Abstract: The calibrated model reproduced the overall trend of specimen-to-specimen mechanical variation observed experimentally. Predicted stiffness values were in reasonable agreement with measured data. Fracture force predictions showed moderate agreement for dynamically tested specimens (R² = 0.60), which improved to R² = 0.88 after exclusion of one statistically identified outlier. Compared with a purely linear elastic formulation, the proposed viscoelastic model demonstrated modest improvement in stiffness prediction and more substantial improvement in fracture force prediction. These findings indicate that incorporating density-dependent viscoelastic effects improves representation of vertebral mechanical behavior, particularly at higher loading rates. Owing to its simplicity and computational efficiency, the proposed model requires only limited imaging input and may be useful for future biomechanical investigations, rapid screening, and injury risk prediction.

Abstract: Purpose: Next-generation sequencing (NGS) is routinely used in the diagnostic workup of neurological diseases, enabling systematic screening for SMA with tailored bioinformatic tools, further enhancing diagnostic speed and accuracy. Methods: We leveraged SMNCopyNumberCaller, SMAca, and SMAFinder in our NGS cohort (n = 3493), including 74 MLPA-validated SMA cases (one compound heterozygous) in the exome dataset. Putative SMA cases were validated using PCR-RFLP and MLPA. Results: With default settings of SMA Finder in exome cohort (n = 2437), 16.4% of samples were uncallable including 40 known SMA cases. Lowering read thresholds markedly improved callability and identified 71/73 known SMA cases, two cases remaining uncallable. SMAca correctly detected 73/73 SMA cases. Both tools had a positive predictive value of 100% and identified two missed cases (DM1, MND), subsequently molecularly confirmed. After inclusion of correction value to scale factor, SMAca showed high concordance with MLPA for SMN2 copy number estimation in SMA cases. Carrier frequencies were estimated as 1:36 and 1:47, in genome and exome respectively. Using SMNCopyNumberCaller, we provided detailed SMN profiling in a Turkish genome cohort (n = 1056). Conclusions: NGS-based SMN analysis enables robust detection of SMA and supports systematic cohort screening to identify missed cases.

Abstract: This study investigates the regularity of the three-dimensional (3D) incompressible Navier-Stokes equations (NSE) for plane Couette flow, a canonical shear-driven flow model with a well-defined laminar-turbulent transition threshold. Employing Sobolev space theory and the Energy-Velocity Monotonicity Principle (EVMP), we rigorously prove that no global smooth solutions exist as the Reynolds number exceeds the critical value \( Re_{cr} \). Prior studies have revealed that a zero velocity gradient on the velocity profile is the necessary and sufficient condition for turbulence generation in 3D plane Couette flow, yet they lack mathematical theoretical proof from the perspective of partial differential equation framework. This study fills this gap via velocity decomposition and singularity analysis. We show that nonlinear disturbance amplification induces local cancellation of mean and disturbance velocity gradients, triggering finite-time singularity formation in flow field, which leads to the breakdown of regularity of the 3D NSE and thus the non-existence of global smooth solutions. It is emphasized that the non-existence of smooth solutions is due to the local regularity breakdown of solutions instead of the velocity blow-up. Further, it is important that the critical condition for regularity breakdown obtained through Sobolev space analysis accords with the critical condition for turbulence onset obtained through experiments and simulations.

Abstract: Partial metrics have shown to be useful dissimilarity measures when incomplete information, partial states, or inherent uncertainty is involved. The main characteristic of this kind of distances is allowing non-zero self-distances. This distinctive property makes them particularly appropriate for applications to computer science, artificial intelligence, pattern recognition and bioinformatics. Nevertheless, in these fields it is often more relevant to quantify the amount of shared information between objects rather than their dissimilarity. In this context, similarity metrics have proven to be a valuable tool. The literature has suggested the existence of a duality relationship between partial metrics and similarity metrics. In this paper we investigate such a relationship. Specifically, we focus on identifying the properties of functions that induce a similarity metric from a partial metric in the sense of O’Neill. We provide a characterization of these functions, showing that they coincide with the class of strictly decreasing and convex functions on the set of non-negative real numbers. We also show that these functions preserve the topology and the partial order, that is, the partial order and topology generated by the induced similarity metric and by the original partial metric are the same. Besides, we characterize the class of functions capable of generating an O’Neill partial metric from a similarity metric showing that such a class is formed by strictly decreasing and concave functions on the set of real numbers. In this case we also show that the partial orders and the topologies generated by the induced partial metric and by the original similarity metric coincide. The results are supported and clarified by appropriate examples.

