Search Results (4,117)

The apple tree (Malus domestica Borkh.) is one of the most economically important fruit crops worldwide, and its productivity is increasingly affected by water deficit. Understanding genotype-specific physiological responses to water deficit is important for improving water deficit resilience in apple. This study evaluated the effects of water deficit (14 days) and subsequent rehydration (7 days) on eight apple genotypes (‘Galaval’, ‘Idared’, ‘Rubinstep’, ‘B11’, ‘HL 308’, ‘HL 2010’, ‘HL 2350’, and ‘HL 827’) grown under semi-controlled container conditions. Physiological parameters, including pigment content, gas exchange, chlorophyll fluorescence, water use efficiency, and leaf water status, were assessed. Water deficit affected all measured parameters, with responses differing among genotypes. In most cases, water deficit was associated with reduced gas exchange and chlorophyll fluorescence, as well as changes in pigment content and leaf water status. However, the magnitude and direction of these responses varied depending on genotype. Some genotypes (e.g., ‘HL 2350’ and ‘B11’) showed more stable physiological performance under water deficit conditions, while others (e.g., ‘Idared’ and ‘Rubinstep’) exhibited more pronounced changes. Rehydration resulted in partial recovery of physiological parameters, although values generally did not reach control levels within the experimental period. The results indicate substantial genotypic variability in physiological responses to short-term water deficit under controlled conditions. These findings provide useful information for further research on water deficit responses in apple; however, additional studies under field conditions and including growth and yield parameters are required to assess the agronomic relevance of the observed differences. Full article

Human astroviruses are small, non-enveloped RNA viruses belonging to the family Astroviridae. Among the four species known to infect humans, the species Mamastrovirus hominis (the classical human astroviruses, formerly MAstV1) is associated with gastrointestinal illness worldwide, while three more recently identified species have been linked to lethal central nervous system infections. High substitution rates and recombination drive their rapid evolution, yet recombination patterns in classical human astroviruses remain poorly characterized. This study systematically analyzes patterns and temporal dynamics of natural recombination in classical human astroviruses. Publicly available genomes of classical human astroviruses were analyzed to identify recombination hotspots. Recombinant forms were defined as stable phylogenetic lineages unaffected by recombination, and their half-lives were estimated based on time-scaled phylogenies (BEAST2v2.7.7). Recombination in classical human astroviruses occurred most frequently at the ORF1b/ORF2 junction, but also within ORF1a, at the ORF1a/ORF1b junction, and within ORF2. Only the 3′-part of ORF1a and a fragment of ORF1b exhibited robust temporal signal, yielding substitution rates of 2.35 × 10⁻³ and 2.14 × 10⁻³ s/s/y, respectively. The half-lives of recombinant forms varied considerably by genomic region: longest for exchanges between the parts of ORF1a (21 years), intermediate for ORF1a/ORF1b recombinants (7–9 years), and shortest for ORF1ab/ORF2 recombinants (2.5–3.6 years). The estimated half-lives for recombinants align with those reported for human enteroviruses and noroviruses. These findings highlight the dynamics of the generation of astrovirus diversity and may inform advanced surveillance of emerging strains. Full article

This study evaluates the extent and quality of tax transparency reporting among the Top 40 firms listed on the Johannesburg Stock Exchange (JSE), distinguishing between mandatory tax disclosures and voluntary transparency practices. A qualitative, disclosure-based research design was employed, involving content analysis of publicly available annual reports, integrated reports, and sustainability reports. A structured tax transparency framework grounded in stakeholder theory and legitimacy theory, and adapted from prior empirical studies was applied to systematically assess tax-related disclosures. Findings indicate high compliance with mandatory tax disclosure requirements, reflecting strong adherence to accounting standards and regulatory obligations. In contrast, voluntary tax transparency shows considerable variation: firms predominantly provide narrative, policy-oriented, and governance-related information, while detailed, forward-looking, and jurisdiction-specific disclosures remain limited. The discussion highlights that voluntary transparency is shaped by stakeholder expectations, legitimacy concerns, and perceived reputational and commercial risks, leading to selective disclosure. Regulatory compliance emerges as the primary driver of tax reporting, whereas voluntary practices are influenced by firm-specific and contextual factors. The results hold relevance for investors, regulators, and policymakers seeking greater corporate accountability, and for standard-setters aiming to enhance the consistency and depth of tax transparency reporting. Overall, the study enriches the limited literature on corporate tax transparency in emerging markets by offering contemporary empirical evidence from South Africa and identifying key areas requiring improvement in voluntary tax disclosures. Full article

