Search Results (14,117)

Spatial and temporal patterns of terrestrial water storage (TWS), and their relationship with groundwater levels, were investigated with the Gravity Recovery and Climate Experiment (GRACE) satellite data, the Global Land Data Assimilation System (GLDAS) land surface model results, and climate observations for the Murray–Darling Basin (MDB). The results show that: (1) TWS displays a clear temporal variability: a negative TWS anomaly with a declining trend during 2002–2009, a positive TWS anomaly with a decreasing trend during 2010–2017, and a period of mixed positive and negative TWS anomalies being accompanied by an increasing trend from 2018 to 2025; (2) five dominant cluster patterns were identified that explain the spatial variability of temporal TWS across the MDB; (3) overall, TWS temporal variability is strongly correlated with rainfall, although it is weak at certain locations; (4) TWS is also influenced by evaporation (both actual and potential evapotranspiration, AET and PET) and runoff, and a combined model significantly improves the overall performance in explaining TWS temporal variability; and (5) TWS-derived groundwater storage changes show both similarities and differences in comparison with groundwater level observation changes, reflecting complex hydrogeological processes and the influence of human activities such as groundwater extraction. These findings provide valuable insights to support improved groundwater resource management with GRACE satellite information and land surface models. Full article

Space debris mitigation is a pivotal endeavor essential for sustaining human space exploration. To address the challenges posed by irregularly shaped, variably sized, and dynamically unpredictable debris in orbit, this paper proposes a mechanical design and motion control strategy for an omniwheel-based driving system. The mechanical architecture and kinematic principles of the system are elaborated in detail, complemented by the formulation of tailored motion control algorithms. First, the fundamental architecture of the driving subsystem is introduced, and the linear mapping between the uniformly distributed triad of omniwheels and the spherical drive is derived. Building upon this foundation, the kinematic transmission from the three evenly spaced driving subsystems to the contact sphere is established. This leads to the derivation of the overall linear mapping relationship between the nine uniformly distributed omniwheels and the contact sphere’s motion, thereby enabling precise trajectory tracking of the contact sphere via omniwheel actuation. Finally, comprehensive experimental validation was conducted in two phases. The first phase evaluated the fidelity and stability of the driving subsystem’s simulation model, as well as the accuracy of the kinematic mapping. Results demonstrate that the simulation model is highly stable and reliable. Under identical desired trajectories, the Root Mean Square Error (RMSE) between theoretical calculations and simulations was 4.082 × 10⁻⁴, while the RMSE between theory and physical prototypes was 0.0032. These results confirm that the motion errors remain within acceptable tolerances and the kinematic mapping is accurate. For the spherical end-effector, under the same trajectory conditions, the RMSE values among theoretical calculations, simulations, and physical prototypes were 0.0929 and 1.62, respectively. These findings validate the derived linear kinematic mapping, demonstrating its efficacy in precise motion control, which lays the foundation for future on-orbit detumbling tasks. Full article

Forecasting fine particulate matter with a diameter of 2.5 μm (PM_2.5) is critically important due to its adverse effects on human health and environmental sustainability. Although ground-based monitoring stations provide accurate measurements, their limited spatial coverage restricts large-scale PM_2.5 assessment, especially in complex urban regions. Consequently, aerosol optical depth (AOD) derived from satellite imagery, combined with advanced deep learning (DL) techniques, has emerged as an effective alternative by offering wide spatial coverage and rich spatio-temporal information. This paper proposed an optimization-driven fuzzy transformer–deep belief network (ODFT-DBN) for accurate PM_2.5 air pollution prediction. The proposed framework integrates a fuzzy inference module to model uncertainty and nonlinear environmental relationships, a transformer encoder to capture long-range spatio-temporal dependencies, and a DBN to extract hierarchical features and improve prediction robustness. In addition, a novel multi-objective gray wolf optimizer (NMOGWO) is employed to jointly optimize the model hyper-parameters and fuzzy membership functions. The proposed approach is implemented for the city of Tehran, Iran, using meteorological variables, topographical features, ground-based PM_2.5 measurements, and satellite-derived AOD data. The ODFT-DBN model is compared with several benchmark methods, including bidirectional encoder representations from transformers (BERT), transformer, long short-term memory (LSTM), gated recurrent unit (GRU), convolutional neural network (CNN), DBN, and extreme gradient boosting (XGBoost). Experimental results demonstrate that the proposed framework achieves superior predictive performance, attaining an R² value of 0.94 and root mean square error (RMSE) of 0.8 μg/m³. Scatter plot analyses indicate a strong agreement between predicted and observed PM_2.5 values, while the proposed model exhibits low variance, stable convergence behavior, and acceptable computational time. Overall, the results confirm the effectiveness, robustness, and practical applicability of the proposed ODFT-DBN framework for spatio-temporal PM_2.5 forecasting. Full article