Abstract: Nano-engineering strategies have been increasingly applied to enhance the biological performance of calcium silicate–based materials; however, the optimal concentration of nano-hydroxyapatite (HANP) remains unclear. This study evaluated the bone-healing response to different concentrations of HANP incorporated into mineral trioxide aggregate (MTA) and bioceramic (BC) sealers in an experimental rabbit model. Thirty adult New Zealand white rabbits were allocated into two experimental groups according to sealer type: HANP-modified MTA and HANP-modified BC (n = 15 each). Two standardized circular intrabony defects were created bilaterally in the maxillary diastema of each rabbit. In the MTA group, the right-side defects were filled with 2% and 4% HANP-modified MTA, while on the left side one defect received 6% HANP-modified MTA and the adjacent defect was left as control. The same protocol was followed for the BC group using corresponding HANP concentrations. Five rabbits per group were sacrificed at 2, 4, and 8 weeks postoperatively for histopathological hematoxylin and eosin (H&E) and Masson trichrome staining. The results demonstrated significant differences among groups at all-time points, with 4% HANP showing the most favorable biological response, including reduced inflammatory cell infiltration, increased new bone formation, and improved collagen organization compared with lower and higher concentrations. Pairwise comparisons at matched HANP concentrations revealed no statistically significant differences between HANP-modified MTA and BC groups. These findings indicate that HANP incorporation enhances the biological performance of calcium silicate–based sealers in a concentration-dependent manner, with 4% representing an optimal formulation for promoting bone regeneration.

Abstract: Additive manufacturing is moving towards the use of machines with five or more axes but is limited by the inability to easily generate print paths. This usually requires the creation of custom G-code in order to utilize five-axis printing. However, as additive manufacturing begins to utilize five-axis printing for scenarios such as repair, modification, or composite printing, the existing print surfaces become potential obstacles that need to be accounted for in path planning. This paper shows a novel way of expanding the capabilities for printing on complex, concave parts, in order to prevent collisions between the printer and the part. This is achieved through two main steps: Area Refinement, and Angle Determination. During Area refinement, the proposed print area is altered based on the geometry of the print surface, along with printer parameters. This results in a print region that is feasible with the given machine configuration and geometry, that will not attempt to print too close to any existing surface in the presence of concavities. During Angle Determination, the finalized print paths are adjusted to set a nozzle orientation that prevents the machine from colliding with the part. In this paper, we present the algorithmic details behind these approaches and show computational results for two complex concave geometries.

Abstract: This study introduces new classes of fuzzy open sets, namely (p,q)-FΩ-open (resp. (p,q)-FΩP open, (p,q)-FΩS-open, (p,q)-FΩα-open, and (p,q)-FΩγ-open) sets in double fuzzy topological spaces (DFTSs) in view of Šostak. We conduct a detailed investigation of the relationships among these classes of open sets, supported by carefully constructed illustrative examples. Furthermore, we propose and characterize the associated DFΩ-interior and DFΩ-closure operators. Subsequently, we define and analyze new classes of fuzzy functions based on (p,q)-FΩ-open sets, referred to as DFΩ-continuous and DFΩ-irresolute functions within the framework of DFTSs (S,ϑ,ϑ^∗) and (Z,ζ,ζ^∗). We also introduce the notions of DFΩP-continuous, DFΩS-continuous, DFΩα continuous, and DFΩγ-continuous functions, which constitute weaker forms of DFΩ-continuity. As an application, we demonstrate that these newly defined continuity concepts generalize, extend, and unify several existing results in the theory of DFTSs. Finally, we propose and discuss the concepts of DFAΩ-continuity and DFWΩ-continuity as additional weaker variants of DFΩ-continuity. Moreover, we establish new separation axioms, termed (p,q)-FΩ-normal and (p,q)-FΩ-regular spaces, formulated via (p,q)-FΩ-closed sets.

