Abstract: This paper takes Tongwei, Gangu, Wushan and Qin'an counties involved in the 1718 Tongwei earthquake as the study area, combines with the case investigation of earthquake damage and historical landslide data, and uses the statistical analysis model to select 10 impact factors related to topography, geology, earthquakes and human activities in the study area.Finally, the relative contribution and coupling effect of different influencing factors to the spatial distribution of earthquake-induced loess landslides are discussed by principal component analysis. The results show that: (1) The loess seismic landslides in the study area are concentrated in the south-facing slope areas with elevation of 1000-1300 m, slope of 10-20°, topographic relief of 0-30 m, 1200-1600 m away from rivers, 2-8 km away from active faults, intensity of X, land use types of grass and farmland, and relatively weak lithology. (2)Further verified that the prone areas of loess landslides in the study area are the areas near rivers with an elevation of 1600-1900m and a slope of 10-20 degrees, and the areas covered by thick loess layers with a distance of 4-12 km from active faults.

Abstract: Hidradenitis suppurativa (HS) is a severe inflammatory dermatosis characterized by profound localized pain. While current pathophysiological feedback loops (vicious cycles) focus on microscopic molecular networks and microbiological dysbiosis, the psychosocial and behavioral burdens of HS are individually well-documented. However, these behavioral maladaptations have not been integrated into a unified macroscopic model. This self-sustaining system operates across three interacting domains: (1) a biomechanical-metabolic loop, where sustained immobility accelerates visceral adiposity and insulin resistance; (2) a psychosocial-physiological loop, where pain-induced sleep disruption and chronic stress drive neuroendocrine dysregulation and maladaptive coping behaviors; and (3) a socioeconomic loop, where economic instability decreases healthcare security. Consequently, these behavioral, psychological, and socioeconomic burdens structurally feed back into the systemic inflammatory core, perpetuating disease chronicity. Moreover, this review explores kinesiophobia (the anticipatory fear of movement) as a potentially critical and overlooked component of the biomechanical-metabolic feedback loop. Currently, there is a notable absence of primary psychometric data quantifying kinesiophobia in the HS population. Future research must first measure this phenomenon to establish its prevalence and role. On a macroscopic level, clinicians should aim to systematically break the broader interconnected behavioral feedback loops through multidisciplinary interventions, including cognitive-behavioral therapy and structured patient education. Ultimately, dismantling these psychological and behavioral barriers may prove biologically imperative to halt systemic inflammatory amplification and improve long-term clinical outcomes.

Abstract: We discuss gravitational concepts and candidate specifications for dark matter that, together, can help explain known ratios of dark-matter effects to ordinary-matter effects and can help explain eras in the rate of expansion of the universe. The ratios pertain to galaxies and galaxy evolution, galaxy clusters, and densities of the universe. The candidate specifications for dark matter reuse, with variations, a set of known elementary particles. Regarding galaxy evolution and the rate of expansion of the universe, we deploy multipole-expansion methods that combine Newtonian gravity, aspects of motions of sub-objects of gravitationally interacting objects, and Lorentz invariance. One outgrowth from our work suggests relationships among some physics constants. Another outgrowth from our work suggests a basis for a candidate specification for quantum gravity.

Abstract: This paper proposes Scheme M, a new presidential design that evolves the American model by introducing flexibility in election timing while preserving executive stability. Its flexible elements draw inspiration from the post-2017 Turkish presidential system, where variable terms are enabled by early general elections. However, unlike Türkiye—where the Assembly can also trigger early presidential elections, creating perceived insecurity—Scheme M removes this reciprocal power, assigning sole responsibility to the president to identify, assess, and resolve executive-legislative deadlocks. The scheme adapts the established American practice of midterm elections by adding contingent, flexible-timing elements: the mechanism is triggered exclusively by presidential decree, limited to once per five-year term and only within the first three years. It keeps the president's fixed term secure while allowing strategic timing—or avoidance—of midterm legislative elections to refresh or realign parliament at low personal cost. Additional safeguards include a mixed SMDP-PR electoral system to prevent chronic presidential majorities, parliamentary confirmation for the vice-presidential nominee, narrowly defined decree powers, and robust term limits. The scheme has two variants: Scheme FM and Scheme VM. Scheme FM features fixed-time general elections, enhancing predictability, cost efficiency, and campaign depth. Scheme VM introduces variable terms, ensuring near-certain same-party succession, empowering a lame-duck president to renew both branches—avoiding paralysis or premature resignation—and allowing strategic general election timing akin to Westminster practices. Scheme M therefore offers a viable blueprint for stable yet responsive presidential governance.

