Search Results (2,573)

Fluent word reading is a key literacy skill, yet the full extent of the oculomotor underpinnings in developing readers remains unknown. Rapid automatized naming (RAN) is a useful clinical measure that has been shown to predict word reading fluency. Here we use RAN scores to predict early, mid, and late local stages of word reading as measured by eye tracking in children who are at a critical time in their literacy development. Thirty-three children participated in two RAN tasks (rapid letter naming (RLN) and rapid digit naming (RDN)) and an eye-tracking task, which included sentence-level reading with an embedded target word. The eye-tracking measures of first fixation duration, regression path duration, and total word reading time were used as early, mid, and late local measures, respectively. RLN and RDN significantly predicted only the mid-stage of the reading process (regression path duration). Faster RLN and RDN times were associated with briefer regressions from target words. Preliminary results link behavioral RAN performance to a mid-stage oculomotor variable, indicating that children with slower RAN times may exhibit longer regressions during reading, suggesting possible difficulties with the integration of phonological processing skills. Full article

This paper presents an all-digital fractional-N phase-locked loop (ADPLL) operating in the 2.86–3.2 GHz range, optimized for IoT and high-frequency RF transceiver applications demanding stringent phase noise performance, fast settling time, and high integration capability. The key innovation lies in the introduction of a bandpass delta-sigma time-to-digital converter (BPDSTDC) that achieves high-resolution phase detection, an extended detection range of ±2$\pi$, and superior noise-shaping characteristics, completely eliminating the complex calibration procedures typically required in conventional TDC designs. The proposed architecture synergistically combines the BPDSTDC with digital down-conversion blocks to extract phase error at baseband, a divider chain integrated with phase interpolators achieving 1/4 fractional resolution to suppress in-band quantization noise, and a wide-bandwidth digital loop filter (>1 MHz) ensuring fast dynamic response and robust stability. The bandpass delta-sigma modulator is implemented with compact resonator structures and a flash quantizer, achieving an optimal balance among resolution, power consumption, and silicon area. The incorporation of highly linear phase interpolators extends fractional frequency synthesis capability without requiring complex digital-to-time converters (DTCs), significantly reducing design complexity and calibration overhead. Fabricated in a 180-nm CMOS technology, the proposed chip demonstrates robust measured performance. The band-pass delta-sigma TDC achieves a low integrated rms timing noise of 183 fs within a 1-MHz bandwidth. Leveraging this low TDC noise, the complete ADPLL exhibits a measured in-band phase noise of −120 dBc/Hz at a 1-MHz offset for a 3.2-GHz output frequency while operating with a loop bandwidth exceeding 1 MHz. This corresponds to a normalized phase noise of −216 dBc/Hz. The system operates from a 1.8-V supply and consumes 10 mW, achieving competitive performance compared with prior noise-shaping TDC-based all-digital PLLs. Full article

The performance upgrading of stratospheric airships hinges on breakthroughs in the mechanical properties of envelope materials. As a multi-layer composite, the envelope’s load-bearing layer exhibits orthotropic and nonlinear mechanical behaviors owing to its unique structure and manufacturing process. To overcome the limitations of traditional testing methods and classical strength criteria in characterizing envelope materials, this paper presents a systematic investigation of typical airship envelope materials. The classical cruciform biaxial specimen was modified with a double-layer heat-sealed loading arm design to ensure preferential failure of the core region. Combined with digital image correlation (DIC) equipment, tensile tests were conducted under seven warp–weft stress ratios to acquire full-range stress–strain data. A three-dimensional stress–strain response surface was fitted based on the experimental results, and biaxial tensile constitutive models with varying precisions were established. Furthermore, a five-parameter implicit quadratic strength criterion was adopted to characterize the failure envelope of the envelope material. The model was calibrated using five biaxial failure points and independently validated against uniaxial tensile strengths, achieving a prediction error of less than 4%. The criterion’s generalization capability was enhanced through systematic parameterization based on the present test data. This work provides experimental evidence and reliable support for the engineering design and strength prediction of envelope materials. Full article

The snowpack in the European Alps is declining due to global warming, which affects both the amount of seasonal snow and the timing of accumulation and melt. As the European Alps is the largest winter tourism destination in the world by revenue, this decline in natural snow poses an existential threat to the sector. Several smaller ski areas have closed permanently since 1980, and all Alpine regions face rising costs due to an increasing reliance on snowmaking. Professional winter sports are also affected, with several canceled events in recent years due to unsuitable snow conditions. In this study, we present the first remote sensing-based assessment of long-term snow reliability for winter tourism in the European Alps. Using snowline elevation (SLE) data derived from Landsat observations from 1985 to 2024, combined with OpenStreetMap ski infrastructure data and digital elevation models, we quantified the monthly snow coverage of ski area segments across 43 Alpine basins. Theil–Sen trends and Mann–Kendall significances were calculated for the full season and for three subseasons, with quality checks applied to guarantee sufficient data coverage. The results show predominantly negative trends across all seasons, with the strongest declines occurring in the late season. In this period, 97.8% of all downhill ski areas and 99.5% of the cross-country ski areas for which a trend was derived exhibited negative trends. For the full season, the corresponding shares were 94% for downhill ski areas and 99.2% for cross-country ski areas. In addition, areas located at the geographical edges of the European Alps showed more pronounced negative trends compared with the core regions. These findings align with previous studies on the subject and highlight the ongoing shortening of natural snow seasons and thus the increased challenges for the winter tourism sector in the Alps. Full article

