Search Results (15,074)

Asia presently houses some of the top and dynamic economies in the world. These economies have also experienced high fintech adoption in their banking sectors. This paper examines the impact of fintech adoption and integration on the efficiency and stability of banks in 9 Asian countries, using panel data from 85 banks spanning 11 years from 2014 to 2024. It first analyzes the impact of fintech on banks across all selected countries and then, on a stratified basis, divides them into three categories: developed economies, large economies, and emerging countries. The paper uses non-performing loan (NPL) and provision for loan losses (PLLs) as proxies for risk, efficiency ratios, and the cost-to-income ratio as efficiency measures, and the stability ratio and Z-score as indicators of stability. To estimate the results, it has applied ordinary least squares and fixed-effect techniques. The study finds that fintech adoption reduces associated bank risk, presents mixed effects on efficiency, and strongly supports bank stability. Moreover, total assets and ROA consistently demonstrate lower risk, higher efficiency, and greater stability. Overall, the results of this study indicate that fintech encourages greater competition, leading banks to lend more aggressively and, consequently, increasing NPLs, PLLs, and overall risk exposure. Based on the findings, this research suggests that policymakers may adopt fintech strategies to maximize the benefits. Full article

The microscopic origin of the de Sitter entropy remains a central puzzle in quantum gravity that is related to the cosmological constant problem. Within the paradigm of $\mathcal{H}$olographic $\mathcal{N}$aturalness, we propose that this entropy is carried by a vast number of light, coherent degrees of freedom—called “hairons”—which emerge as the moduli of gravitational instantons on orbifolds. Starting from the Euclidean de Sitter instanton ($S^4$), we construct a new class of orbifold gravitational instantons, $S^4/{\mathbb{Z}}_N$, where N corresponds to the de Sitter entropy. We demonstrate that the dimension of the moduli space of these instantons scales linearly with N, and we identify these moduli with the hairon fields. A ${\mathbb{Z}}_N$ symmetry, derived from Wilson loops in the instanton background, ensures the distinguishability of these modes, leading to the correct entropy count. The hairons acquire a mass of the order of the Hubble scale and exhibit negligible mutual interactions, suggesting that the de Sitter vacuum is a coherent state, or Bose–Einstein condensate, of these fundamental excitations. Then, we present a novel framework which unifies neutrino mass generation with the cosmological constant through gravitational topology and holography. The small neutrino mass scale emerges naturally from first principles, without requiring new physics beyond the Standard Model and Gravity. The gravitational Chern–Simons structure and its anomaly with neutrinos force a topological Higgs mechanism, leading to neutrino condensation via $S^4/{\mathbb{Z}}_N$ gravitational instantons. The number of topological degrees of freedom $N\sim M_{\mathrm{P}}^2/\mathrm{\Lambda }\sim {10}^{120}$ provides both the holographic counting of the de Sitter entropy and a $1/N$information see-saw mechanism for neutrino masses. Our framework makes the following predictions: (i) a neutrino superfluid condensation forming Cooper pairs below meV energies, as a viable candidate for cold dark matter; (ii) a possible resolution of the strong CP problem through a QCD composite axion state; (iii) time-varying neutrino masses which track the evolution of dark energy; and (iv) several distinctive signatures in astroparticle physics, ultra-high-energy cosmic rays and high magnetic field experiments. Full article