Abstract:

Background: The local twitch response (LTR) elicited during ultrasound-guided fascial hydrorelease (FHR) is conventionally attributed to dysfunctional motor endplates. However, in a related observational paper under concurrent submission, 89/89 evaluable archived LTR events were observed within stacking fascia at sites incompatible with direct endplate excitation. Hypothesis: We propose the Fascial Capacitor Model: stacking fascia functions as a multilayer biological capacitor in which collagen sublayers act as electrodes and the interposed densified hyaluronic-acid (HA)-rich loose layer acts as the dielectric, with the LTR reinterpreted as a transient electrophysiological discharge when a needle bridges its layers. This biophysical model is explicitly grounded in the established molecular and histological architecture of human deep fascia. Supporting evidence: Each premise is independently supported by primary literature from at least eight research lines spanning roughly seventy years. Voltage gap: The apparent gap between estimated bulk discharge voltages and motor neuron threshold is resolved by reconsidering needle-tip geometry and stimulation modality, anchored by the ±6 V triboelectric measurements of Ouyang et al. (2022). Implications: The model is the immediate-phase complement to the Fascial Memory Reset Hypothesis (Int J Mol Sci 2026, 27, 3720), explains intra-procedural symptom relief, and yields falsifiable predictions. A direct empirical validation programme using insulating-needle SEA recording is in preparation at the corresponding author’s institution.

Abstract: This paper examines whether digital skill requirements in educational job postings are associated with higher advertised salaries in the labor markets of Almaty and Astana, Kazakhstan, and whether the observed salary gap reflects genuine skill valuation or employer heterogeneity. Using 794 vacancies collected via the HH.kz API, we construct an analytical sample of 755 observations after data cleaning. A seven-category dictionary-based skill extraction pipeline is implemented and its integral lexical consistency is evaluated against a TF-IDF+Logistic Regression baseline (5-fold CV: F1=0.755, AUC=0.928). Vacancies specifying at least one digital requirement carry a median advertised salary that is 18.2% higher than non-digital postings. OLS with HC3- robust standard errors and occupational and city controls yields a coefficient of 0.200 (SE = 0.039, p< 0.001, approximately +22.2%). Adding an employer-type proxy reduces this estimate to +15.2% (p < 0.001). In the Almaty subsample, the effect is no longer statistically significant (p = 0.075). Part of the observed premium reflects a measurement problem. Higher-paying employers are also more likely to specify digital requirements, inflating the estimated association. The design does not identify firm effects and supports only an associational interpretation. Quantile regression shows that the salary-digital gradient increases from +15.0% at Q25 to +44.4% at Q90. This pattern is consistent with labor market segmentation rather than a uniform skill premium.

Abstract: In this study the development of sustainable electrocatalysts for clean energy by modifying biomass-derived activated carbon with nitrogen and transition metals is presented. Activated carbon (AWC) was synthesized using alder wood char as a precursor, while nitrogen and cobalt or copper nanoparticles were incorporated with the aim to create efficient materials for hydrazine oxidation (HzOR) and direct hydrazine-hydrogen peroxide fuel cells (DHHPFC, N2H4–H2O2). The composition, structure, and surface morphology of the created catalysts were examined using inductively coupled plasma optical emission spectroscopy (ICP-OES), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and scanning electron microscopy and energy dispersive X-ray analysis (SEM/EDX). The activity of the AWC, AWC–Co–N, and AWC–Cu–N catalysts for HzOR was evaluated by cyclic voltammetry (CV) and linear sweep voltammetry (LSV). N2H4–H2O2 fuel cell tests were carried out by employing the catalysts both as the anode and cathode. It was found that all materials retained a hierarchical porous carbon framework, while metal incorporation altered surface compactness Cobalt doping produced well-dispersed Co nanoparticles and abundant Co–N–C coordination sites, whereas Cu introduction resulted in moderately compact structures with uniformly distributed Cu-based nanoparticles. Electrochemical measurements demonstrated that both metal dopants enhanced HzOR activity, with the catalytic performance following the order AWC–Co–N &gt; AWC–Cu–N &gt; AWC. Fuel-cell testing further confirmed this trend: AWC–Co–N achieved the highest maximum power density (30.4 mW cm–2), outperforming AWC–Cu–N (17.7 mW cm–2). These results identify AWC–Co–N as a highly effective bifunctional electrocatalyst for DHHPFCs.