Abstract: Alzheimer’s disease (AD) represents a escalating global neuropharmacological crisis, with prevalence in high-growth demographic regions such as India projected to exceed 14 million by 2040. This study addresses the urgent need for high-potency, dual-site acetylcholinesterase (AChE) inhibitors through an integrated computational pipeline. Background: We address the failure of mono-target paradigms by designing scaffolds capable of simultaneously anchoring the Catalytic Active Site (CAS) and the Peripheral Anionic Site (PAS). Methods: A robust GA-MLR QSAR model was developed from 115 quinoline analogues using 11,135 descriptors. Lead candidates were prioritized via blind molecular docking (7XN1) and 100-ns molecular dynamics (MD) simulations. Results: The five-descriptor model (R2 = 0.7569, QLOO2 = 0.7244) was validated by an external set of 8 experimental compounds (Rext2 = 0.8620). Lead Compound 19 emerged as a superior candidate (ΔG = -11.1 kcal/mol), exhibiting a stable MD trajectory (PL-RMSD ≈ 2.4 Å) and preserving essential Gly121-His447 catalytic anti-correlations. Conclusions: This study provides a statistically validated scaffold and mechanistic foundation for future biomimetic chromatography validation, advancing the high-throughput screening of neuroprotective agents on a global scale.

Abstract: We prove that \delta^{(4)}(x - y) \notin L^{2}(\mathbb{R}^{4}) is not a legitimate physical Green's function under the quantum- mechanical postulate of finite energy (A1). A fourth postulate of closed sourcelessness (A4)—methodologically analogous to Einstein's postulate of the constancy of the speed of light—is derived as a theorem from the quantum- gravity result \dim \mathcal{H}_{\mathrm{universe}} = 1 [1- 8]. Under three independent postulates A1- A3 together with this result, we derive the unique physical Green's function G = \sin (\Omega \sqrt{-\sigma^{2} - i\epsilon}) / (\Omega \sqrt{-\sigma^{2} - i\epsilon}) , \Omega = \pi /t_{P} . The bandlimited two- point function K of the resulting Paley- Wiener space \mathrm{PW}_{\pi /t_{P}} admits the spherical Bessel decomposition

Abstract: Irreversible loss of neurons in the adult mammalian central nervous system is a core driver of cognitive decline, yet existing "repair after damage" strategies cannot reverse established injury. Here, we propose a disruptive hypothesis: utilizing mitochondrial outer membrane permeabilization (MOMP) as the molecular switch for "irreversible" apoptosis, we construct a closed-loop system for real-time seamless replacement of apoptotic neurons. The system comprises two core modules: a labeling module that performs specific membrane modification (PS acetylation) on neurons at the earliest stage of irreversible apoptosis, and a replacement module (engineered autologous neural progenitor cells) that precisely targets apoptotic sites via dual-signal recognition (modified PS + chemokine CX3CL1), accomplishing timed clearance of apoptotic debris and in situ neuronal differentiation before cellular disintegration, achieving "zero-latency replacement." The core innovation of this hypothesis lies in not pursuing "pixel-level replication" of the apoptotic neuron's connections. Instead, it relies on the nervous system's inherent plasticity: after precise delivery of newborn neurons to the apoptotic site, subsequent synapse outgrowth, competition, and stabilization are accomplished by the neuron's intrinsic growth programs and local network activity-dependent plasticity. The human nervous system is inherently in a state of continuous synaptic turnover and remodeling; newborn neurons, as participants in this dynamic process, will manifest their functional contributions over time. Therefore, even partial synaptic functional replacement is sufficient to make a substantial contribution to neural network homeostasis—this itself represents a paradigm shift from 0 to 1. All core designs of this hypothesis are grounded in established consensus findings, with clear stepwise validation pathways and strict falsifiability, providing a novel theoretical framework for neural repair and intervention in cognitive aging.

