Search Results (180,486)

Soil erosion is recognised as one of the most pervasive forms of land degradation across the Western Balkans (WB), a 208,052 km² region for which its erodible substrates, contrasting climates, and long history of land-use pressure produce highly variable erosion regimes. This study delivers the first regional-scale assessment of soil erosion susceptibility for the entire WB through a cloud-based implementation of a modified Erosion Potential Method (EPM) in Google Earth Engine (GEE). The computation was performed at 30 m resolution and aggregated across 9524 catchments derived from the EU-Hydro database, with the dimensionless erosion coefficient (Z) serving as the primary susceptibility metric. The modelled patterns reveal a strong north–south asymmetry in erosion intensity: The highest country-level coefficients were obtained for Albania (0.47), North Macedonia (0.38) and Montenegro (0.37), while Serbia (0.29) and Bosnia and Herzegovina (0.28) recorded lower regional means. About 19.8% of the WB area falls within catchments classified as highly to very highly susceptible, with such basins concentrated along the Adriatic-facing mountain front and across the Aegean headwaters. Validation was carried out at three complementary levels, including point-based statistical validation on 1379 field- and orthophoto-verified points distributed across the WB, which yielded an AUC = 0.828. Although the proposed framework should not be considered a substitute for fine-scale, field-based modelling, it provides a transparent, reproducible, and scalable basis for regional screening, catchment prioritisation, and the design of soil-conservation and land-management interventions across the WB. Full article

As we move further into a more digital supply chain, we have seen tremendous improvements in terms of efficiency, but we have also seen a rise in the risks that data vulnerabilities pose, particularly for intermediary supply chain nodes. As a result, traditional security measures have proven inadequate in protecting critical data that flows through these intermediary supply chain nodes, making them more susceptible to possible security breaches and tampering. In this paper, we introduce a novel solution that utilizes cryptography and Artificial Intelligence (AI)-powered predictive modeling for the security of supply chain data. Unlike other solutions that only protect endpoint data, our solution provides a more comprehensive security solution that extends cryptography for intermediary supply chain data, making it more secure and protected from possible breaches and tampering. To further improve our solution, we have utilized AI models, namely, XGBoost, Random Forest, and LightGBM, for predictive modeling. To prevent target leakage, features arithmetically derived from the recovery-duration target were excluded from the predictor set prior to training. The results indicate that, once the leakage-affected features are removed and hyperparameters are properly tuned, all five models achieve modest but genuine predictive accuracy, with $R^2$ values in the range of 0.542–0.552. The best-performing model on this leakage-audited feature set is XGBoost, with an $R^2$ value of 0.5525 and a test RMSE of 38.16 days, closely followed by Linear Regression and Ridge Regression (RMSE = 38.22 days, $R^2$ = 0.5512), with the practical difference between the two being small (0.06 days RMSE) despite being statistically consistent across ten random splits. This demonstrates the solution’s effectiveness in reducing security risks while maintaining realistic, leakage-free predictive accuracy. Full article

An anthropomorphic patient-derived 3D-printed breast phantom (4.8 cm compressed thickness, 12.2% volumetric breast density) was evaluated for image-quality assessment in contrast-enhanced mammography (CEM). It comprises four 1.2 cm plates printed via fused filament fabrication (PLA/ABS). Five replicates of one of the plates (target) containing a glandular-tissue surrogate and four cavities for iodinated disks with same iodine area density per plate (0.2–0.5–0.75–1.0–1.5 mg/cm²) were fabricated. As a reference, a homogeneous PET-G phantom was printed. CEM images (low-energy (LE), high-energy (HE), and DES) were acquired in three different systems. Iodine signal linearity (mean pixel value, signal difference, signal-difference-to-noise ratio (SdNR)) and background cancellation (residual signals, texture cancellation coefficient (TCC), parameter β from noise power spectrum (1D-NPS)) were estimated. Evaluation across the three systems demonstrated the phantom provides appropriate measurements of iodine signal linearity (R² > 0.986, based on mean values across the four inserts) and background cancellation (TCC:0.04–0.11). Fitting 1D-NPS = αf^−β within 0.25–1.0 mm⁻¹ yielded β values ≈ 3.1–4.0, compatible with the literature, for patient LE and HE images, whereas DES reduced β to ≈1.1. In the homogeneous phantom, β remained invariant between LE and DES images (β ≈ 0.6). The local glandular ratio at each position of the iodinated disks enabled evaluating the impact of background on iodine signal. Full article