This work presents an enhancement to the Dynamic Traffic Management (DTM) framework aimed at reducing signaling overhead between SDN controllers in multi-domain cloud environments. This extension is based on the ability to transmit information regarding the amount of balanced traffic and the optimal transfer pattern. In the baseline periodic mode, the system regularly exchanges the compensation vector ($\overrightarrow{C}$) and the reference pattern ($\overrightarrow{R}$). To minimize communication, we define non-periodic modes that restrict $\overrightarrow{C}$ updates and eliminate $\overrightarrow{R}$ transmission entirely. Within these restricted signaling modes, we further distinguish between reactive and proactive operational schemes. Our experimental results demonstrate that reducing the visibility of optimization goals ($\overrightarrow{R}$ and only sign of $\overrightarrow{C}$) and cutting signaling frequency in this manner maintains a comparable level of cost-efficiency. Specifically, the initial evaluation shows that DTM typically decreases transit costs by 8% to 15%, with maximum savings reaching up to 29% when compared to the worst-case default BGP path scenario. These findings suggest that the DTM mechanism can maintain its economic efficiency even with significantly reduced inter-domain coordination. Full article

Vehicle-to-grid (V2G) technology has emerged as a key enabler for coupling large-scale electric vehicle (EV) deployment with the operation of smart energy systems. By allowing bidirectional power and information exchange between EVs and the grid, V2G transforms EVs from passive loads into distributed energy resources capable of supporting grid flexibility, reliability, and renewable energy integration. However, the practical realization of V2G remains challenged by technical complexity, system coordination, user participation, and regulatory constraints. This paper presents a comprehensive review of V2G integration from a system-level perspective. Rather than focusing solely on individual technologies, the review examines how V2G is embedded within smart energy systems, emphasizing the interactions among EVs, aggregators, grid operators, energy markets, and end users. Key enabling technologies, including bidirectional charging, aggregation mechanisms, communication frameworks, and data-driven control strategies, are discussed in relation to their system-level roles and limitations. The impacts of V2G on grid operation, energy management, and market participation are analyzed, with particular attention to reliability, battery lifetime, and user trust. Furthermore, this review identifies critical open issues that hinder large-scale deployment, spanning infrastructure readiness, standardization, economic incentives, and cybersecurity. Emerging application scenarios, such as building-integrated V2G, fleet-based services, and artificial intelligence (AI) supported coordination, are also discussed to illustrate potential evolution pathways. By synthesizing technological developments with system-level impacts and unresolved challenges, this paper aims to provide a structured reference for researchers, system planners, and policymakers seeking to advance the integration of V2G into future smart energy systems. Full article

This study explores how environmental, social and governance (ESG) disclosure relates to analysts’ forecast accuracy in Saudi Arabia, focusing on the ESG disclosure guidelines introduced by the Saudi Stock Exchange (Tadawul) in 2021. It suggests that ESG disclosure enhances corporate transparency, decreases information asymmetry, and provides analysts with additional non-financial information that can improve the earnings forecast quality. Furthermore, the introduction of ESG guidelines is likely to enhance the consistency and reliability of sustainability reporting, thereby strengthening the informational environment of the capital market. Based on a sample of listed firms from 2017 to 2024 and employing panel regression techniques, including fixed-effects and two-step system generalized method of moments (GMM) estimations, the results indicate that a higher ESG disclosure is associated with lower analyst forecast errors, reflecting an improved forecast accuracy. The findings also reveal that the forecast accuracy increased following the ESG guidelines’ introduction and that the connection between ESG disclosure and analysts’ forecast accuracy became greater after the implementation of the guidelines. Our results demonstrate the informational value of ESG disclosure and suggest that ESG reporting initiatives can boost the quality of financial information in emerging markets. Full article