Abstract: This study investigates the relationship between economic growth, technological innovation, renewable energy consumption, and CO₂ emissions in Vietnam from 1988 to 2021, using a Vector Error Correction Model. Three key findings emerged. First, economic growth remains strongly coupled with carbon emissions in the long run, indicating a fossil fuel-dependent economic structure. Second, technological innovation yields positive but limited short-term effects, requiring extended periods to achieve a full impact. Third, renewable energy exerts strong positive short-term effects, but negative long-term effects, reflecting structural economic shifts. This study proposes five policy recommendations: commercializing patent innovations, rapidly expanding renewable energy for immediate growth, decoupling growth from emissions, combining clean energy with technological advancement, and implementing policy reforms immediately rather than relying on long-term strategies alone.

Abstract:

Stable oxygen isotopes (δ¹⁸O) in wood provide integrative records of plant water use and regional hydroclimatic processes, offering a powerful framework for spatial ecological analysis in tropical forests. Here, we present the first regional-scale δ¹⁸O isoscapes for Amazonian wood based on 387 trees sampled across 25 sites. After α-cellulose extraction, δ¹⁸O values were modeled using multiple linear regression (MLR) and Random Forest (RF) approaches. A Moran’s I test revealed no significant spatial autocorrelation (p = 0.73), indicating that geostatistical interpolation methods such as kriging were not appropriate for this dataset. The MLR model based on site-average data achieved an R² of 0.70, with a mean absolute error (MAE) of 0.56‰ and root mean square error (RMSE) of 0.68‰. The RF model showed comparable performance (R²= 0.67; MAE = 0.64‰; RMSE = 0.77‰). Both approaches reproduced a coherent southeast-to-northwest gradient, with lower δ¹⁸O values in the western Amazon and higher values in the east, consistent with regional patterns in precipitation isotopic composition and evapotranspiration. These findings demonstrate that climate-driven statistical modeling effectively captures large-scale isotopic structure across the Amazon basin, providing a robust spatial representation of δ¹⁸O variability in tropical forest wood.

Abstract: In this work, we inspected the friendship network on Twitter (recently rebranded as X), concentrating on individuals and organizations intertwined with the energy field. We particularly focus on seasoned professionals, corporate entities, and domain specialists, all connected through `following’ relationships. By meticulously examining these ties, we uncover several distinct groupings within the network, each defined by the unique roles its members occupy. Our analysis demonstrates that the natural emergence of such clusters on social platforms exerts a profound influence on public discourse regarding energy and other critical matters, including climate change. Furthermore, we reveal that the ever-changing interplay of misleading information catalyzes the formation of ideologically divided factions, which often leads to reduced engagement in online conversations. These emergent clusters, characterized by their shared communication styles, form relatively compact communities where the exchange of information is infrequent compared to larger networks and is usually confined to accounts created for specific commercial objectives. Additionally, by leveraging a machine learning approach, we are able to pinpoint pivotal actors within these niche segments and elucidate the mechanisms that sustain their connectivity. This method provides novel insights into how corporate communication unfolds on social media, offering a refreshed perspective on professional networking. Ultimately, our findings highlight the ways in which companies within the energy sector take advantage of Twitter to coordinate their initiatives, with key institutions serving as central nodes in maintaining the organization of these networks.