This study examines the influence of stakeholder engagement with corporate social responsibility (CSR) disclosures on social media and corporate financial performance, grounded in legitimacy theory and stakeholder theory. Using a panel dataset of 388 firm-year observations of Indonesian listed companies over the period 2019–2022, we investigate how stakeholder interactions across four social media platforms—Facebook, Twitter, Instagram, and YouTube—relate to firm performance measured by Return on Assets (ROA) and Return on Equity (ROE). Panel data regression results reveal that stakeholder engagement on visual-based platforms plays a significant role in enhancing financial performance. In particular, Instagram likes and YouTube likes are positively associated with ROA (β = 0.0004, p < 0.05; β = 0.0002, p < 0.05), while Instagram comments, YouTube likes, and YouTube views show a significant positive relationship with ROE (β = 0.011, p < 0.01; β = 0.0006, p < 0.01; β = 0.000249, p < 0.01). In contrast, engagement metrics on Facebook and Twitter do not exhibit a statistically significant association with firm performance. These findings suggest that stakeholder engagement with CSR disclosures through high-engagement, visual-oriented social media platforms can strengthen corporate legitimacy and stakeholder relationships, ultimately contributing to improved financial outcomes. The study highlights the strategic importance of platform-specific digital communication in enhancing firm performance. Full article

Using a quantile–frequency connectedness framework, this study analyzes the regime-contingent and horizon-specific transmission of shocks among AI assets, FinTech markets, and Blue Economy financial instruments. The empirical results reveal a distinctly asymmetric connectedness structure, whereby high-frequency spillovers intensify in upper-quantile states associated with liquidity stress and sentiment-driven trading, while low-frequency connectedness remains comparatively muted, thereby preserving cross-segment diversification potential. AI assets emerge as dominant net transmitters in short-horizon dynamics, reflecting rapid innovation cycles and speculative adjustments. FinTech markets exhibit stabilizing properties under median regimes but transition into net propagation roles when risk conditions escalate. Blue finance instruments act as conditional net absorbers, attenuating volatility originating from digital innovation-driven markets, particularly during adverse market states. By decomposing spillover intensities across quantiles and spectral bands, the analysis highlights a structural differentiation between innovation-sensitive digital assets and the comparatively stable behavior of blue-themed financial assets. These findings advance the understanding of nonlinear dependence, asymmetric contagion, and state-dependent co-movements in emerging financial ecosystems. The results provide actionable insights for systemic-risk measurement, cross-market shock diagnostics, and multi-asset portfolio construction in an increasingly interconnected global financial system. Full article

Informal food trading is a cornerstone of urban livelihoods and food security in Namibia, yet traders operate under fragile conditions marked by limited capital, policy exclusion, and exposure to shocks such as COVID-19. Despite this vulnerability, traders exhibit resilience through everyday forms of social innovation. This study investigates how adaptive pricing, customer credit, and digital communication and e-payment practices function as pathways of resilience among 470 informal food traders in Windhoek, using Structural Equation Modelling to assess gender-differentiated determinants and outcomes. The analysis reveals that women’s adoption of adaptive pricing and digital tools is driven primarily by education and startup capital, while men’s innovation practices are shaped by vendor type and access to financing. Social innovations mediate the effects of these structural factors on enterprise growth, demonstrating that innovation acts as a critical mechanism linking resources and resilience. The study concludes that enhancing informal traders’ resilience requires policies that strengthen human and financial capital, improve digital inclusion, and recognize gendered differences in access to opportunity. It recommends targeted support for women’s entrepreneurial training, affordable credit, and digital infrastructure to transform the informal food sector into a more equitable and sustainable component of Namibia’s urban economy. Full article