This study investigates the relationship between economic growth, health expenditure, institutional quality, gross fixed capital formation, and foreign direct investment in EU countries outside the euro area over the period 2000–2024. The analysis is grounded in neoclassical and endogenous growth theory, with particular emphasis on the role of institutional quality as a conditioning factor in the growth process. Methodologically, this study employs an integrated empirical time-series framework focusing on selected health, institutional and investment-related determinants of growth, including linear and nonlinear unit root tests, structural break analysis, and an Autoregressive Distributed Lag/Error Correction Model (ARDL/ECM) approach to capture both long-run equilibrium relationships and short-run dynamics. ECM-based Granger causality tests are further applied to examine the direction of causal interactions. The results confirm the existence of a long-run cointegration relationship across all countries, although the magnitude and direction of the effects vary considerably. Gross fixed capital formation exerts a robust positive influence on economic growth, while foreign direct investment mainly affects growth in the short run and is highly sensitive to external shocks. Health expenditure contributes to growth through human capital formation, with predominantly lagged effects. Institutional quality is associated with growth dynamics, although the direction and strength of this relationship vary across countries and should be interpreted in light of feedback effects identified in the causality analysis. Overall, the findings highlight significant cross-country heterogeneity and underscore the importance of institutional quality in enhancing the effectiveness of investment and public spending for sustainable economic growth. Full article

Accessory proteins of SARS-CoV-2 play crucial roles in viral pathogenesis, yet their structural properties remain elusive. ORF7b, a small accessory protein comprising only 43 amino acids, is widely assumed to parallel the structure–function relationships of its SARS-CoV ortholog based solely on sequence homology. In this study, we challenge this paradigm through direct physicochemical and structural characterization. Sequence analysis and electrostatic profiling reveal that the SARS-CoV-2 protein is a macromolecular polyanion with a net charge of −4 at neutral pH, featuring a diffuse negative surface that is highly responsive to pH changes. Complete 3D structures generated via ab initio modeling display a helical core flanked by two highly fluctuating, disordered termini. Residue Interaction Network (RIN) topology and Normal Mode Analysis (NMA) identified specific hinges governing these flexible extremities. Furthermore, the calculated dipole moment vector is tilted outward by 24°, misaligning with the central axis. Molecular dynamics simulations suggest that while the soluble structure is highly stable in water, it undergoes severe distortions and insufficient solvation within a membrane-mimetic environment. Thermodynamic association profiles and verified interactomic data from BioGRID reveal a strong propensity for ORF7b to participate in liquid–liquid phase transitions alongside human and viral partners. Taken together, these unique properties suggest that ORF7b operates as a dynamic peripheral membrane protein rather than a sedentary transmembrane component, providing a fresh framework for future therapeutic targeting. Overall, these in silico findings shift the current paradigm on ORF7b2 topology and provide a robust, physically grounded framework that identifies specific molecular priorities for future in vitro and in vivo validation. Full article

Extreme temperatures are an emerging public health concern due to their significant impact on humans, yet the evidence remains limited in tropical countries. This study examined the non-linear relationship between ambient temperature and non-accidental and cause-specific mortality in two northern parts of Peninsular Malaysia, from 2011 to 2019. Daily mortality and meteorological data were analyzed using a quasi-Poisson Generalized Linear Model with a Distributed Lag-Non-Linear model to estimate the relationship between temperature and mortality. A U-shaped and J-shaped relationship was observed for the cumulative effects of 21-day lag periods for Kedah and Penang, respectively. The minimum mortality temperature (MMT) at 27.4 °C in Kedah and 28.2 °C in Penang was observed. Extremely high temperatures were associated with an increased non-accidental mortality, with a 16% increase at cumulative lag days 0–3 in Kedah and a 21% increase at cumulative lag days 0–7 in Penang. Vulnerable groups included individuals with respiratory diseases, the elderly, both genders and those residing in both urban and rural areas. These findings highlight the acute impact of heat on mortality in Malaysia and underscore the need for targeted public health interventions. Strengthening heat-health warning systems, improving healthcare preparedness, and prioritizing vulnerable populations are essential to mitigate the health impacts of rising temperatures in tropical regions. Full article