Abstract: Background/Objectives Light-assisted in-office whitening procedures are widely used in clinical practice; however, comparative clinical data remain limited, particularly when evaluated using objective outcome measures. This exploratory pilot randomized clinical trial aimed to assess the immediate objective performance of two light-assisted in-office whitening protocols using standardized digital spectrophotometry. Materials and Methods Twelve healthy adult participants (18–45 years) presenting extrinsic or mixed-type tooth discoloration (baseline shade VITA A3 or darker) were randomly allocated into two parallel groups (n = 6 each). One group received whitening with a 35% hydrogen peroxide gel activated by a diode laser device, while the other group underwent whitening with a 25% hydrogen peroxide gel activated by an LED-based device. Tooth color was measured before and immediately after treatment using a digital spectrophotometer (VITA Easyshade V, VITA Zahnfabrik, Bad Säckingen, Germany), and color differences (ΔE) were calculated based on CIE L*a*b* coordinates. Statistical analysis was performed using the Mann–Whitney U test. Results: Both light-assisted interventions resulted in clinically perceptible whitening outcomes (ΔE > 3.3). The LED-assisted group showed a slightly higher mean ΔE value (11.62 ± 5.93) compared with the laser-assisted group (10.96 ± 3.27); however, the difference was not statistically significant (p = 0.818). Given the limited sample size, the study was not powered for definitive comparative inference. No adverse events were recorded. Conclusions: Within the limitations of this exploratory pilot randomized clinical trial, both light-assisted in-office whitening protocols produced immediate clinically perceptible color changes. Although no statistically significant difference was detected, the limited sample size precludes definitive conclusions regarding relative efficacy. Larger, adequately powered randomized studies incorporating longitudinal follow-up and patient-reported outcomes are required to confirm these preliminary findings.

Abstract: Seasonal influenza in children is usually recognized as acute febrile respiratory syndrome. This commentary highlights recent clinical observations in which influenza-like illness was accompanied by conjunctivitis and sleep-related breathing abnormalities (new snoring and brief apnea-like events), sometimes accompanied by oxygen desaturation. Because these features are not classic manifestations of seasonal influenza, they are best framed as associated findings that may reflect upper-airway inflammation, post-nasal drip, or concomitant lower-respiratory involvement. The commentary discusses the Egyptian/African approach using Kelleni’s protocol in its outpatient management and calls for independent monitoring by pediatric and ENT/sleep clinicians to determine whether a reproducible pattern is emerging across settings.

Abstract: This study presents an innovative approach for the selective extraction of Co(II) and its separation from Ni(II) using ethyl ester glycine-betaine derivatives, specifically tri(n-pentyl)[2-ethoxy-2-oxoethyl]ammonium dicyanamide, as extractants in combi-nation with continuous-mode liquid–liquid contact. Semi-pilot-scale implementation requires non-equilibrium conditions, characterized by short contact times between ef-fluent and extractant phases. To address this, we propose dissolving analog of gly-cine-betaine ionic liquid (AGB-IL) in low-viscosity MIBK solvents to enhance mass transfer while reducing dependence on fossil-based solvents. Liquid–liquid extraction and continuous-flow stripping experiments were designed based on prior batch results and conducted in a saline environment, employing a chaotropic electrolyte for extrac-tion and a kosmotropic electrolyte for stripping. Both open and closed systems were tested to compare extractive performance with batch conditions and with scenarios representative of industrial operations. Results indicate that continuous-flow systems achieve performance comparable to batch systems in terms of extraction efficiency, Co/Ni separation coefficients, and recyclability. These findings provide proof of con-cept for the development of semi-pilot and pilot-scale processes for efficient cobalt re-covery.