Ecological sustainability is one of the key dimensions of sustainable development in any economy. Developing economies exhibit high-risk levels in terms of political stability and corruption, thereby inhibiting them from successfully adopting techniques for ecological sustainability. A framework that comprises a strong financial system for green financial investment, coupled with correct policy frameworks becomes fundamental in the attainment of sustainable environments. Pervasive corruption in developing nations is a formidable barrier that impedes financial development and undermines green finance initiatives’ efficacy in fostering ecological sustainability. This research takes the data of the Central African nations, which is analyzed with the ‘Methods of Moments Quantile Regression’ technique. The major results presented show that digitalization, renewable energy, and governance support ecological sustainability. Institutional quality and green finance are expected to increase ecological sustainability, but the findings show that in the Central African countries with high corruption they tend to reduce ecological sustainability. The poor institutional quality in the Central African nations, because of high corruption and political instabilities, impedes the efficacy of financial development and green finance in advancing ecological sustainability. The Central African nations can achieve sustainability by fostering digitalization and renewable energy, as well as reducing corruption and political instabilities. Full article

In the era of the digital economy, enhancing enterprise resilience has become a strategic imperative for sustainable manufacturing development. However, the micro-level mechanisms through which data element policies, specifically China’s National Big Data Comprehensive Pilot Zone, empower enterprise resilience remain insufficiently explored. To address this gap, this study leverages the policy rollout as a quasi-natural experiment and employs a multi-period difference-in-differences approach to analyze panel data of listed manufacturing firms. The results reveal that enterprises within pilot zones exhibit a 2.3% average increase in resilience compared to non-pilot counterparts. This effect is significantly amplified by enterprise digital transformation and regional innovation-entrepreneurship vitality. Mechanism analysis further identifies that the policy enhances resilience primarily by reducing supply chain coordination costs and improving relationship stability, with additional positive spillovers observed in adjacent cities. These findings highlight the disruptive potential of big data in reshaping corporate resilience paradigms and provide empirical support for scaling data-driven industrial policies to foster high-quality economic development. Full article

Gravity currents constrained by bottom walls are prevalent in engineering applications such as industrial discharges and deep-sea mining, and will pose significant environmental risks. In this study, the influence of jet source parameters on the dynamics and diffusion characteristics of particle-driven bottom currents was investigated through physical experiments using Digital Image Processing (DIP). This non-invasive technology is cost-effective and exhibits broad applicability. The results demonstrated that the downstream plume front $d_{\mathrm{L}\mathrm{m}\mathrm{a}\mathrm{x}}$, the maximum lift height $h_{\mathrm{L}\mathrm{m}\mathrm{a}\mathrm{x}}$ and the average lift height $h_{\mathrm{a}\mathrm{v}\mathrm{e}}$ all exhibit a decreasing trend with increasing Richardson number (Ri) after impingement, and show a linear increase with rising Reynolds number (Re). The plume diffusion scale S follows a two-stage evolution: during the inertia-dominated stage, S evolves exponentially over time t as $S=a{e}^{bt}$, while in the equilibrium stage of negative buoyancy and turbulent dissipation, S follows a power-law relationship $S=a{t}^b$ (b < 1). The rate of change of S increases with smaller jet angles α, and the variations with dimensionless bottom clearance H/D remain within 10%. The dimensionless average longitudinal expansion rate ${\displaystyle \frac{\overline{E}}{\sqrt{g\prime /D}}}$ reaches minimum values at α = 75°, peaks at H/D = 10, and exhibits a linear decreasing trend with Ri. As Re increases, ${\displaystyle \frac{\overline{E}}{\sqrt{g\prime /D}}}$ displays a three-stage fluctuating behavior. This study provides valuable experimental data that improve the understanding of gravity current behavior under wall confinement and support the predictive modelling of gravity current. Full article

Urban sustainability is increasingly defined by the resilience of the built environment against hazards. While Agent-Based Models (ABMs) are commonly used to simulate these dynamics, their predictive capacity is often limited by a lack of empirical behavioral data. This study addresses this gap by introducing a Human-Centric Digital Twin framework that integrates procedural generation with immersive Virtual Reality (VR) to quantify ‘spatial sustainability’, defined as the capacity of an urban form to support life safety without compromising its morphological identity. In this framework, VR serves as a controlled environment for observing navigation under stress, while procedural generation creates structurally distinct urban morphologies (orthogonal vs. organic) to enable universal calibration. The approach was validated through evacuation experiments with 37 participants under varying visibility conditions. Results reveal that while performance was similar in daylight, significant behavioral divergence emerged at night; the organic layout (Type A) exhibited greater variability and longer evacuation times compared to the orthogonal grid (Type B). These findings confirm that spatial configuration dictates resilience when sensory inputs degrade. Consequently, this study offers a transferable, data-independent protocol for measuring and monitoring urban resilience in data-scarce environments. Full article

