardware co-design for near-term quantum devices.

Abstract: Background: Immunosenescence, the age-related decline in immune function, represents a critical challenge in geriatric medicine. Traditional modeling approaches fail to capture the spatial heterogeneity and compositional complexity of the aging immune system.Methods: We developed a quantum-inspired tensor product Hilbert space framework integrating 11 immune cell types across 8 tissue compartments (dimension: 88). Two cohorts—young adults (<50 years) and elderly individuals (>65 years)—were simulated using empirically derived distributions from recent immune cell census studies. State evolution was governed by a spatial Hamiltonian incorporating intratissue dynamics, cellular trafficking, and cytokine-mediated coupling.Results: The elderly cohort exhibited hallmark immunosenescence signatures: 30% reduction in naive T lymphocytes (p<0.001), 25% expansion of NK cells (p<0.001), and 33% impairment in migration capacity. Tissue-specific Shannon entropy decreased by 8-12% across major compartments (lymph nodes: -11%, bone marrow: -8%, peripheral blood: -9%), providing a quantitative metric for immune aging. Enhanced intertissue coupling (1.5-fold increase) captured inflammaging signatures. Multivariate analysis yielded a composite aging index with 89% discrimination accuracy (AUC=0.89, 95% CI: 0.83-0.94).Conclusions: Information-theoretic diversity metrics derived from spatially resolved models provide quantifiable biomarkers of immunological aging with strong clinical correlations. This framework enables personalized immune age assessment, vaccine responsiveness prediction, and rational design of immune rejuvenation strategies.

Abstract: Multipath interference and non-stationary channel dynamics severely degrade Wi-Fi CSI-based vital sign monitoring. This paper introduces Deep Wavelet Scattering Networks (DWSN), integrating multi-resolution wavelet scattering transforms with deep convolutional separation layers and path signature normalization. Extending the wavelet-domain decoupling framework, DWSN achieves translation/deformation invariance through second-order scattering coefficients while learning non linear separation boundaries. Rigorous theoretical analysis derives scattering stability bounds under Lipschitz-continuous multipath perturbations (O(ϵlog(1/ϵ))), establishing >32 dB cross-talk attenuation. Extensive experiments on 200 synthetic CSI traces (3–12 Rayleigh paths, SNR: 0–20 dB) demonstrate 67% CTR improvement over EMD, 58% MAEreduction (0.7 BrPM RR, 1.6 BPM HR at SNR=5dB), and 2.3× robustness to HR/RR transitions vs. baseline wavelet MRA. Real-time ESP32 deployment achieves 68 ms latency via tensorized scattering operators. No human subjects were involved; all validation uses synthetic physiological models.

Abstract: A retrospective ozone simulation was conducted with the Microscale Forward and Adjoint Chemical Transport (MicroFACT) model for an industrialized area of Detroit, Michigan, USA using a 24 km × 24 km horizontal × 1.5 km vertical grid. The domain encompassed a regulatory monitoring station at East 7 Mile Rd at the northern edge of the grid. The episode day was 30 June 2022, when the station-measured 8-hour ozone reached 76 ppb during predominantly southwesterly wind. The ozone impacts of mobile, point, nonpoint, and biogenic emissions were simulated at 400 m horizontal resolution. Simulation results were compared against station measurements of ozone, nitrogen oxides, and total reactive nitrogen. Local nitrogen oxide sources were found to titrate ozone, while ozone turbulently entrained to the surface from ~500 m aloft enhanced surface Ozone Production Efficiency and led to extended periods of high ozone concentrations very similar to observations. Volatile Organic Compound emission reductions produced only weak decreases in maximum 8-hour ozone, suggesting that radicals were enhanced mostly by photolysis of subsiding ozone. Entrainment of ozone layers aloft may thus be critical in explaining historical ozone exceedances of the United States National Ambient Air Quality Standard at the East 7 Mile Rd station.

Abstract: Mitochondria orchestrate energy transfer, redox poise, and cell fate. Within this landscape, tryptophan catabolism yields kynurenines (KYNs), a versatile metabolite shaping organelle function. Emerging studies implicate G protein–coupled receptor 35 (GPR35), the aryl hydrocarbon receptor (AhR), and N-methyl-D-aspartate (NMDA) receptors as conduits between extracellular cues and adenosine 5′-triphosphate (ATP) maintenance, calcium handling, mitophagy, and inflammasome restraint. Parallel work links quinolinate driven de novo nicotinamide adenine dinucleotide (NAD⁺) synthesis to tricarboxylic cycle (TCA) control and sirtuin programs across tissues. Yet the field lacks an integrated view that connects receptor pharmacology to NAD⁺ economics and respiration, and it lacks single run clinical assays that quantify both KYN and TCA nodes. This review addresses those gaps by mapping receptor specific mitochondrial mechanisms of KYNA, delineating pathway–cycle crosstalk, and appraising unified liquid chromatography–mass spectrometry (LC–MS) strategies for simultaneous quantification. We synthesize evidence for mitochondrial GPR35 signaling that preserves ATP, AhR programs that tune mitophagy and oxidative defenses, and NMDA antagonism that limits excitotoxic stress. These mechanisms are integrated with quinolinate dependent NAD⁺ biogenesis and α-ketoglutarate checkpoints, then benchmarked against chromatographic and ionization solutions suitable for clinical workflows. Here we highlight a receptor to organelle axis that couples KYN metabolism flux to respiratory control and offer a practical roadmap for standardized, single run LC–MS panels. The framework can sharpen target validation in ischemia, neurodegeneration, psychiatry, and oncology, while de-risking biomarker qualification through harmonized analytics. More broadly, resolving temporal dynamics, compartmental signaling, and cross matrix comparability will accelerate movement from association to intervention and enable decision grade metrics for patient selection, pharmacodynamic readouts, and therapeutic design.