Background: Metabolic syndrome (MetS) is a pathological condition characterized by the co-occurrence of multiple metabolic abnormalities. The affected population is increasingly shifting toward younger age groups. Emerging digital health technologies, arising from advances in digital society, offer novel methodological tools for lifestyle-based interventions targeting metabolic risk. This systematic review aims to evaluate the effectiveness of emerging digital health technologies based on dietary and physical activity regulation in improving MetS-related outcomes among adolescents, including school-aged children. Methods: This review followed the PRISMA guidelines, systematically searched PubMed, Web of Science, Embase, MEDLINE, and Scopus, and screened eligible studies based on the PICO framework. Results: A total of 12 randomized controlled trials published between 2012 and 2025 were included in the analysis. Single device interventions (5/12) and dual device combinations (5/12) were the predominant approaches used in current digital health technology applications. Intervention content primarily focused on either physical activity alone (5/12) or combined exercise and nutrition interventions (7/12), with most programs lasting 3–6 months (7/12). Across the included digital health interventions, 13 MetS-related measures were assessed, including anthropometric/body composition measures (BMI, BMI z-score, WC, WHR, WHtR, and VFA), blood pressure measures (SBP/DBP), and biochemical markers (BG, HOMA-IR, TG, TC, HDL-C, and LDL-C). Conclusions: The available evidence supports the potential of digital health technologies to improve MetS-related outcomes. Although the selection of biochemical markers varied across studies, the findings highlight the importance of combined exercise and nutrition interventions or physical activity of moderate to high intensity in improving MetS. These results underscore the value of digital health technologies in elucidating the complex interactions among diet, physical activity, and metabolic responses. Overall, these findings support integrating digital health technologies into adolescent lifestyle interventions to facilitate more personalized monitoring and behavior support, and to potentially improve MetS-related outcomes. By promoting timely improvements in these outcome measures, such digital health interventions may have potential longer term implications for chronic disease prevention. Full article

This paper presents a breakthrough in activating the skin effect at conventional broaching speeds (1–8 m/min) by using laser defocus gradient modification to induce surface embrittlement in martensitic stainless steel Z10C13. Through controlled defocusing, a 50 μm gradient remelting layer was created, which features ultrafine grains (0.8 μm) and a high-density geometrically necessary dislocation (GND) zone (ρGND = 2.27 μm⁻³). The quasi-cleavage fracture was triggered via dislocation pinning by non-oriented low-angle grain boundaries (28.4% LAGBs). Multiscale characterization confirms that this microstructural transformation enhances surface hardness by 12.95% (reaching 31.4 HRC), reduces cutting force by 34.07%, and improves surface roughness by 63.74% (Sz = 28.80 μm). Simultaneously, a parallel crack-deflection mechanism restricts subsurface damage propagation, resulting in a crack-free subsurface zone. These results demonstrate the effectiveness of the embrittlement–toughening dichotomy for precision machining of difficult-to-cut materials under low-speed constraints. Full article

This study examines how the design and interaction features of AI-powered fintech chatbots shape the customer experience of Generation Z users by integrating the Stimulus-Organism-Response framework with dual-process perspectives. Two cross-sectional surveys were conducted in Türkiye. Study 1 (n = 166) examines the effect of social presence, interactivity, visual appeal, design originality, and usability on perceived competence and perceived warmth, which, in turn, shape the customer experience. Social presence and design originality significantly increased perceived competence (β = 0.47, p < 0.001), while visual appeal enhanced perceived warmth (β = 0.32, p < 0.001). Together, competence and warmth explained a substantial proportion of customer experience (R² ≈ 0.60). Usability and interactivity showed no significant effects. Study 2 (n = 195) replicated these findings with trained users and introduced task complexity as a moderator. Under high task complexity, usability and interactivity became significant predictors of competence, which emerged as the primary driver of customer experience, whereas the influence of warmth diminished. Non-normal data distributions justified the use of Partial Least Squares Structural Equation Modeling. Overall, the findings suggest a shift from heuristic to systematic processing as fintech tasks become more complex, highlighting the growing importance of competence-based evaluations in fintech chatbot interactions. Full article

This investigation provides a comprehensive analytical framework for the topological morphology and global convergence dynamics governing a specific family of sixth-order iterative schemes designed for nonlinear equations with multiple roots. By invoking a Möbius conjugacy transformation upon the specialized polynomial class $f\left(z\right)={\left((z-p)(z-q)\right)}^m$, we project the iterative sequence onto the Riemann sphere $\widehat{\mathbb{C}}$, effectively recasting the algorithm as a discrete complex dynamic system. The core of this study lies in the bifurcation analysis of the associated parameter space. We meticulously chart the stability manifolds, tracing the evolution of critical orbits to distinguish between regions of predictable convergence and those characterized by chaotic instability. By examining the iterative methods generated by these rational endomorphisms, the research unveils the intricate fractal boundaries that delineate the basin of attraction, offering a profound insight into the structural robustness of higher-order methods. In the dynamical plane, the geometry of the basins of attraction is scrutinized to evaluate the robustness of the numerical flow and its sensitivity to the configuration of weight functions. By analyzing the fractal complexity of the boundaries within these basins, we provide a detailed characterization of the iterative morphology and its global reliability. The analytical findings are supported by high-resolution graphical representations and comparative numerical data, illustrating the superior performance and structural integrity of the proposed methods in solving nonlinear problems. Full article