Abstract: Background/Objectives: Intubation and tracheostomy were previously considered dis-tinct approaches to airway management during mechanical ventilation. Ventila-tor-associated pneumonia (VAP) remains a leading cause of morbidity and mortality in patients requiring prolonged mechanical ventilation. The role of tracheostomy in modify-ing VAP risk is controversial, especially when taking into account how exposure changes over time and the conditions typically found in real intensive care unit (ICU) settings. This study was conducted to evaluate whether tracheostomy timing influences the VAP risk and hospital length of stay in patients undergoing prolonged mechanical ventilation. Methods: We conducted a hybrid case–cohort study in a tertiary-care ICU in Mexico City, enrolling patients receiving invasive mechanical ventilation for ≥ 48 h (January–December 2023). Patients undergoing a tracheostomy were compared with an age- and sex-matched subcohort of intubated patients. VAP incidence was evaluated using cumulative incidence and incidence density. Multivariable generalized linear models, Kaplan–Meier survival analysis, and Cox regression were used to identify risk factors and assess time-to-event outcomes. Results: A total of 218 patients were included (55 tracheostomies vs. 163 intu-bations). The incidence density of VAP was similar between groups (31.5 vs. 30.3 per 1000 ventilator-days; RR 1.04, 95% CI 0.7–1.7). However, cumulative incidence was higher in tracheostomized patients (61.8% vs. 22.7%; RR 2.7, 95% CI 1.9–3.9), reflecting prolonged exposure. Independent risk factors included broad-spectrum antibiotics, mechanical ven-tilation ≥ 5 days, chronic pulmonary disease, and ICU stay. In contrast, tracheostomy was associated with a lower time-dependent hazard of VAP (HR 0.43, 95% CI 0.25–0.75). Gram-negative microorganisms predominated, with higher antimicrobial resistance in tracheostomized patients. A class-based analysis showed that MDR was primarily driven by E. coli, with consistent resistance to cephalosporins and fluoroquinolones. The MAR index was higher in tracheostomized patients (0.50 vs. 0.25), indicating a greater burden of antimicrobial resistance. Conclusions: Tracheostomy increases cumulative VAP inci-dence due to longer exposure but is associated with a reduced time-dependent risk. These findings highlight the importance of accounting for exposure time and support targeted strategies integrating airway management and antimicrobial stewardship to reduce VAP burden in real-world ICU settings.

Abstract: Aiming at the non-stationary and slowly varying stochastic nature of bearing degradation from normal operation to failure, this paper proposes a fratcional Generalized Cauchy (fGC) prediction model with 1/f process and dual parameters: fractal dimension and Hurst exponent. First, 1/f process sequences exhibit long-range dependence and power-law characteristics. Next the fGC degradation model is established, and the Hurst exponent and fractal dimension are calculated using the R/S method and box-counting dimension method, respectively. Then a dimensionless jump descriptor is employed as a Health Indicator to detect incipient faults and estimate degradation parameters. The maximum likelihood algorithm method is applied to parameter estimation. Finally, a experiment verifies the satisfactory prediction performance through compared with CNN and LSTM predicting model.