Introduction: Breast milk is the best food for a growing infant during the first 6 months of life. The presence of trans fatty acids (TFAs) in breast milk can interfere with the synthesis of long-chain polyunsaturated fatty acids (LC-PUFAs), increasing the risk of developing, among other issues, asthma or atopic dermatitis. TFAs are not synthesised de novo in the human body. Their content in breast milk may be a good marker of short-term dietary intake of these compounds by breastfeeding mothers. However, the literature shows differences in the assessment of the relationship between dietary TFAs intake and TFAs content in breast milk. Furthermore, the decrease in the TFAs content in food observed recently seems to make it impossible to use Craig-Schmidt’s formula to estimate the TFAs content in the diet or in breast milk. The aim of this study was to confirm the possibility of using TFAs content in breast milk as a marker of their short-term intake within the breastfeeding mother’s diet, together with an attempt at preliminary quantitative determination of the relationship between these parameters. Materials: The study material was collected from a single breastfeeding mother and included 10 breast milk samples and 10 samples of daily food rations reconstructed based on the 24 h food consumption survey. Methods: The content of fatty acids, including TFAs, was determined by gas chromatography–mass spectrometry (GC-MS). Results: The TFAs content in the whole-day mother’s diet and in 100 mL of breast milk ranged from 0.11 to 0.54 g/day and from 0.02 to 0.07 g, respectively. A strong statistically significant (p < 0.05) positive correlation between these parameters was found. Equations for an exploratory linear relationship between the TFAs content in a breastfeeding mother’s diet and the concentration of these fatty acids in breast milk have been developed. Due to the small number of samples, these data should be interpreted very cautiously and validated in a larger cohort. Conclusions: This single-participant pilot study suggests that TFAs content in breast milk may be a marker of the dietary intake of these compounds from the previous day. It seems that the dietary habits of breastfeeding mothers of twins are a significant factor influencing the composition of breast milk and, consequently, the nutritional quality of breastfed infants. Full article

Background: Melanoma incidence is rising rapidly worldwide and stands out due to its high lethality. Despite advances in clinical treatment and in understanding melanoma-sensitive genes and molecular pathogenesis, a specific area of ongoing research is the connection between stress-related β-adrenergic receptors (ARs), hypoxia, and neovascularization in melanoma tumor progression. This exploratory study aimed to investigate the expression of β3-AR, HIF-1α, and CD31 in several cellular subsets of atypical melanocytic lesions and their interplay in promoting melanoma malignancy. Methods: Twenty-seven patients with melanocytic lesions at different stages that were surgically removed were retrospectively selected; clinical-pathological and dermoscopic data were collected. Results: Immunohistochemical and digital evaluation revealed a significant upregulation of β3-AR in malignant melanoma melanocytes and in macrophages from invasive >pT1a melanomas compared to dysplastic nevi. Increased HIF-1α expression in malignant melanocytes and CD31 expression levels in >pT1a melanomas were observed. Ulcerated lesions exhibited a higher percentage of β3-AR, HIF-1α, and CD31 expression. Pearson correlation analysis revealed positive associations among these markers in human malignant melanoma, suggesting a potential relationship between adrenergic signaling, hypoxia, and tumor vascularization. Conclusions: These exploratory findings suggest that β3-AR, HIF-1α, and CD31 may represent interconnected components of the melanoma microenvironment. Unraveling these interactions in larger, independent cohorts and functional studies may provide additional insights into melanoma biology and help define their potential translational relevance. Full article

This study acknowledges the role of high-involvement work practices (HIWPs) in promoting proactive behavior among public organization employees, addressing the need to obtain further insights into the mechanisms and identify contingencies (i.e., both conditional and individual factors) that might impede the effectiveness of such practices. This builds on emerging empirical studies in the public management literature by drawing on social exchange theory and social cognitive theory to empirically test the impact of HIWPs on employees’ proactive behavior, using data collected through a two-wave, time-lagged survey design with a one-month interval from Turkish public organizations. The mediating role of public relations values was also examined, along with the moderating roles of role breadth self-efficacy and employees’ use of normative public values. Relying on 554 data obtained from Turkish public organization employees, this study finds that HIWPs positively impact employees’ proactive behavior and public relations values. Public relations values positively impact employees’ proactive behavior and partially mediate the link between HIWPs and employees’ proactive behavior. Role breadth self-efficacy moderates the positive relationship between HIWPs and public relations values, with the relationship being stronger for employees with high role breadth self-efficacy than for those with low. Employees’ use of normative public values moderates the positive link between public relations values and employees’ proactive behavior, with the relationship being stronger for employees with high use of normative public values than for those with low. The main theoretical and practical implications of the study’s outcomes are outlined and discussed, along with important future research directions. The findings highlight the importance of human-centric organizational practices in fostering public value in VUCA-D environments. By enabling proactive behavior, public organizations can enhance adaptability, support value co-creation with citizens, and strengthen trust in public service systems. Full article