Human serum albumin (HSA) is the most abundant protein in plasma, and the redox state of circulating HSA has been used as a biomarker of systemic oxidative stress (OS) for decades. While informative, many traditional biomarkers of OS measure short-lived or downstream products of oxidative damage that offer limited perspectives on the dynamic and integrated processes that govern systemic redox biology within human populations. By moving beyond single-analyte damage markers and towards coordinated patterns of protein modifications, HSA-Cys³⁴ adductomics offers a systems-level approach that simultaneously captures change in multiple layers of OS. Because of its high abundance in plasma and HSA’s unique and highly reactive single free thiol (Cys³⁴), HSA-Cys³⁴ serves as an ideal sentinel target for monitoring reactions with reactive oxygen species (ROS), reactive nitrogen species (RNS), and electrophilic species produced by endogenous metabolism and responses to exogenous chemical exposures. The reaction of HSA with ROS, RNS, and reactive electrophiles yields a diverse array of protein modifications, including direct oxidation products (sulfenic, sulfinic, and sulfonic acid), low molecular weight thiol-disulfide exchange, and lipid peroxidation (LPO)-derived reactive aldehydes. With a mean residence time of about a month, these accumulated adducts serve as an integrated picture of oxidative and electrophilic stress that together function as a molecular record of systemic redox physiology. Previous studies using high-resolution mass spectrometry-based adductomics have enabled global untargeted analysis of HSA-Cys³⁴ modifications, yielding an expansive inventory of novel redox signatures of environmental stressors and disease states. In this paper we review the chemistry and biology underlying OS-related modifications of HSA-Cys³⁴ and highlight the important role of HSA-Cys³⁴ adducts as integrative biomarkers of OS at the interface of molecular biology, exposure assessment, and public health research. Full article

As a crucial pathway for optimizing land factor allocation, farmland transfer plays a pivotal role in implementing the “storing grain in land and technology” strategy and safeguarding national grain security. Based on panel data from 30 provinces in China spanning 2009 to 2023, this study employs a two-way fixed effects model and a Spatial Durbin Model (SDM) to systematically examine the mechanisms, heterogeneity, and spatial spillover effects of farmland transfer on grain production capacity. The results indicate that: (1) Farmland transfer significantly enhances grain production capacity, and this conclusion remains robust after multiple robustness and endogeneity tests. (2) Farmland transfer boosts grain production capacity by promoting cultivated land connectivity and facilitating the substitution of machinery for labor; however, the accompanying non-grain tendency and land governance disputes exert inhibitory effects on capacity release. (3) Transfers to farming households and professional cooperatives, as well as the adoption of leasing and informal exchange arrangements, exhibit the strongest positive effects on production capacity, and the scale-efficiency gains of farmland transfer are particularly pronounced in major grain-consuming areas. (4) Improvements in a region’s farmland transfer level drive the enhancement of grain production capacity in neighboring regions through the diffusion of management experience and the sharing of social services. This study provides empirical evidence and policy insights to optimize farmland transfer mechanisms and safeguard food security. Full article

This paper aims to navigate the complexity inherent in the concept of place by defining and highlighting the role of place-informed education across different international contexts: the periphery in Northern Israel, coastal areas of England, and rural Montana in the United States. Using a thematic analytic framework, we conducted a cross-context comparison of three case studies in order to identify each locale’s unique definitions and meanings of place, producing a portrait of the similarities and differences among the three international contexts. Following the ‘Simplicity–Accuracy Paradox’ and recognizing the ‘cost of oversimplification’, we explored complexity as a basis for action, which enables the creation of a process in which the strengths and limitations of the place both have an important role to play in any intervention or action to mitigate and/or enhance the consequences of distance from urban centers. The proposed strategies presented in the paper are based on embracing the complexity of place for place-informed education, and include context-responsive policy design, targeted workforce strategies, international learning exchanges, and policy and classification reform. These processes may serve as a guide for action among educators, policymakers and researchers, supporting a mindset of place-informed education where complexity is embraced and where challenges of place may also offer solutions. Full article