Abstract: Titanium-based dental implants have evolved significantly, with the development of binary alloys like Ti-15Zr (Roxolid™) representing a pivotal advancement in mechanical performance. Current research focuses on biomimetic surface engineering to further accelerate osseointegration and optimize bone regeneration, particularly in clinically compromised sites. This review constitutes a narrative synthesis of how these strategies replicate the bone extracellular matrix (ECM) through a holistic framework of architectural, mechanical, and biochemical integration. A structured literature search across PubMed, Scopus, and Web of Science (2010–2026) identified relevant studies focusing on the synergy between Ti-15Zr substrates and surface modifications. Evidence confirms that the high fatigue strength of Roxolid™ alloys provides an ideal foundation for advanced, hierarchical surface engineering without compromising structural integrity. This strategy utilizes macro-topography for primary stability, nano-topography for protein adsorption, and bio-functionalization (e.g., RGD peptides, osteogenic ions) to direct mesenchymal stem cell (MSC) differentiation. This synergy accelerates the transition from passive to active osseointegration, effectively bridging the "biological gap" during early healing. Biomimetic engineering transforms implants into instructive biological platforms, improving outcomes for patients with compromised bone quality and facilitating predictable immediate loading protocols.

Abstract: The k-nearest neighbor (KNN) algorithm remains one of the most fundamental and widely-used methods in machine learning. A common rule of thumb sets the number of neighbors as k = √n, where n is the size of the training set. Despite its widespread adoption, the theoretical justification for this choice has remained obscure. We provide a comprehensive rate-based analysis. First, we derive the minimax-optimal exponent β★ = 4/(d+4) for k = n^β under standard Hölder-smoothness assumptions, recovering as a special case Theorem 1: k = √n is minimax-optimal if and only if the feature space has dimensionality d = 4. Second, Theorem 2 quantifies the sub-optimality of any fixed β as R_n(n^β) = Θ(n^(−r(β,d))) with r(β,d) = min{β, 4(1−β)/d}, yielding an asymmetric penalty for the classical rule when d ≠ 4 that we make precise in Corollary 1. The predicted rate is empirically verified across d ∈ {2,…,20} on controlled synthetic data. On 48 datasets from the OpenML-CC18 benchmark suite, the dimension-aware rule k = ⌊n^(4/(d+4))⌋ outperforms the classical √n rule in 32 of 48 head-to-head comparisons (paired Wilcoxon p = 4.6 × 10⁻⁴, mean accuracy gain +2.5 percentage points), demonstrating that the theoretical improvement translates to a practical one. We further test the Hassanat distance metric against Euclidean across all KNN variants on the same 48 datasets, finding that Hassanat outperforms Euclidean in five of six configurations (paired Wilcoxon p < 0.05), with the largest gains on unstandardized data. Cross-validation remains the strongest k-selection strategy when computationally feasible, and the theoretical results provide a principled non-cross-validated alternative.

Abstract: Automated diabetic retinopathy (DR) screening has achieved expert-level accuracy, yet clinical adoption remains limited by the opacity of deep neural networks. We address this gap with a DenseNet121-based binary classifier trained on 3,662 retinal fundus images from APTOS 2019, optimised through a two-phase transfer-learning and fine-tuning strategy with focal loss and class-balanced sampling. The model achieves 95.45% test accuracy, an AUC-ROC of 0.9881, sensitivity of 93.91%, and specificity of 95.94%. To make these predictions interpretable, we integrate and systematically benchmark six complementary explainable AI (XAI) techniques drawn from three theoretical families: perturbation (Occlusion Sensitivity, LIME, RISE), gradient (Integrated Gradients), and activation-based (Grad-CAM++, Score-CAM). Each method is evaluated on processing time, memory footprint, and agreement with expert-annotated anatomical structures. The six methods converge on clinically meaningful regions, including the optic disc (85% average agreement), major vessels (78%), and macula (66%), indicating that the network's decisions are grounded in established DR pathology rather than spurious correlations. Statistical tests (DeLong, McNemar, bootstrap with 10,000 resamples) confirm significant gains over standard CNN baselines. The framework demonstrates that strong screening performance and clinical interpretability can be jointly achieved, providing a deployment-ready template for DR decision support.

