Search Results (6,600)

This study investigates how board gender diversity affects firms’ long-term investment behavior in Korea, focusing on capital expenditures and R&D spending from 2011 to 2021. Using firm fixed-effects regressions and robustness tests with alternative measures of gender diversity, the results show that independent female directors are positively associated with long-term investment. However, this effect is significant only in non-Chaebol firms, where board independence is stronger, and gender diversity reflects genuine governance engagement. In Chaebol-affiliated firms, where female directors are often appointed to meet regulatory requirements, the relationship is insignificant, suggesting that diversity driven by formal compliance fails to enhance strategic decision-making. These findings highlight that the effectiveness of gender diversity depends on institutional authenticity rather than numerical representation. The study contributes to the corporate governance literature by showing how ownership structure and board independence condition the real impact of gender-diverse boards and offers policy implications for promoting substantive rather than symbolic diversity reforms. Full article

Urban vitality is a crucial indicator of a city’s sustainable development and the quality of life of its residents. Investigating the spatiotemporal patterns and influencing mechanisms of urban vitality is essential for optimizing the built-environment and improving governance. Using the central urban area of Guiyang, China, as a case study, this research integrates multi-source urban sensing data to investigate the spatiotemporal patterns of urban vitality and their driving factors. Geographically weighted regression (GWR) and machine learning combined with SHapley Additive exPlanations (SHAP) are applied to capture spatial heterogeneity, nonlinear relationships, and threshold effects among influencing variables. Results show that urban vitality exhibits a Y-shaped, single-core, multi-center, and clustered spatial configuration, with slightly higher intensity on weekdays and similar diurnal rhythms across weekdays and weekends. The effects of influencing factors display strong spatial non-stationarity, characterized by a concentric gradient radiating outward from the historic Laocheng core. Building density (BD), residential point density (RED), normalized difference vegetation index (NDVI), and road density (RD) emerge as the dominant contributors to urban vitality, while topographic conditions play a relatively minor role. The relationships between key landscape and built-environment variables and urban vitality are highly nonlinear, with distinct threshold effects. By integrating spatial econometric modeling and explainable machine learning, this study advances methodological approaches for urban vitality research and provides practical insights for landscape-oriented urban planning and human-centered spatial design. Full article

Leading agribusiness firms are pivotal to modernizing agricultural supply chains, yet evidence on how digital transformation translates into high-quality development remains fragmented. Using a 2024 sample of 30 Chinese national agribusiness leaders and the technology–organization–environment (TOE) framework, we integrate grey relational analysis with DEMATEL to quantify interdependencies among conditions, and combine fuzzy-set QCA with necessary condition analysis to identify both configurational pathways and binding constraints. The results of the analysis indicate that high-quality development rarely stems from a single driver; it emerges from complementary bundles linking digital technologies and R&D investment with organizational readiness (e.g., talent and governance) under supportive external conditions (e.g., policy incentives and market pressure). The findings provide a configurational explanation of digital upgrading in agribusiness and inform differentiated digital strategies for managers and policymakers. Full article

Potyvirus genomes are expressed as a single large open reading frame, which is translated into a polyprotein that is post-translationally cleaved by three virus-encoded proteases into 10 functional proteins. Several of these potyviral proteins, including nuclear inclusion protein b (NIb), are multifunctional. Here, using the classic GFP silencing in Nicotiana benthamiana gfp-transgenic plants, we show that potato virus Y (PVY) NIb, in addition to its canonical role as the viral RNA-dependent RNA polymerase (RdRP), functions as a suppressor of RNA silencing. Mutational analyses reveal a previously unreported NIb nuclear localization signal (NLS) consisting of a triple-lysine motif. NIb suppression of RNA silencing activity was lost when the NLS was mutated, suggesting that nuclear localization is required for NIb suppression of RNA silencing activity. Analysis of sequenced GFP siRNAs revealed three reproducible hotspot regions at ≈175 nt, ≈320–330 nt, and a broader 3′-proximal region spanning ≈560–700 nt that contains multiple local maxima. These data show differences in the positional distribution of siRNAs between samples expressing NIb and those expressing NIb^Del3×2, the NIb null mutant that does not suppress RNA silencing. However, the positional distribution of GFP-derived small RNAs across the transgene differed modestly between NIb and NIb^Del3×2, while both treatments showed the same three reproducible hotspot regions. Furthermore, NIb was found to interact with four key RNA silencing pathway proteins—AGO4, HSP70, HSP90, and SGS3. Except for HSP90, each of these proteins showed degradation products that were absent in NIb mutants that did not suppress RNA silencing. These findings support a role for NIb in countering host defense during virus infection. Full article