Topsoil features within a depth of 0–10 cm are vital for making soil management decisions that affect crop production. However, the use of these soil features to predict soil organic carbon (SOC) at 10–20 cm requires further investigation. The study aims to predict SOC at 10–20 cm using total nitrogen (total N), pH, cation exchange capacity (CEC), and SOC at 0–10 cm and select a suitable model for predicting SOC. This study was conducted using data from a long-term tillage, winter wheat (Triticum aestivum L.)-fallow experiment established in autumn 1970. Treatments included moldboard plow, stubble mulch, no-till, and native sod, each replicated three times. Soil samples were collected from each plot at depths of 0–10 cm and 10–20 cm in April of 2010 and 2011. Models were fit using ordinary least squares (OLS), least absolute shrinkage and selection operator (LASSO), random forests, and Bayesian additive regression trees (BART). Using root mean square error (RMSE), SOC was predicted with an accuracy of 1.44 g kg⁻¹ or relative RMSE (rRMSE) of 13.5%. This was achieved with the OLS model that used total N, pH, and CEC as predictors. The good performance of the OLS model over more flexible machine learning approaches suggests that the information predictors provide about the response variable (SOC) is approximately linear. As the agricultural dataset was small (n = 24), the less complex model reduced the chances of overfitting while keeping the variance relatively low. Random forests and BART had an rRMSE greater than 21%. Statistical models could be used to estimate SOC at 10–20 cm and reduce destructive soil analysis methods. Full article

This study investigates the dynamic patterns of global financial risk transmission across 11 major economies and four key asset classes (stocks, bonds, foreign exchange, and gold) using daily data spanning 2012 to 2025. To capture the non-linearities of extreme market stress, we construct a multilayer directed network based on least absolute shrinkage and selection operator (LASSO) penalized quantile regression at the 5% lower tail. We estimate tail risk spillovers using a one-year rolling window approach and identify systemically important nodes via an extended PageRank algorithm applied to the resulting adjacency tensors. Empirical results suggest that the rankings of systemically important countries undergo significant re-orderings during crisis periods. We find robust statistical evidence that the Herfindahl–Hirschman Index (HHI) of risk concentration provides forward-looking information regarding structural polarization and systemic fragility. These observed associations remain consistent across alternative quantile thresholds, varying lag lengths, and alternative rolling window specifications. Our results provide granular insights for policymakers monitoring cross-asset contagion and provides a framework for institutional investors to assess potential tail-risk hedging strategies within an increasingly interconnected multilayer architecture. Full article

Wi-Fi networks used in smart grids are essential for enabling communication between smart meters and data aggregation units. A key challenge, however, is the ability to hide the existence and traffic patterns of these communications, so that sensitive information exchanges cannot be easily detected or intercepted. Unfortunately, most existing solutions do not provide support for traffic prioritization and steganographic channel encryption. In this paper, we propose a novel covert channel with Quality of Service (QoS) and encryption support for smart grid environments based on the IEEE 802.11 standard. We introduce an original steganographic approach that leverages the backoff mechanism, the Enhanced Distributed Channel Access (EDCA) function, frame aggregation, and the StegoPaddingCipher algorithm. This design ensures QoS-aware traffic handling while enhancing security through encryption of the transmitted covert data. The proposed protocol was implemented and evaluated using the ns-3 simulator, where it achieved excellent performance results. The system maintained high efficiency even under heavily saturated network conditions with additional background traffic generated by other nodes. The proposed covert channel offers an innovative and secure method for transmitting substantial volumes of QoS-related data within smart grid environments. Full article