Abstract: Background/Objectives: In the United States alone, new prostate cancer (PCa) cases for 2023 are estimated at 288,300 and deaths at 34,13700 [1]. Prostate imaging is increasingly evaluated by artificial intelligence and computer-assisted targeting which opens new opportunities in biopsy and the focal therapy of visualized lesions [2]. Our objective was to investigate the safety and feasibility of using MR-guided focal laser (light amplification by the stimulated emission of radiation) therapy for these visible cancers using a transrectal approach for both laser applicator placement and therapy delivery in an outpatient setting. Methods: We used a 1.5 Tesla MRI scanner (Philips Healthcare, Best, The Netherlands) for both image acquisition and real-time thermometry. In addition, we used a commercially available CAD system and targeting hardware (Philips, Best, The Netherlands) for image analysis and interventional planning. Laser focal therapy of biopsy-proven lesions was delivered using a U.S. Food and Drug Administration (FDA) 510(k) cleared laser emitter, laser fiber and thermal mapping visualization software (Medtronic, Minneapolis, MN, USA) introduced transrectally under MRI-guidance. Results: 112 cancer foci were treated in 81 men, from Gleason Grade 1 (GG1) to GG3 for treatment-naïve patients and all Gleason Grades for salvage patients. With pre-treatment lesion volumes ranging from 0.03 cc to 6.6 cc, with a mean of 1.1 cc and a median of 0.49 cc (25% and 75% quartiles of 0.25 cc and 1.4 cc respectively). The mean MRI volume of coagulation necrosis was 7.1cc and ranged from 0.6cc to 22.9cc. No serious adverse events or morbidity were reported. At six-month MR-guided in-bore biopsy 25 treatment regions were positive for clinically significant disease (GG>1), consistent with in-field residual or recurrent cancer rate of 22% of regions and 23% of subjects. We observed a 40% decrease in mean PSA at 1 year post therapy in the entire cohort. Conclusions: Our data indicate that transrectally delivered MRI-guided laser focal therapy for prostate cancer is both safe and feasible in an outpatient setting and results in a significant biochemical response and acceptable cancer control rate at 6 months.

Abstract: Background: Spirituality and religious diversity are increasingly recognized as essen-tial components of holistic nursing care in global healthcare systems. However, their integration into undergraduate nursing education remains heterogeneous and often insufficiently structured, creating a gap between professional values and students’ preparedness to address spiritual needs in culturally diverse clinical environments. This study aimed to explore nursing students’ perceptions, attitudes, and perceived skills regarding spirituality, religion, and spiritual care, and the factors associated with these dimensions. Methods: A descriptive exploratory survey was conducted on a sample of 69 third-year students of the Degree Course in Nursing belonging to two Roman universities. Data were collected between May and July 2025 using the Nursing Care and Religious Diversity Scale (NCRDS), consisting of 31 items. Statistical analyses included descriptive statistics, internal reliability analyses, group comparisons, and multivariate regression models. Results: Students showed moderate levels of attention to patients' spiritual needs and integration of spirituality into care practice, while high importance was given to spiritual care skills. University education was perceived as only partially adequate. Multivariate analyses showed that students' personal spiritu-ality is positively associated with the assessment of spiritual needs and the perception of competence, while exposure to contexts characterized by greater religious diversity is associated with a lower perception of preparedness. Conclusions: The results high-light a discrepancy between professional values and perceived operational skills, sug-gesting the need to systematically integrate spirituality and religious diversity into nursing curricula. A structured training approach could strengthen transferable pro-fessional skills and promote truly holistic and person-centred care.