Galeopsis tetrahit L. (Lamiaceae) is a traditional European medicinal species rich in phenolic compounds, among which verbascoside is a key bioactive marker with strong antioxidant potential. This study reports the standardization of a G. tetrahit leaf extract in verbascoside using a fully validated UHPLC–PDA method developed according to ICH Q2(R2) requirements. Leaves of wild-grown G. tetrahit collected from southwest Romania flora were extracted with 70% ethanol, yielding 17.28% dry extract. Chromatographic identification of verbascoside was confirmed by retention time, UV–PDA spectra, and QDa mass spectrometry (m/z 623.3 [M–H]⁻). The method showed excellent performance, including high specificity, linearity over 1.875–60 μg/mL (r = 0.999955), low LOD and LOQ (0.2649 and 0.8028 μg/mL, respectively), and robust precision and accuracy. Dry extract contained 345.8 ± 28.3 mg verbascoside per g (34.6%, w/w), corresponding to approximately 59.8 mg/g in dried leaves. Antioxidant assays (DPPH, ABTS, FRAP), TPC and TFC confirmed notable radical scavenging and reducing activity, with pure verbascoside showing markedly stronger effects, supporting its major contribution to the extract’s antioxidant potential. These results demonstrate a reliable analytical approach and establish a verbascoside-based standardization framework for G. tetrahit extracts of documented Romanian origin. Full article

To overcome the limitations of ground-based observations, this study aims to identify optimal color indices for detecting tree phenological events using time-series Unmanned Aerial Vehicle(UAV) orthomosaics. We monitored 37 woody taxa at the Korea National Arboretum from April to November 2025. By extracting Red, Green, and Blue (RGB) values from canopy polygons, we calculated four indices: Brightness, Green Chromatic Coordinate (GCC), Red Chromatic Coordinate (RCC), and Green-Red Vegetation Index (GRVI). We then evaluated signal detectability using Z-score standardization. The analysis confirmed that 74.6% of phenological events were detectable. Specifically, flowering and autumn coloration showed high detection rates (88.9% and 100%, respectively), identifying Brightness, RCC, and GRVI as key indicators for capturing these distinct visual changes. Conversely, gradual transitions like leaf-out showed lower detectability. These findings demonstrate that selecting specific color indices based on the visual characteristics of each event enables effective quantitative monitoring. This study provides a methodological basis for utilizing UAV-based indices as a complementary tool in long-term ecological monitoring. Full article

Feature extraction and description are fundamental components of visual perception systems used in applications such as visual odometry, Simultaneous Localization and Mapping (SLAM), and autonomous navigation. In resource-constrained platforms, such as Unmanned Aerial Vehicles (UAVs), achieving real-time hardware acceleration on Field-Programmable Gate Arrays (FPGAs) is challenging. This work demonstrates an FPGA-based implementation of an adaptive ORB (Oriented FAST and Rotated BRIEF) feature extraction pipeline designed for high-throughput and energy-efficient embedded vision. The proposed architecture is a completely new design for the main algorithmic blocks of ORB, including the FAST (Features from Accelerated Segment Test) feature detector, Gaussian image filtering, moment computation, and descriptor generation. Adaptive mechanisms are introduced to dynamically adjust thresholds and filtering behavior, improving robustness under varying illumination conditions. The design is developed using a High-Level Synthesis (HLS) approach, where all processing modules are implemented as reusable hardware IP cores and integrated at the system level. The architecture is deployed and evaluated on two FPGA platforms, PYNQ-Z2 and KRIA KR260, and its performance is compared against CPU and GPU implementations using a dedicated C++ testbench based on OpenCV. Experimental results demonstrate significant improvements in throughput and energy efficiency while maintaining stable and scalable performance, making the proposed solution suitable for real-time embedded vision applications on UAVs and similar platforms. Notably, the FPGA implementation increases DSP utilization from 11% to 29% compared to the previous designs implemented by other researchers, effectively offloading computational tasks from general purpose logic (LUTs and FFs), reducing LUT usage by 6% and FF usage by 13%, while maintaining overall design stability, scalability, and acceptable thermal margins at 2.387 W. This work establishes a robust foundation for integrating the optimized ORB pipeline into larger drone systems and opens the door for future system-level enhancements. Full article