The increasing frequency and complexity of zoonotic disease outbreaks highlight the limitations of traditional surveillance systems operating within specific disciplines. Although the One Health approach provides a widely accepted framework for addressing interconnected human, animal, and environmental health threats, its practical implementation remains constrained by fragmented data systems, limited interoperability, and challenges in translating multisectoral information into timely, actionable intelligence. Advances in artificial intelligence, geospatial analytics, Earth observation, climate monitoring, genomic epidemiology, and digital health technologies provide new opportunities to strengthen integrated preparedness and anticipatory decision-making. Building on emerging international One Health Intelligence (OHI) initiatives, this perspective presents an operational framework for implementing One Health Intelligence Systems (OHIS) and proposes the One Health Intelligence Maturity Model (OHIMM) as a conceptual tool to support the progressive development and assessment of intelligence capabilities. The framework integrates multisectoral information from human, animal, wildlife, environmental, climatic, laboratory, genomic, and socioeconomic domains to support risk assessment, early warning, preparedness, and response at the human–animal–environment interface. Using West Nile Virus in Europe and Rift Valley Fever in Africa as illustrative examples, we demonstrate how existing surveillance and multidisciplinary intelligence components can be integrated to strengthen situational awareness and anticipatory public health action while discussing the governance, interoperability, and implementation challenges that remain. We argue that operationalizing OHI through structured implementation frameworks and maturity assessment can support the development of more predictive, adaptive, and resilient systems for zoonotic disease preparedness while providing a foundation for future validation and implementation research. Full article

Background/Objectives: Active-duty military personnel may use caffeinated and sweetened beverages to manage alertness and fatigue, but co-occurring beverage behaviours are rarely examined. We identified beverage-frequency co-consumption profiles in Spanish Army personnel and tested their cross-sectional associations with self-reported sleep and habitual physical fatigue. Methods: This cross-sectional study included 1155 active-duty Spanish Army personnel. Latent classes were estimated from ordinal frequencies of caffeinated beverages, sugar-sweetened beverages, and energy drinks; these indicators represented frequency categories rather than caffeine dose, sugar intake, or standardized serving size. Adjusted outcome models incorporated classification uncertainty and controlled for demographic, occupational, training, hydration, alcohol, smoking, and recruitment-cohort covariates. Results: A three-class solution identified lower-frequency (47.7%), intermediate-frequency (28.3%), and higher-frequency (24.0%) profiles. Compared with the lower-frequency profile, the higher-frequency profile was associated with 0.230 h less sleep per night (95% CI −0.416 to −0.045; q = 0.022), 2.129 percentage points lower sleep efficiency (95% CI −4.177 to −0.082; q = 0.041), and 0.395 points greater habitual physical fatigue (95% CI 0.077 to 0.714; q = 0.022). Sensitivity analyses were directionally consistent. Conclusions: Beverage-frequency responses clustered into three profiles. The higher-frequency profile was cross-sectionally associated with shorter self-reported sleep, lower sleep efficiency, and higher habitual physical fatigue. The sleep-duration contrast was approximately 13.8 min/night, but the clinical or perceptible relevance of the sleep-efficiency and fatigue differences cannot be established from these self-reported measures. Prospective studies with product-specific dose and timing data are required to establish temporality and practical relevance. Full article