Abstract: Background: Tuberculosis (TB) remains a major public health challenge in many low- and middle-income countries, where socio-economic inequalities continue to undermine treatment success. Structural barriers such as poverty, unemployment, and limited access to healthcare services can disrupt treatment adherence and contribute to poor outcomes. While biomedical interventions remain central to TB control, there is growing recognition that community engagement strategies may strengthen TB management. This study examined the influence of socio-economic determinants on TB treatment outcomes and explored the potential contribution of community engagement interventions to improving TB care in rural settings. Methods: A retrospective quantitative analysis was conducted using a dataset of 512 patient records with documented TB treatment outcomes. Descriptive statistics were used to summarise patient characteristics. Multivariable logistic regression was applied to identify socio-economic determinants associated with unsuccessful treatment outcomes. Scenario-based predictive modelling and marginal effects analysis were then used to estimate the potential impact of integrating community engagement mechanisms, including community health worker outreach, peer support networks, and community-based health education. Results: Overall, 79.1% of patients achieved successful treatment outcomes, while 17.0% experienced unsuccessful outcomes. Social vulnerability was strongly associated with poor treatment outcomes (AOR = 1.8; 95% CI: 1.2–2.6). Unemployment (AOR = 1.6; 95% CI: 1.1–2.3) and unstable income sources (AOR = 1.5; 95% CI: 1.0–2.2) were also significant predictors of unsuccessful outcomes. Predictive modelling suggested that integrating community engagement interventions could reduce the predicted probability of unsuccessful treatment outcomes from 17% to approximately 10%. Interaction analysis further indicated that the greatest improvements occurred among patients with high socio-economic risk. Conclusion: Socio-economic vulnerability remains a critical determinant of TB treatment outcomes. Integrating community engagement strategies, particularly community-based health education and patient support mechanisms, may improve treatment adherence and reduce unsuccessful outcomes, especially among socially disadvantaged populations. Strengthening community participation in TB programmes may therefore represent an important pathway toward more equitable and effective TB control. Keywords: tuberculosis; community engagement; socio-economic determinants; treatment outcomes; health education; rural health; predictive modelling.

Abstract: Functional information measures how rare functional configurations are. Wong and colleagues argue that selection should drive a law of increasing functional information. This is often read as a claim that complexity must increase. Here I give a different interpretation, which is that survivors tend to be the systems that did not overcommit. I model a system as a policy π, meaning a bundle of commitments expressed in a finite embodied vocabulary. New selection pressures arrive as a set of future requirements drawn from the unobserved outcome set U. A currently viable policy leaves an unobserved buffer B_π ⊆ U of outcomes it still permits. Under a maximally ignorant novelty model, the survival probability of π is exactly 2^{|B_π| − |U|}. Under any exchangeable novelty prior, survival remains monotone in B_π. So persistence under novelty favours weak policies, where weakness counts the compatible completions left open. I define degree of future function as survival probability and functional information as Hazen and Szostak rarity within the currently viable set. Conditioning on persistence reweights the viable set toward larger buffers and therefore toward higher functional information. This yields a mathematical analogue of the proposed law under explicit assumptions. Supplementary analysis quantifies how much structured novelty is needed before that buffer size ordering can reverse. In fully enumerated toy worlds, weakness maximisation improves mean log survival probability relative to random choice. Weakness and simplicity are not the same thing. Weakness helps a system persist under novelty, because it keeps more futures compatible. Simplicity helps a system persist because there is less to break, which obviates the need for repair. Complexity requires self-repair to persist, increasing weakness. Life is persistent complexity. In between complex life and simple nonlife is the void of the unviable: complexity which is not alive.

Abstract: Open-pit mining relies heavily on visual inspection to identify indicators of slope instability such as surface cracks. Early identification of these geotechnical hazards allows for the implementation of safety interventions to protect both workers and assets in the event of slope failures or landslides. While computer vision (CV) approaches offer a promising avenue for autonomous crack detection, their effectiveness remains constrained by the scarcity of labelled geotechnical datasets. Deep learning (DL) models require large amounts of representative training data to generalize to unseen conditions; however, collecting such data from operational mine sites is limited by safety, cost, and data confidentiality constraints. To address this challenge, we propose a hybrid game engine—generative artificial intelligence (AI) framework for large-scale dataset synthesis. Leveraging a parameterized virtual environment developed in Unreal Engine 5 (UE5), the framework captures realistic images of open-pit surface cracks and enriches their visual diversity using StyleGAN2-ADA. The resulting datasets were used to train the YOLOv11 real-time object detection model and evaluated on a real-world dataset of open-pit slope imagery to assess the effectiveness of the proposed framework in improving CV model generalizability under extreme data scarcity. Experimental results demonstrated that models trained on the proposed framework substantially outperformed the UE5 baseline, with average precision (AP) at intersection over union (IoU) thresholds of 0.5 and [0.5:0.95] increasing from 0.403 to 0.922 and 0.223 to 0.722 respectively, accompanied by a reduction in missed detections from 95 to eight for the best-performing configurations. These findings demonstrate the potential of hybrid generative AI frameworks to mitigate data scarcity in CV applications and support the development of scalable automated slope monitoring systems for improved worker safety and operational efficiency in open-pit mining.