Background: Borderline left ventricle represents a heterogeneous spectrum of congenital heart disease for which accurate prediction of suitability for biventricular versus univentricular circulation is often difficult. Serial fetal echocardiography may provide dynamic information to support postnatal decision-making. Case Presentation: We report the case of a fetus diagnosed at 32 weeks’ gestation with a borderline left ventricle, ventricular disproportion, hypoplastic left-sided structures, ductal-dependent systemic circulation, and a non-restrictive ostium secundum atrial septal defect. Serial fetal echocardiographic evaluations demonstrated stable left ventricular dimensions, preserved systolic function, impaired diastolic relaxation, and absence of endomyocardial fibroelastosis. Postnatal echocardiography confirmed hypoplastic aortic arch and coarctation. Following multidisciplinary evaluation, a biventricular repair strategy was selected. At 14 days of life, the patient underwent aortic arch reconstruction and partial atrial septal defect closure with preservation of a small therapeutic interatrial communication. Postoperative evolution was favorable, with progressive left ventricular growth and preserved function. At 2-year follow-up, echocardiography showed normalized mitral and aortic valve z-scores, good left ventricular systolic performance, and no evidence of myocardial fibrosis. Conclusions: This case highlights the value of serial fetal echocardiography in guiding individualized management of borderline left ventricle. Careful assessment of ventricular function and atrial septal physiology may support selection of a biventricular strategy in selected patients and contribute to favorable mid-term outcomes. Full article

Background: Dementia is a growing global public health concern and identifying modifiable risk and protective factors is crucial for its prevention. Fruits and vegetables, due to their antioxidant and anti-inflammatory properties, may offer neuroprotective benefits. This study aims to investigate the prevalence of adequate fruit and vegetable consumption and its association with dementia and cognitive impairment no dementia (CIND) in individuals aged 50 years and older. Methods: This cross-sectional, population-based study analysed data from 2865 participants in the second wave (2019–2021) of the Brazilian Longitudinal Study of Ageing (ELSI-Brazil). CIND was defined as a global cognitive Z-score ≤ −1.5, and dementia as cognitive decline with impairment in at least one instrumental activity of daily living. Adequate consumption of fruits, vegetables, and both combined (FV) was defined as daily intake on all seven days of the week. Associations were assessed using multivariate Poisson regression models, with prevalence ratios (PRs) and 95% confidence intervals (CIs). Results: The study sample consisted of 2865 participants. The prevalence of adequate fruit consumption was 58.08% (95% CI: 56.3–59.9), vegetables 44.14% (95% CI: 42.31–45.9), and FV 32.18% (95% CI: 30.5–33.9). Adequate vegetable consumption was significantly associated with CIND (PR: 0.19; 95% CI: 0.07–0.50; p < 0.001), while adequate fruit consumption was associated with higher prevalence of CIND (PR: 1.47; 95% CI: 1.22–1.77) and FV (PR: 0.20; 95% CI: 0.07–1.58; p = 0.003). No significant association was observed between fruit, vegetable, and FV consumption and dementia. Conclusions: Adequate vegetable and combined FV consumption were protective against CIND, though not associated with dementia. Nonetheless, overall adequate intake remains low in older Brazilian adults. Full article

In the context of increasingly pressing environmental challenges, promoting green consumption through effective marketing of green products has become a critical focus for corporate operations. In this study, we seek to establish a theoretical framework examining the cognitive outcomes of green advertising and online interpersonal influence within social media environments and to investigate the moderating roles of online celebrity endorsement and Generation Z within this framework. Based on the Stimulus–Organism–Response model, empirical data collected from 527 survey responses reveal that both green advertising and online social influence positively enhance consumers’ attitudes. These attitudes, in turn, strengthen green purchase intentions, with online celebrity endorsement serving as a significant moderator in this relationship; this moderating effect is amplified among Generation Z consumers. Additionally, purchase intentions exert a positive influence on word-of-mouth intentions. The results of this study provide important insight into the development of green consumption and social media within the Chinese context. Full article