Background: The optical losses in the form of reflections, parasitic absorption, and scattering limit photovoltaic efficiency. This review examines plasma-assisted surface engineering as an effective tool for improving light management in solar cells. Plasma-based methods, including etching, oxidation, deposition, and texturing, enable precise control of surface morphology and chemistry, lowering reflectance, enhancing light trapping, and passivating defects. Methods: In contrast to wet-chemical or high-temperature processes, plasma processes are dry, low-temperature, scalable, and can be used with silicon, perovskite, thin-film, and organic solar cells, as well as tandem structures. The fundamentals of optical losses are described, along with the principles of radio-frequency (RF), inductively coupled plasma (ICP), microwave, and atmospheric plasma systems and their distinctive advantages for controlling ion and reactive-species generation. Key applications reviewed include black-silicon texturing by ICP reactive-ion etching (ICP-RIE), anti-reflective/passivation coatings by plasma-enhanced chemical vapor deposition (PECVD), and interface activation by atmospheric plasma. Results: Among performance improvements are a reflectance of less than 2%, a photocurrent increase of 10–20%, and longer carrier lifetime. Conclusions: The advantages of plasma compared to lithography and sol–gel processes are in the precision and affordability of the method. The difficulties include damage caused by the processing, uniformity over extensive areas, and environmental stress resistance. Future directions rely on low-temperature plasmas for flexible PV, machine-learning-guided process optimization, and hybrid plasma–laser systems. This synthesis of otherwise fragmented studies is intended to support the implementation of plasma-based methods in next-generation, high-efficiency, and sustainable solar production. Full article

This systematic review and meta-analysis investigated resisted sled training (RST) efficacy compared to unresisted sprint training (UST), alongside the moderating effects of sprint distance, sled load, and surface. Following PRISMA guidelines, PubMed, Web of Science, Scopus and SPORTDiscus were searched up to May 2026. Risk of bias was assessed via the PEDro scale. Twelve studies (N = 324) were included. Data were analyzed using Correlated Robust Variance Estimation (CRVE). Overall, RST reduced sprint times compared to UST (Hedges’ g = −0.250, p = 0.046; I2 = 0.0%). While time reductions were significant for early acceleration (≤10 m; g = −0.360, p < 0.001), and not for longer-distance outcomes (>10 m; g = −0.168, p = 0.293), the between-distance interaction was non-significant (p = 0.094). Moderate loads (g = −0.352, p = 0.062) and indoor gym floors (g = −0.495, p = 0.096) showed larger point estimates than natural grass (g = −0.180) and synthetic tracks (g = −0.197). In conclusion, no statistically significant moderating effects of distance, load, or surface were demonstrated. Because training surfaces influence the actual mechanical stimulus, prescribing sled loads based on velocity decrement (%Vdec) rather than percentage of body mass (%BM) is a promising hypothesis to standardize resistance across terrains, requiring confirmation via future prospective trials. PROSPERO: CRD420261415365. Full article

Background/Objectives: Tarin exhibits immunomodulatory and antiproliferative properties against several tumor cell lines. Nano-encapsulation in liposomes enhances its therapeutic potential by improving protein stability, bioavailability, and sustained release. Previous studies demonstrated that nano-encapsulated tarin induces cell cycle arrest, migration inhibition, apoptosis, and autophagy in triple-negative breast cancer cells; however, the molecular mechanisms underlying these effects remain poorly understood. To investigate the proteomic response elicited by nano-encapsulated tarin, MDA-MB-231 cells were treated for 24 and 48 h. Methods: Intracellular proteins were extracted, digested with trypsin, and analyzed by label-free LC-2D-MS/MS using HDMSE acquisition. Differentially expressed proteins were identified and quantified using the Progenesis QI platform, and then functional classification and pathway enrichment analyses were performed. Results: A total of 2818 proteins were identified, of which 2150 displayed time-dependent modulation following treatment. After 24 h, cells exhibited an adaptive stress response profile characterized by increased DNA repair proteins (CHEK1, CDK12), migration/remodeling factors (LAMA4, CTTN, A2M), and immune/cell cycle regulators (PER2, HLA-B), while antioxidant proteins (SOD1, GPX1) and BRCA1 were reduced, indicating oxidative stress and DNA damage. After 48 h, the proteomic profile shifted toward cell death, with increased PARK7, OPA1, ATL3, and CASP8 expression, disruption of DNA repair and cell cycle regulators (CHEK1, CDK12, MSH6, KIF2C), and decreased migration-related proteins (LAMA4, CTTN, ITGB3, A2M). Conclusions: Nano-encapsulated tarin promotes a time-dependent transition from early adaptive stress responses to apoptosis, autophagy, cell cycle disruption, and loss of migratory capacity. These findings provide novel insights into the molecular mechanisms underlying tarin antitumoral activity and support its potential as a promising therapeutic strategy against triple-negative breast cancer. Full article