Fungal extracts have been reported to exert diverse biological activities, including anti-inflammatory, antibacterial, and antiviral effects. However, the anti-coronaviral properties of fungal extracts remain largely unexplored. In this study, we demonstrated that the Penicillium compactum extract (PCE) inhibits the replication of human coronavirus. RD cells were infected with human coronavirus and subsequently treated with PCE. PCE treatment reduced the expression of viral proteins and ameliorated virus-induced cytopathic effects. In addition, PCE markedly decreased viral RNA levels in both the cells and the conditioned medium. Finally, we confirmed that PCE treatment reduced the production of infectious viral particles. Collectively, these findings indicate that PCE exhibits potent antiviral activity against human coronavirus. Full article

Background: Sleep is a key determinant of recovery and performance in elite athletes, yet its optimization extends beyond sleep duration alone and encompasses multiple subjective and physiological dimensions. Environmental factors, including the sleep surface, represent modifiable components of sleep that may influence perceived sleep quality. This study aimed to examine whether an individually adjustable modular sleep system improves subjective sleep quality in elite athletes and whether alterations in objective sleep metrics, circadian timing, or nocturnal autonomic physiology accompany such changes. Methods: Forty-three elite athletes participated in this pre–post-intervention study (without a control group). Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), while objective sleep and physiological parameters were recorded using a wearable device (Oura Ring, 3rd generation). Outcomes were averaged across three consecutive nights at baseline (T0) and post-intervention (T1). Baseline values were derived from the final three nights of a standardized pre-intervention monitoring period (minimum 7 nights), and post-intervention values from the final three nights following a standardized intervention exposure period (minimum 14 nights). Statistical analyses included paired frequentist tests and complementary Bayesian paired-sample analyses. Results: Subjective sleep quality improved significantly following the intervention, with a mean reduction in PSQI score of 0.67 points (p < 0.001). In contrast, no meaningful changes were observed in total sleep time (p = 0.28), REM duration (p = 0.26), circadian timing (p = 0.47), or nocturnal minimum heart rate (p = 0.42), as supported by the absence of physiological changes in these parameters. Conclusions: It seems that an individually adjustable sleep system can be able to improve perceived sleep quality in elite athletes without disrupting sleep architecture, circadian regulation, or nocturnal autonomic function. In athletes whose sleep duration and physiological sleep metrics are already near optimal, such micro-environmental interventions may offer a feasible, low-risk means of enhancing recovery by targeting subjective sleep quality. This dimension dissociates from objective sleep measures. Optimizing the sleep surface may therefore represent a practical adjunct to existing recovery strategies in high-performance sport. Full article

This paper constructs a two-way fixed effects model using data from 4623 Chinese A-share listed enterprises from 2011 to 2022, confirming that firm digital transformation can enhance access to sustainable trade credit. Specifically, for every 1% increase in the standard deviation of digital transformation, the trade credit obtained by enterprises increases by 2.14% in relation to their average value. We employed instrumental variable (IV) and propensity score matching (PSM) methods, utilizing the Broadband China pilot policy as a quasi-natural experiment to conduct a multi-period propensity score matching-difference in differences (PSM-DID) analysis to address potential issues of reverse causality and sample selection bias. Mechanism analysis indicates that the diversification of supplier structures, R&D innovation, and market share facilitated by digitalization are three main channels. This effect is particularly significant in state-owned enterprises, mature enterprises, and those with higher social trust. Finally, the study also found that the spillover effects of digital transformation encourage client enterprises to allocate credit resources to downstream firms, thereby promoting the sustainable development of supply chain finance. Furthermore, the digital transformation primarily alleviates short-term credit challenges for enterprises and reduces their reliance on bank credit. Full article

This study introduces the Sustainable Development Goals Achievement Measurement Framework (SDG-AMF), a novel analytical tool used to systematically evaluate the relationships between digitalization and the Sustainable Development Goals (SDGs). Unlike the United Nations (UN) E-Government Development Index (EGDI) and Organization for Economic Co-operation and Development (OECD) Digital Government Indicators (DGIs) frameworks, the proposed SDG-AMF links digitalization indicators to specific SDG outcomes using proxy-based time-series analysis. The SDG-AMF provides a unified, statistically grounded approach that connects digital development with measurable sustainability outcomes. Using direct, high-quality time-series data (2010–2024) from internationally recognized sources, the framework maps key digitalization indicators such as Internet penetration, e-government maturity, research and development (RD) expenditure, gross domestic product (GDP) per capita, and gender participation in information and communication technology (ICT) to the selected SDG targets (SDGs 4, 5, 8, 9, and 16). Through correlation and regression analyses, the study identifies enabling and inhibiting relationships, highlighting Saudi Arabia’s strengths in digital infrastructure and e-government maturity while emphasizing areas for improvement, such as civic participation and RD intensity. Comparative benchmarking with digitally advanced economies underscores Saudi Arabia’s strengths in Internet penetration and e-government maturity, while gaps in RD investment are identified. The SDG-AMF provides policymakers with a replicable roadmap and scalable model to align foundational connectivity and governance reforms with advanced digital transformation, facilitating progress toward achieving Sustainable Development Goals worldwide. This research contributes original methodological insights and equips stakeholders with practical tools to monitor, compare, and accelerate SDG progress in the digital era. Full article