Conducting regular verticality inspections for thin tower structures is essential for ensuring structural safety, extending service life, and optimizing operation and maintenance strategies. However, the traditional theodolite inspection method, as a commonly used technique for verticality assessment, still has certain limitations, including strict requirements for station setup, the need for high-altitude contact-based operations, and difficulty in accurately resolving the tilt azimuth of the central axis. More importantly, the conventional method provides insufficient understanding of the overall verticality geometric characteristics of thin tower structures, particularly lacking in systematic approaches for characterizing the axis morphology under non-contact, full three-dimensional (3D) perception conditions. Therefore, this study proposes a refined method for inspecting the verticality of thin tower structures using the Marching Square algorithm. The tower body of a tower crane was selected as the experimental subject. Firstly, ground-based LiDAR was employed to scan and acquire the raw point cloud data of the tower crane. After point cloud registration and denoising, high-precision and valid point cloud data of the tower body were obtained. Secondly, a cross-sectional slicing segmentation strategy was designed for the point cloud of the tower body standard sections, and a slice-polygon-contour extraction method based on the Marching Square algorithm was proposed to extract the contour vertices and compute the coordinates of the contour centroids. Finally, a spatial line-fitting algorithm based on the least squares method was proposed to fit a 3D line to the coordinates of the contour centroids, thereby determining the direction vector of the central axis. The direction vector was then subjected to vector operations with the x-axis and z-axis in the station-center space coordinate system to derive the tilt azimuth and tilt angle of the central axis, thereby providing the verticality inspection results of the tower crane. The experimental results indicate that the four cross-section slicing segmentation schemes designed using the proposed method in this study yielded tower crane verticality values of 2.45‰, 2.35‰, 2.20‰, and 2.18‰. All verticality values meet the verticality requirement of no more than 4‰ specified in GB/T 5031-2019 (Tower Cranes). This verifies that the proposed method is feasible and effective, providing a novel, high-precision, and non-contact inspection method for inspecting the anti-overturning stability of thin tower structures. Full article

In this study, a targeted SSR (Simple Sequence Repeat) marker resource was developed based on genes and protein families associated with pathogen- and pest-related defense–resistance mechanisms in Camellia sinensis. Forty-one genes and protein families reported to show upregulation, increased expression, or functional validation under disease and pest stress were selected, and the corresponding 195 loci were mapped onto the Camellia sinensis cv. Shuchazao genome. SSR screening within gene bodies and gene-flanking regions (±5 kb) identified 5197 SSR loci. Putative QTL hotspot regions were defined using locus-based sliding-window analysis, Z-score calculations, and permutation tests, yielding 633 SSRs filtered at the 99% and 95% significance thresholds. Proteome-wide scans based on conserved amino acid motifs identified multiple loci within the WRKY, NAC, LRR, PRX, and CHI families, and Random Forest analysis was used to prioritize SSRs within these families. Finally, 386 SSR primer sets were designed and evaluated by in silico PCR across six tea genomes. Of these, 245 primers produced amplicons in more than one genome, and 124 exhibited polymorphic information content values greater than 0.500. Overall, the developed SSR panels represent a biologically contextualized and experimentally transferable marker resource targeting defense–resistance-associated genic and gene-proximal regions. Full article

This study investigates the impact of ESG practices on the financial stability in a multisector sample of 86 publicly listed Brazilian firms, focusing on the Weighted Average Cost of Capital (WACC) and Altman Z-Score (AZS) as a proxy for insolvency risk. Using Bloomberg data from 2010 to 2021, this research applies advanced econometric methods, including Ordinary Least Squares (OLS), Vector Autoregression (VAR) and Fully Modified Ordinary Least Squares (FMOLS), to capture both short- and long-term effects. The findings reveal a financial learning curve: in the short term, ESG adoption can temporarily increase WACC and insolvency risk due to initial implementation costs, whereas in the long term, it reduces financial risk, enhances operational efficiency, and strengthens corporate resilience. These results underscore ESG practices as a strategic determinant of long-term value creation and financial stability. This study offers actionable insights for policymakers, investors, and corporate leaders aiming to align sustainability initiatives with financial performance in emerging market contexts. Full article