Abstract: Chronic Mycobacterium tuberculosis (M.tb) infection reflects failure of sterilizing immunity and persistent pulmonary bacterial burden. While CD4+ T cells and IFN-γ are central to protection, the role of CD8+ T cells in chronic disease remains unclear. This study examined whether CD8+ T cells contribute to immune dysregulation during chronic tuberculosis through IL-10 production. Susceptible CBA/J and resistant C57BL/6 mice were infected with a low-dose aerosol of M.tb Erdman and followed for 150 days. Lung bacterial burden, cytokine responses, and T-cell populations were assessed using high-purity CD8+ T-cell isolation (>97%), ELISA, ELISPOT, and in vivo CD8+ depletion. In susceptible CBA/J mice, chronic infection was associated with progressive pulmonary accumulation of CD8+ T cells, reduced CD4:CD8+ ratios, increased IL-10 levels, and impaired bacterial control. Antigen-experienced CD8+ T cells were a major source of IL-10, which correlated with reduced IFN-γ responses and higher bacterial burden. CD8+ depletion during chronic infection was associated with reduced bacterial burden and increased IFN-γ responses. Resistant C57BL/6 mice showed limited expansion of IL-10-associated CD8+ responses and better bacterial control. These findings support a model in which chronic M.tb infection is associated with expansion of IL-10-producing CD8+ T cells in susceptible hosts and altered immune control. CD8+ T-cell modulation during chronic disease is associated with changes in bacterial burden, suggesting a contributory role in disease outcome. These results highlight CD8+ T-cell functional polarization as a factor to consider in tuberculosis pathogenesis and vaccine design.

Abstract: Small and medium enterprises (SMEs) in the entertainment sector face significant challenges managing seat assignments through manual processes that are error-prone and time-consuming. This paper presents an intelligent agent-based system that automates seat assignment while providing natural language support for operational staff. The system integrates a large language model (Gemini 2.5 Flash) for conversational interaction with a constraint-based optimization algorithm that considers capacity, accessibility, revenue, and business priorities. A fuzzy matching engine combining spaCy with the fuzzy string matching library FuzzyWuzzy consolidates duplicate reservations from multiple channels. The cloud-based architecture leverages AWS serverless services (Lambda, Fargate) with PostgreSQL for data management. Technology Readiness Level 4 (TRL4) validation demonstrated 94% precision in duplicate detection, successful assignment of 87% of reservations with 82% average capacity utilization, and effective natural language query handling. The system reduces manual processing time by 65% while improving assignment quality through systematic enforcement of constraints. This work demonstrates the feasibility of AI-powered operations management for resource-constrained SMEs, offering a practical reference architecture combining conversational AI with algorithmic optimization.

Abstract: Traditional biomechanical research has focused on joint mechanics and the be-havior of the center of mass (CoM); however, the dynamics of the center of pressure (CoP) and the neuromuscular strategies that support stability under load remain un-derexplored. This study examined balance control during the back half squat by ana-lyzing the relationship between the CoM and the CoP in five experienced male weightlifters performing segmented squats at five load levels (20–80% 1RM). Vicon force platforms and motion capture systems were used to quantify the area of the 95% confidence ellipse. Due to the small sample size (n = 5), a dual inferential framework was used: frequentist repeated-measures ANOVA supplemented with unified adaptive Bayesian hierarchical modeling. The phase of the motion showed a strong effect on the stability of the CoP in both frames (frequentist: F(1.65, 6.59) = 19.44, p = 0.002, ηp² = .829; Bayesian: P(β_phase2 < 0) > 0.999). The external load was not significant in the frequentist analysis (p = 0.177), but the subsequent Bayesian analysis gave moderate evidence of a positive load effect (β_load = 0.059, 95% HDI [0.005, 0.115], P=0.981). The area of the CoM ellipse did not show significant effects in either frame. Limb asym-metries were substantial and stable (frequentist: 48.01 ± 30.13%; Bayesian: 69.48%, 95% HDI [55.86%, 81.44%], P(AI > 20%) = 1.000), with no condition-dependent modulation. CoP-CoM coupling was stronger in the mediolateral than the anteroposterior direction in both frames. These results suggest that phase is the main factor influencing pressure point stability, that loading may have a moderate positive effect detectable only with low-power probabilistic techniques, and that the dual framework improves the ro-bustness of conclusions in biomechanical research with small samples. Confirmatory studies with larger sample sizes are needed.