Cognitive neuroscience has addressed the understanding of human brain processes through numerous techniques and psychological paradigms. In general, different types of tasks have been used depending on the specific cognitive operation under study. Since these tasks are usually designed to register responses at the single-trial level, the most common methodological approach to electroencephalography (EEG) is to obtain event-related potentials (ERPs). Crucially, the linear analysis methods associated with ERPs often overlook the intrinsic non-linear and multiscale dynamics of brain activity. Hence, to better characterize brain activity, there is increasing interest in the study of the non-linearity and complexity of EEGs. Given that experiments relating cognitive processing and EEG complexity are still scarce, this work is a narrative review of studies in which non-clinical cognitive processing, such as memory, perception, or attention, is addressed using complexity measures. Here, we focus on EEG metrics derived from the concepts of fractality, information, and randomness across different temporal and spatial scales. We discuss how these measures complement more classical analyses, try to integrate the findings using a predictability–regularity framework, and finally, we point out possible future directions with which to advance current knowledge about the relationship between cognition and EEG complexity. Full article

The aim of the study was to assess the level of implementation of the Industry 4.0 and Quality 4.0 concepts in manufacturing enterprises in Poland and Slovakia, as well as to identify the main barriers, supporting factors, and organizational effects related to digital and quality transformation. The study was conducted using a qualitative–quantitative approach based on a multiple case study strategy and the matched-pair method. The analysis covered 10 manufacturing enterprises (5 from Poland and 5 from Slovakia) representing various industrial sectors. Research triangulation was applied, including a diagnostic questionnaire, semi-structured interviews, analysis of organizational documents, and direct observation. Two synthetic indicators were developed: the Industry 4.0 Readiness Index (I4RI) and the Quality 4.0 Maturity Index (Q4MI). The results indicate a moderate level of implementation of both Industry 4.0 and Quality 4.0 in the analyzed enterprises, with Polish companies achieving slightly higher scores than Slovak enterprises. The highest level of advancement was observed in the area of technologies and automation, while the lowest concerned data integration and the use of analytics. The analysis revealed a strong positive relationship between the level of Industry 4.0 implementation and Quality 4.0 maturity, as well as the positive impact of both concepts on selected operational performance indicators, such as OEE, delivery timeliness, and defect rates. The obtained results confirm the complementary nature of Industry 4.0 and Quality 4.0 and highlight the need for a more integrated and human-centric approach to the digital transformation of manufacturing enterprises in Central and Eastern Europe. Full article

This study investigates the asymmetric and heterogeneous effects of renewable energy, non-renewable energy, capital stock, labour, and trade openness on CO₂ emissions in BRICS countries over the period 1991–2022. The study applies a panel nonlinear autoregressive distributed lag (PNARDL) model to capture short- and long-run asymmetries, complemented by a panel quantile nonlinear ARDL (QNARDL) to assess distributional heterogeneity. Robustness is ensured using Fully Modified Ordinary Least Squares (FMOLS) and Robust Least Squares (RLS) estimators. The study is grounded in the Environmental Kuznets Curve (EKC) and Just Energy Transition Theory. The results reveal a stable long-run cointegrating relationship among the variables, with a significant error correction mechanism confirming convergence toward equilibrium. Renewable energy consumption consistently reduces CO₂ emissions in both the short and long run, while non-renewable energy significantly increases emissions, exhibiting strong asymmetric effects. Capital stock shows mixed dynamics, increasing emissions in the short run but reducing them in the long run when directed toward productive and efficient investments. Labour is found to reduce emissions in the long run, highlighting the role of human capital in supporting cleaner production. Trade openness generally increases emissions, reflecting energy-intensive trade structures. Quantile results confirm heterogeneity, with stronger renewable energy effects at higher emission levels and greater environmental gains from reducing fossil fuel dependence than from increasing it. The FMOLS and RLS estimations confirm robustness, reinforcing the negative relationship between renewable energy and emissions and the positive impact of non-renewable energy. The study recommends accelerated renewable energy deployment, fossil fuel phase-down strategies, and targeted green capital investment. It further emphasizes grid modernization and energy storage systems to enhance renewable integration, alongside labour reskilling and green trade policies. These coordinated strategies are essential for achieving sustainable decarbonization in BRICS economies. Full article