Modern battlefield operations require wearable technologies to operate reliably under harsh physical, environmental, and security conditions. This review looks at today and tomorrow’s potential for ready field-grade wearables embedded with biometric authentication systems. It details physiological, kinematic, and multimodal sensor platforms built to withstand rugged, high-stress environments, and reviews biometric modalities like ECG, PPG, EEG, gait, and voice for continuous or on-demand identity confirmation. Accuracy, latency, energy efficiency, and tolerance to motion artifacts, environmental extremes, and physiological variability are critical performance drivers. Security threats, such as spoofing and data tapping, and techniques for template protection, liveness assurance, and protected on-device processing also come under review. Emerging trends in low-power edge AI, multimodal integration, adaptive learning from field experience, and privacy-preserving analytics in terms of defense readiness, and ongoing challenges, such as gear interoperability, long-term stability of templates, and common stress-testing protocols, are assessed. In conclusion, an R&D plan to lead the development of rugged, trustworthy, and operationally validated wearable authentication systems for the current and future militaries is proposed. Full article

With the rapid advancement of intelligent technologies in electric vehicles, various control technologies and algorithms are emerging. Most existing research, however, is limited to simulations of single modules such as suspension, braking, and battery management, lacking comprehensive modeling and simulation for the entire vehicle system, which impedes the integrated development and verification of advanced intelligent technologies. Therefore, this article focuses on the vehicle control system of electric vehicles. It first analyzes the overall scheme and clarifies the core functions of system operation control, fault detection, and storage. Subsequently, a data acquisition simulation platform for the vehicle control system is established based on MATLAB/Simulink, creating simulation modules for accelerator pedal, braking pedal, key position, and gear signal, forming a complete vehicle simulation platform. For the established simulation platform, specific electric vehicle model parameters are set, and under the QC/T759 urban driving conditions, simulations of the electric vehicle’s operation are conducted to obtain relevant signals such as vehicle speed, accelerator pedal, and braking pedal, verifying the feasibility of the vehicle control system. Finally, a hardware platform for the entire vehicle power system is built, and based on the PCAN-Explorer5 software, the connection and debugging of the vehicle controller, battery management system, and motor control unit are achieved to obtain the status parameters of each system and debug the vehicle control system, laying the foundation for the actual operation of the pure electric SUV. Through the simulation of the electric vehicle’s control system, the R&D cycle is greatly shortened, development costs are reduced, and a foundation is established for the actual vehicle debugging of electric vehicles. Full article

RNA-directed DNA methylation (RdDM), a new plant breeding technology, induces epigenetic modifications that can be inherited even after segregation of the responsible transgene. The transgene-free descendants (null segregants) are potentially exempt from the regulation of genetically modified plants. To evaluate the risks of potential unintended molecular changes in the null segregants of RdDM-positive plants, we produced null segregants (S44end2-null) from a transgenic tobacco line in which RdDM targeting the promoter of the transgene was introduced. Comprehensive multi-omics analyses, including transcriptomics, proteomics, and metabolomics, were conducted using S44end2-null and wild-type (WT) plants. Principal component analysis demonstrated clear separation of the transcriptomic and proteomic profiles of the two groups. The metabolomic profiles of S44end2-null plants exhibited considerable overlap with those of WT plants. Proteomic analysis of the null segregants of tobacco plants transformed with an empty vector demonstrated distinct cluster separation from WT plants. Because only sporadic DNA methylation on the tobacco genome was expected by the RdDM construct used in this study, the observed differences in omics profiles are considered to be significantly influenced by genetic variation accumulated during the transformation and regeneration processes (somaclonal variation). The safety assessment points for null segregants using RdDM technology are discussed. Full article