Abstract: Time-restricted feeding (TRF) has emerged as a promising intervention to improve metabolic health and promote healthy aging, yet the cellular mechanisms underlying its effects remain incompletely understood. Here, we applied imaging-based and quantitative cellular analyses to investigate how TRF modulates aging-associated and neurodegeneration-related phenotypes in vitro. Human fibroblasts and AC16 cardiomyocytes were used as models of cellular aging, alongside fibroblast-based models of neurodegeneration. TRF was simulated through cyclic nutrient availability, and cellular responses were evaluated using microscopy-based assessment of cellular morphology, senescence-associated features, metabolic state, and circadian rhythm-associated gene expression dynamics. Imaging analyses demonstrated that TRF modulated key hallmarks of cellular senescence, including changes in cell morphology and intracellular organization, consistent with enhanced cellular resilience and altered metabolic adaptation. In AC16 cardiomyocytes, TRF influenced aging-associated cellular phenotypes, indicating that its effects extend beyond proliferative cell systems to cardiac-relevant models. In neurodegeneration-associated fibroblast models, TRF altered disease-related cellular signatures and stress-associated phenotypes, supporting a potential protective role in neurodegenerative conditions. Quantitative analyses further revealed significant TRF-induced changes in circadian rhythm characteristics across all models, including altered oscillatory amplitude, supporting a mechanistic link between nutrient timing and cellular timekeeping. Together, these findings demonstrate that TRF induces measurable changes in cellular architecture and circadian regulation associated with improved aging- and neurodegeneration-related phenotypes. This work highlights the utility of imaging-based approaches for investigating the spatiotemporal cellular effects of metabolic interventions and supports TRF as a potential therapeutic strategy for age-associated diseases.

Abstract: The southern coast of Java, Indonesia, lies along the active Sunda subduction margin, where coastal landforms record the interaction between sea-level change, wave erosion, sedimentation, and tectonic uplift. Marine terraces and raised coastal surfaces are important geomorphic indicators of vertical deformation, but their interpretation remains difficult where chronological control is limited and where coastal surfaces have been modified by erosion, deposition, karstification, or human activity. This study presents new Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) topographic profiles from four coastal sites: Pantai Ajah, Kalijali, Kulon Progo, and Wingko. The profiles were measured from the beachward side toward the landward side and were used to identify terrace treads, risers, slope breaks, residual topographic highs, and possible raised coastal platforms. These field data are integrated with published information on Holocene sea-level change, marine terraces, coastal uplift, and forearc deformation along the southern Java margin. The RTK profiles show variable terrace morphology between sites. Pantai Ajah preserves a prominent riser and a probable terrace tread at approximately 7–8.5 m elevation. Kalijali records a lower terrace-like surface at approximately 4–5 m, an upper surface at approximately 7–9 m, and a higher local topographic high near 12–13 m. Kulon Progo shows a subdued low-elevation raised coastal surface, while Wingko contains a distinct slope break at approximately 1450–1500 m from the beachward end and a broad landward surface at approximately 5–6.5 m elevation. The profiles suggest two tentative morphostratigraphic terrace groups: a lower group at approximately 4–6.5 m and an upper group at approximately 7–9 m. Higher local peaks, including the 12–13 m high at Kalijali and comparable elevated points at other sites, may represent remnants of older or more strongly uplifted coastal features. One possible interpretation is that some of these higher surfaces originated near the mid-Holocene sea-level highstand, when relative sea level in parts of Indonesia and Sundaland was higher than present, and were subsequently uplifted to different elevations according to local uplift rates. However, this hypothesis requires direct chronological and sedimentological confirmation. The raised terrace ridges and topographic highs may also act as partial natural barriers that reduce tsunami flow penetration inland, although they should not be treated as complete protection. Overall, RTK profiling provides a useful field method for recognizing coastal terrace morphology and identifying priority sites for future dating, tsunami-inundation modelling, and coastal-hazard planning.