Abstract: This work offers formal proofs which were enabled by a change in perspective from studying individual integer iterations to analyzing how the conjecture's rules organize the positive integers. The proofs rigorously demonstrate the satisfaction of several critical criteria: the universal inclusion of all positive integers within the proof's scope; the disclosure of a simple and predictable pattern among the numbers; the conclusive absence of any major loops; the demonstration that no number continuously increases indefinitely without eventually decreasing; and the ultimate convergence of all positive integers to 1 when subjected to the Collatz iteration rules. Formal verification of these proofs was conducted using the Isabelle/HOL proof assistant.

Abstract: The use of virtual reality for pilot flight training, whether as a stand-alone device, or to augment or replace a conventional simulator, has gained significant attention in recent years. The primary purported benefit of virtual reality is its increased ability to achieve immersion of the trainee, which has particular benefits for visuospatial awareness. This benefit of the technology would appear to offer little advantage in the training of instrument-flying skills, where only the aircraft’s instrumentation needs to be accurately rendered in order that the status of the ownship can be known. However, given the wide-scale intention toward the adoption of the technology, it is likely that instrument flight training will be one of its uses at flight schools. In order that the effectiveness of the VR Simulator can be evaluated, for instrument flight training, a quasi-randomised separate-sample pretest–posttest design study was completed. The ability of this low-cost VR simulator to transfer the flying skills required to conduct an ILS approach, after establishment on approach, was evaluated with 44 participants. Results indicate significant improvement in participants’ flying skills based on operational (r_rb = 0.508) and synthetic (g = 0.844) performance metrics. The findings indicate that the VR simulator appears effective for the training of these skills, and that the immersion and presence are not detrimental, even when the primary focus is the instrument panel. The idea that VR is an effective tool for training instrument flight skills has not previously been demonstrated. Due consideration must, however, be given to the context of this study and the noted limitations of the VR technology.

Abstract: Background: Although physical activity (PA) offers substantial physical and psychosocial benefits, engagement remain suboptimal among cancer survivors. A theory-informed understanding of survivors’ perceived barriers, facilitators, and recommendations is needed to inform patient-centered PA survivorship interventions. Objective: This study aimed to explore perceived barriers, facilitators, and recommendations for PA engagement among adult cancer survivors using the Theoretical Domains Framework (TDF). Methods: A phenomenological qualitative design was used. Eighteen cancer survivors from Nebraska participated in semi-structured interviews via Zoom or telephone. Interviews were transcribed verbatim, imported into MAXQDA 2024, and analyzed using TDF to identify themes and subthemes. Results: Three overarching themes emerged: barriers, facilitators, and recommendations related to PA engagement. Barriers included individual factors (low motivation and self-efficacy, limited awareness of PA guidelines, time constraints, and physical limitations due to treatment and comorbidities), social factors (limited support from family, friends, and healthcare providers), and environmental factors (restricted access to resources and unfavorable weather). Facilitators included individual factors (PA knowledge, motivation, goals, and health benefits), social factors (support from family, friends, and healthcare providers), and environmental factors (favorable weather and available community PA resources). Recommendations emphasized the need for tailored education, supportive counseling, and structured PA programs within survivorship care. Conclusions: Cancer survivors described multilevel determinants of PA engagement across individual, social, and environmental contexts. Findings highlight the importance of theory-informed, patient-centered strategies that enhance PA guideline awareness, strengthen social and clinical support, and improve access to community resources to promote sustained PA during cancer survivorship.

Abstract: This paper introduces Ze, a novel theoretical framework for cognitive architecture based on the concurrent operation of two distinct generative models of the environment: a causal (forward) model M_A and a counterfactual (inverse) model M_B. The core dynamics of Ze arise from the minimization of two separate variational free energies, F_A and F_B, and the management of the conflict between them, ΔF = |F_A - F_B|. This conflict regulates a phase transition between an interference regime, where model outputs are constructively fused, and a localization regime, which resolves the conflict through a discrete projection. We formally establish a deep structural isomorphism with quantum measurement, particularly the double-slit experiment, without invoking quantum physics in the substrate. Ze is proposed as a complete, falsifiable theory that reinterprets cognitive "collapse" as an optimization-driven transition, generates novel experimental predictions, and integrates perception, action, and representational learning into a unified architecture. This preprint provides the full mathematical elaboration of the framework.