As digital technologies increasingly permeate urban governance and economic systems, the digital economy (DE) is widely regarded as a key driver of green urban transformation. However, its environmental effects remain complex under the dual constraints of resource dependence (RD) and spatial structure. Drawing on panel data from 277 Chinese prefecture-level cities from 2011 to 2019, this study systematically evaluates the green impacts of the DE across varying resource conditions and urban lifecycle stages. The results reveal a dual-effect pattern: while digitalization significantly promotes local green sustainable development (GSD), it simultaneously suppresses the green performance of neighboring cities through siphoning effects, creating spatial divergence. Cities with lower levels of RD are more likely to benefit from digital dividends, whereas in high-dependence settings, the green effects of digitalization reverse beyond a critical threshold. Grouped regressions for resource-based (RBCs) and non-resource-based cities (NRBCs) further confirm this moderating mechanism. Moreover, lifecycle heterogeneity among RBCs leads to differentiated green outcomes. By introducing the dual mechanisms of “resource lock-in” and “digital siphoning” into the framework of GSD, this study expands the theoretical understanding of the interaction between digitalization and RD. The findings provide empirical support for interpreting the structural divergence in DE–GSD linkages and offer a quantitative basis for differentiated policy strategies in resource-intensive urban contexts. Full article

Selenium (Se) biofortification in rice presents a promising strategy to address Se deficiency in populations relying on rice as a staple food. This study evaluated the impact of foliar Se application on Se accumulation, its distribution in unpolished and polished rice grains, grain yield, and antioxidant capacity across 21 rice genotypes. Foliar Se application significantly improved grain yield, with increases ranging from 5.7 to 67.5% compared to non-foliar Se application. Se concentrations in both unpolished and polished grains were notably enhanced by foliar application, reaching 41.1–543.9 µg kg⁻¹, whereas non-foliar treatments resulted in much lower concentrations (0–30.5 µg kg⁻¹). Foliar Se also altered Se partitioning, decreasing Se retention in unpolished grains (from 9.8–100% under non-foliar application to 19.7–66.1% with foliar Se application) and increasing its proportion in polished rice. Se loss during polishing was genotype-dependent and generally reduced by foliar Se application (9.4–72.3%). Antioxidant capacity was highest in unpolished rice and varied among genotypes, increasing further with foliar Se. A positive correlation between grain antioxidant capacity and Se concentration was observed in unpolished, but not polished rice. Overall, these findings demonstrate the effectiveness of foliar Se biofortification in enhancing Se content and antioxidant properties, emphasizing the importance of genotype selection such as RD16, RD79, KDML105, K2, KJ CMU 107, and HMD to maximize biofortification benefits. Full article

Annual influenza vaccination remains critical for mitigating severe illness and reducing healthcare strain, particularly among high-risk populations. Despite advancements in vaccine platforms, the comparative efficacy of novel vaccines—such as high-dose (HD-IIV), recombinant (rIV), cell-based (cIV), and adjuvanted (aIV) influenza vaccines—versus standard-dose non-adjuvanted (SD-IIV) vaccines remains a public health concern. Traditional Relative Vaccine Efficacy (rVE) metrics, though robust, may overestimate population-level benefits. This short communication explores alternative comparative efficacy measures: risk difference (ΔRD) and number needed to vaccinate (ΔNNV). Analysis of data derived from randomized controlled trials (RCTs), or robust pragmatic trials, shows that while rVE values for newer vaccines often indicate superior efficacy, ΔRD and ΔNNV highlight the limits in incremental protection at the population level, with ΔRD generally below 10 cases per 1000 vaccinated. These findings underline the sustained relevance of SD-IIV in immunization programs and emphasize the need for broader vaccine coverage to highlight the benefits of vaccination and enhance population health outcomes. Full article

Pulses (edible dry seeds from legumes) are among the most important crops worldwide. These legumes contain a diverse range of carbohydrates, some of which, such as RFOs (raffinose family oligosaccharides), are considered antinutritional factors due to their negative impact on digestion. An analytical method based on high-power ultrasound-assisted extraction and HPLC analysis was developed and validated for the quantitative determination of soluble carbohydrates (verbascose, stachyose, raffinose, sucrose, galactinol, glucose, galactose, fructose, and myo-inositol) in common beans (Phaseolus vulgaris) and peas (Pisum sativum). The proposed method is fast (extraction time: 1 min), reproducible (RDS: 6.9%), accurate (97.5%), and environmentally sustainable. The method was applied to local collections of P. vulgaris (n = 12) and P. sativum (n = 34), revealing similar qualitative profiles but notable quantitative differences. In P. vulgaris, sucrose and stachyose were predominant, while in P. sativum, verbascose stood out. The total sugar content was higher in peas, especially in commercial varieties, which also showed elevated sucrose levels. Some local varieties combined high sugar content with favorable relative levels between RFOs and other sugars, making them valuable candidates for breeding programs. Linear discriminant analysis enabled classification and prediction of species and varieties, confirming the usefulness of soluble carbohydrates as tools for characterizing these plant materials. Full article