Zeolite P was synthesized by hydrothermal treatment of coal fly ash and applied to the individual removal of six heavy metals (Pb²⁺, Ni²⁺, Cu²⁺, Cr³⁺, Hg²⁺, Cd²⁺) from aqueous solutions. Characterization by SEM-EDS, FTIR, BET, XRD, zeta potential, and XPS revealed a BET surface area of 30 m²/g, Si/Al ratio of 1.63, and pH_pzc of 3.2. Batch experiments at the natural solution pH of 3.9 in all cases (C₀ = 10, 100, 200 mg/L; t = 1–60 min) yielded an apparent selectivity sequence at C₀ = 200 mg/L of Hg²⁺ (10.47 mg/g) > Pb²⁺ (9.12) > Ni²⁺ (2.18) > Cr³⁺ (2.05) > Cu²⁺ (1.82) > Cd²⁺ (1.26), where Hg²⁺ and Pb²⁺ reached near-equilibrium while the remaining metals were still approaching it at t = 60 min. Weber–Morris and Boyd analyses confirmed three sequential diffusion stages with a concentration-dependent shift from film to intraparticle diffusion control through the narrow GIS channels (3.1 × 4.5 Å). Ion exchange was identified as the dominant mechanism based on convergent kinetic, diffusion, XPS, and selectivity–electronegativity evidence (r = +0.76). A leakage-free machine learning framework combining physicochemical descriptors with experimental variables was tested under three cross-validation strategies of increasing stringency. Gradient Boosting achieved R² = 0.979 ± 0.043 (repeated K-Fold) and R² = 0.880 on six completely held-out kinetic curves. An ablation study confirmed that physicochemical descriptors are essential (experimental-only models yielded negative R²). SHAP feature importance rankings were consistent with established ion exchange selectivity theory. This work demonstrates that group-level validation, physics-informed descriptors, and systematic ablation testing are able to identify both the capabilities and the boundaries of small-dataset ML when testing for metal kinetics prediction. Full article

Adenine nucleotide translocase (ANT) has traditionally been defined as the ADP/ATP exchanger of the inner mitochondrial membrane. However, accumulating mechanistic evidence reveals a substantially broader functional spectrum that extends beyond nucleotide transport. In this review, we integrate these advances into a unified conceptual framework that positions ANT isoforms as modulators of mitochondrial bioenergetics, quality control, and cellular communication. Beyond its canonical exchange activity, ANT influences permeability transition thresholds and membrane potential stability, participates in regulated uncoupling and redox control, and contributes to inner membrane organization and cristae integrity. ANT further modulates TIMM23-dependent protein import and PINK1–Parkin-mediated mitophagy, thereby shaping mitochondrial quality control decisions. In addition, ANT regulates mitochondrial nucleic acid release and inflammasome activation, linking bioenergetic imbalance to innate immune signaling. Emerging evidence for alternative subcellular localizations suggests that ANT-dependent signaling extends mitochondrial state information to extracellular and intercellular contexts. Collectively, these findings support an expanded view of ANT as a multifunctional modulator linking mitochondrial energetic state to stress adaptation, inflammatory signaling, and tissue-level communication. Full article

Preterm birth interrupts critical phases of lung development and is associated with long-term alterations in respiratory structure and function. While bronchopulmonary dysplasia (BPD) has traditionally been considered the principal determinant of adverse outcomes, accumulating evidence indicates that prematurity per se contributes substantially to persistent pulmonary impairment. Lung function trajectories in preterm-born children frequently track along lower percentiles from infancy into adolescence and early adulthood, with limited catch-up growth and increased vulnerability to chronic airflow limitation. Assessment of lung function requires a developmentally tailored approach, as feasibility and interpretability vary across age groups. In infancy, non-volitional techniques such as tidal breathing flow-volume loop analysis and raised-volume rapid thoracoabdominal compression allow early evaluation of respiratory mechanics. During toddlerhood, methodological limitations persist, although emerging technologies may expand feasibility. In preschool children, impulse oscillometry enables detection of small airway dysfunction, often preceding spirometric abnormalities. From school age onward, spirometry, body plethysmography, diffusing capacity, and multiple breath washout provide complementary information on obstructive, restrictive, and gas-exchange impairments. Longitudinal studies demonstrate that reduced lung function is not confined to children with BPD and may predispose to early-onset chronic obstructive pulmonary disease-like phenotypes. Early identification of abnormal trajectories and modifiable risk factors supports structured long-term follow-up and preventive strategies. Standardization of age-specific assessment protocols and harmonization of reference values are essential to improve risk stratification and optimize long-term respiratory outcomes in this vulnerable population. Full article