Background/Objectives: Polycystic ovary syndrome (PCOS) is increasingly recognized as a condition associated with cardiometabolic risk, yet its relationship with subclinical atherosclerosis in premenopausal women remains unclear. This systematic review aimed to synthesize and critically appraise the available evidence on the association between PCOS and markers of subclinical atherosclerosis. Methods: A systematic search of PubMed/MEDLINE, Embase, Scopus, Web of Science, and the Cochrane Library was conducted for studies published between January 2021 and January 2026. Eligible studies included premenopausal women with PCOS and assessed direct vascular markers or validated surrogate indicators of subclinical atherosclerosis. Data were synthesized narratively following PRISMA guidelines. Results: Nine studies were included, comprising five human clinical studies and four bioinformatics analyses. Evidence from imaging-based studies demonstrated increased carotid intima-media thickness, reduced wall shear stress, and a higher prevalence of subclinical vascular abnormalities in women with PCOS, particularly in some hyperandrogenic phenotypes. In contrast, adolescent populations showed predominantly metabolic and inflammatory alterations without clear structural vascular changes. Biochemical studies reported adverse lipid profiles and elevated atherogenic markers, while mechanistic studies highlighted inflammatory and mitochondrial pathways. Conclusions: Current evidence suggests that PCOS may be associated with early vascular alterations in premenopausal women; however, findings are limited by heterogeneity and observational designs. Further large-scale, phenotype-stratified prospective studies using standardized vascular assessments are needed to clarify cardiovascular risk in this population. Full article

The present study investigates the relationship between human perception, multisensory gastronomic experiences, and technological mediation within the context of gastrotourism. The research introduces the concept of G@strotourism as a perception-centered and digitally mediated experiential tourism framework, where tourist experiences are shaped through the interaction of sensory engagement, experiential memory, and digital technology. A quantitative methodology was employed, with data collected from 942 international tourists who had visited Greece at least once. EFA, CFA, and SEM analyses were conducted to examine the relationships among pre-trip perceptions, memorable food experiences, technologically enhanced memories, loyalty, and behavioral intention. The findings provide preliminary evidence that technologically enhanced gastronomic experiences influence memory formation, emotional attachment to destinations, and future tourist behavior. The study contributes to the literature on perception-centered tourism experiences by highlighting the roles of sensory perception, memory processes, and digital mediation in gastronomic tourism, and by discussing their implications for tourism experiences enhanced through digital technologies. Full article

Flash flood events are among the most critical hydrological hazards in arid and semi-arid regions, posing extreme threats to critical infrastructure, human safety, and sustainable development plans. This paper evaluates the flash flood susceptibility of the Al’Ataya catchment, a key watershed on the southern Red Sea coast, using an integrated geospatial analysis approach. To assess and quantify the flood hazard, we investigated 15 morphometric parameters for 24 particular sub-catchments within a sixth-order drainage system. Two complementary methods, the Morphometric Ranking Method and El-Shamy’s approach, were utilized to classify the catchment into different flood susceptibility levels. Results from the Ranking Method identified seven sub-catchments (SC-2, SC-3, SC-6, SC-7, SC-8, SC-9, and SC-19) as having high flood hazard levels, mainly driven by large watershed areas, steep slopes, and high relief ratios. In contrast, El-Shamy’s approach resulted in a different evaluation, identifying sub-catchments in Zone B (SC-23, SC-16, SC-17, SC-15, SC-6, SC-20) as high hazard sub-catchments due to the particular relationship between the bifurcation ratio parameter and the drainage density and stream frequency parameters. The integration of the two methods suggests that the susceptibility factor is controlled by the combined influence of a low drainage density and steep mountainous terrain draining toward the coastal zone. These results provide a spatial model for flood mitigation and early warning systems, supporting Saudi Vision 2030 through improvement to the development of southern urban centers such as Al’Ataya and Sabya. Full article