The rapid expansion of corporate sustainability reporting has increased transparency requirements while raising concerns about greenwashing driven by selective, narrative-based disclosure. This study assesses the credibility of Environmental, Social, and Governance (ESG) communication by comparing corporate sustainability reports with external media coverage for a sample of 204 large firms operating in Central and Eastern Europe in 2023. Using natural language processing techniques, the analysis constructs a Greenwashing Severity Index (GSI) that captures discrepancies between firms’ ESG self-representation and external public narratives. The index combines ESG-specific focus measures, sentiment analysis, TF–IDF-based term weighting, and topic modeling to quantify imbalances in ESG communication. Results indicate moderate but widespread greenwashing across countries, industries, and firm sizes, with substantial heterogeneity linked to differences in regulatory maturity and stakeholder scrutiny. Higher alignment between corporate disclosures and external narratives is observed among larger firms and in sectors subject to stronger public accountability, while finance, aviation, and online commerce exhibit higher greenwashing severity. A propensity score matching analysis further shows that firms with imbalanced emphasis across ESG dimensions display significantly higher GSI values, consistent with strategic disclosure behavior rather than substantive sustainability engagement. Overall, the findings demonstrate that transparency alone is insufficient to ensure credible ESG communication, highlighting the need for EU sustainability governance to move beyond disclosure-based compliance toward digitalized, data-driven monitoring frameworks that systematically integrate external information sources to curb strategic ESG misrepresentation and enhance corporate accountability under evolving regulatory regimes. Full article

While the Internal Model Principle (IMP) and Disturbance Observer (DOB) are fundamental to robust control, their systematic equivalence within a unified framework has received limited attention. IMP-based control achieves robustness through the structural inclusion of signal generators, whereas DOB-based methods rely on extended state representations for disturbance estimation. This paper bridges this gap by designing a state-space Reduced-Order Disturbance Observer (RODOB)-based controller that achieves systematic equivalence with an IMP-based transfer function controller. As a design example, an IMP-based controller is synthesized using a Linear Quadratic Regulator (LQR) for an augmented system in error space, with reference inputs directly integrated into the RODOB structure to eliminate the need for additional filters. Simulations and hardware experiments on a Brushless DC (BLDC) motor verify that both structures exhibit consistent control input and output characteristics, significantly outperforming conventional cascade and PID strategies. Numerical stability during digital implementation is ensured via partial fraction expansion. Furthermore, a method for estimating equivalent disturbances—encompassing both external loads and model uncertainties—is proposed by leveraging RODOB states. These findings suggest significant potential for future applications in fault diagnosis and real-time condition monitoring. Full article

The growing prevalence of AI-powered chatbots in digital service environments has raised user expectations from mere functional efficiency to emotionally satisfying interactions. Drawing on Language Expectancy Theory (LET), this study investigates the impact of AI chatbot language style (namely, elaborate vs. succinct language) on customer service satisfaction. Across three studies, we demonstrate that customers exhibit higher satisfaction when interacting with chatbots employing elaborate language as opposed to succinct language. Furthermore, this effect is mediated by warmth and moderated by customer relationship norm orientation. The influence of elaborate language is more pronounced among customers with communal relationship norms, whereas those with exchange relationship norms respond more favorably to succinct language. Theoretically, this study enriches the literature on language style in human–computer interaction by introducing elaborateness as a pivotal communicative dimension. Practically, our results offer strategic guidance that can help service providers and developers to strategically tailor chatbot language styles to distinct customer segments, consequently enhancing service quality, fostering emotional engagement, and cultivating long-term customer loyalty within automated service systems. Full article

This study evaluates how legal and regulatory architectures shape banks’ digital transformation in Qatar relative to peer jurisdictions and isolates the regulatory components that most strongly predict observed differences in digital maturity. Employing a comparative mixed-methods design, the study links a structured legal-regulatory assessment to quantitative benchmarking of fifteen banks (five Qatar, ten international) using a Digital Maturity Index and inferential tests (descriptive statistics, independent-samples t-tests, and OLS regressions). International banks exhibit higher average digital maturity than Qatar banks, and across the sample, regulatory clarity and coherence are positively and significantly associated with digital maturity, whereas supervisory intensity alone shows no comparable effect; implementation frictions in open banking/interoperability, unified data protection, and approval timelines constrain collaboration and product rollout in Qatar. Moreover, the cross-sectional design, modest sample size, and index weighting choices limit causal inference and external validity, indicating the need for longitudinal and quasi-experimental designs to corroborate mechanisms and generalize findings. Policymakers should adopt risk-proportionate, outcomes-based rules, codify interoperable API standards, strengthen data rights and cloud/third-party governance, and establish sector-level KPIs to match supervisory expectations with bank execution and accelerate safe digitalization. Enhancements to privacy, data portability, and inclusive digital onboarding are likely to improve consumer trust, competition, and access, thereby advancing broad-based participation in digital financial services. The study integrates legal analysis with bank-level operational metrics through an analytically tractable index and a Qatar–international comparison, demonstrating the outsized role of regulatory clarity in advancing digital maturity. Full article