Abstract: Background/Objectives: Heart rate variability (HRV) and ventricular repolarization parameters are non-invasive markers of cardiac autonomic regulation and electrical stability. Although these parameters un-dergo significant maturational changes during childhood, normative data and their physiological interac-tions in healthy pediatric populations remain insufficiently explored. This study aimed to evaluate the rela-tionship between HRV and ventricular repolarization indices (QT, QTc, QTd, QTcd) in healthy children and to establish age-stratified normative reference values for HRV parameters across four distinct age groups. Methods: This cross-sectional study included 254 healthy children (145 males, 57.1%; mean age 12.51 ± 3.55 years, range 5–18 years). All participants underwent 24-hour ambulatory electrocardiographic (Holter) monitoring. HRV parameters (SDNN, SDANN, RMSSD, pNN50, LF, HF, and LF/HF ratio) and ventricular repolarization indices (QT, QTc, QTd, QTcd) were derived. Participants were stratified into four age groups: 5–8, 9–12, 13–15, and 16–18 years. Normative percentile distributions (5th–95th) were generated for all HRV parameters. Results: Significant maturational increases were observed in all time- and frequency-domain HRV parame-ters across the four age groups (p < 0.001), accompanied by a decline in heart rate (r = -0.471, p < 0.001). The uncorrected QT interval showed strong positive correlations with all HRV indices, particularly SDNN (r = 0.434, p < 0.001) and RMSSD (r = 0.426, p < 0.001), while heart rate correction (QTc) attenuated these associations. Repolarization heterogeneity (QTd) correlated significantly with SDNN (r = 0.269, p < 0.001) and HF (r = 0.186, p = 0.004). Females exhibited significantly higher QTc values (r = 0.294, p < 0.001) and lower mean HRV values compared to males. Multivariate regression identified sex as the only significant independent predictor of QTc (β = 0.294, p < 0.001). Conclusion: Cardiac autonomic modulation, as reflected by HRV, significantly influences ventricular re-polarization dynamics in healthy children. The age-specific normative percentile charts established in this study provide a robust physiological reference for pediatric cardiac autonomic and electrophysiological assessment, facilitating improved clinical interpretation and arrhythmic risk stratification in children and adolescents.

Abstract: Certain integer transformations exhibit unexpected forms of stability that resemble attractors in dynamical systems. Two classical examples are the Kaprekar transformation leading to the constant 6174 and the arithmetic structure of perfect numbers. Although traditionally studied in separate areas of number theory, both phenomena reveal a common feature: the emergence of stable configurations under discrete informational constraints. In this work, we propose a unified framework based on Viscous Time Theory (VTT) and its informational geometry perspective, in which these two structures are interpreted as complementary forms of arithmetic stabilization. The Kaprekar transformation defines a discrete dynamical system whose iterations rapidly converge to a unique attractor (6174) for almost all four-digit inputs. Perfect numbers, on the other hand, arise as equilibrium points of the divisor-sum operator, where the informational deviation between a number and the sum of its proper divisors vanishes. We formalize both mechanisms using a common representation based on discrete informational tension functions defined over the integers. Within this framework, Kaprekar collapse appears as a dynamic attractor produced by iterative dissipation of digit-configuration tension, while perfect numbers correspond to static coherence wells generated by structural balance in the divisor field. Numerical exploration further suggests the presence of near-equilibrium zones—arithmetic configurations where informational gradients become locally minimal. These structures provide a natural bridge between iterative attractors and divisor-based equilibria, suggesting that stability phenomena in number theory may be understood through a broader lens of informational relaxation processes. The results do not claim new proofs regarding perfect numbers, but instead propose a conceptual and computational framework that unifies dynamic and structural stability in arithmetic systems. This perspective may provide new tools for exploring discrete attractors, divisor dynamics, and informational structures within number theory.