The emergence of seekRNA- and bridgeRNA-guided recombination has introduced a distinct paradigm in genome engineering by coupling programmable RNA-directed DNA recognition with recombinase-mediated insertion, excision, inversion, and genomic rearrangement without canonical double-strand breaks. Since their discovery in 2024, these systems have progressed rapidly from bacterial mobile genetic elements and mechanistic characterization to structural elucidation and programmable genome engineering in human cells. However, these advances remain distributed across foundational and rapidly emerging studies, creating a need for an integrated molecular perspective on their mechanisms, technological development, and position within contemporary genome engineering. This review synthesizes the molecular architecture, RNA-guided recognition, strand-exchange mechanisms, programmability, and engineering of seekRNA and bridgeRNA systems, with particular emphasis on complementary human-cell advances involving ISCro4 and engineered IS621. Whereas ISCro4 systems have enabled multikilobase DNA insertion, genomic excision, and near-megabase inversion, the enIS621–tebRNA platform has enabled scarless kilobase-scale integration across multiple human cell types, including proof-of-concept functional CD19 chimeric antigen receptor and factor IX gene insertion. The review further integrates recent genome-scale bacterial rewriting and Targetable Recombinase Assisted DNA Exchange (TRADE)-mediated DNA replacement, while benchmarking RNA-guided recombination against conventional site-specific recombination, clustered regularly interspaced short palindromic repeats (CRISPR)-based editing, Programmable Addition via Site-specific Targeting Elements (PASTE), CRISPR-associated transposases, and emerging large-payload genome-writing strategies, including kilobase-scale nickase-targeting (KNIT) editing, Prime Assembly, engineered R2 retrotransposons, and TransCRISTI. This comparative framework highlights a broader transition from programmable sequence modification toward direct engineering of genomic architecture, while identifying recognition-site constraints, mismatch-tolerant recombination, unintended recombination products, delivery, and genome-wide specificity as key translational barriers. By integrating foundational mechanisms with recent mammalian engineering, genome-scale bacterial rewriting, large-payload technologies, and emerging computational design strategies, this review provides a contemporary framework for defining the distinctive capabilities, current limitations, and future development of programmable RNA-guided DNA recombination. Full article

Background: Children with Autism Spectrum Disorder (ASD) Level 1 face barriers to sports participation that remain insufficiently understood. Methods: This qualitative study explored parental perspectives on barriers and facilitators to physical activity following participation in a multicomponent physical activity program (MCPAP). Semi-structured interviews were conducted with 17 parents (11 mothers, 6 fathers) of boys aged 8–12 years with ASD Level 1 who completed a 12-week MCPAP in Valencia, Spain. Data were analyzed using reflexive thematic analysis. Results: Seven themes were identified, capturing both barriers and facilitators: (1) parental fears and previous negative experiences; (2) parents’ accounts of their sons’ avoidance of physical activity in relation to bullying and social exclusion; (3) methodological barriers linked to non-adapted teaching approaches; (4) challenges with non-specialized professionals; (5) limited availability of programs specifically designed for children with ASD Level 1; and (6) location and accessibility concerns; and (7) parent-perceived facilitators and outcomes associated with the MCPAP, including transfer to natural contexts. Conclusions: Parents described children with ASD Level 1 as an “invisible population” with regard to existing sports opportunities. Parents further perceived that specialized programs with trained professionals, adapted methodologies, and small-group formats supported their sons’ sustained engagement in physical activity. These findings reflect parental interpretations and were not triangulated with standardized outcome measures. Full article

In Christianity, the tree symbolizes both human and divine life and is closely associated with wisdom and with the knowledge of good and evil, whose root is love. This article examines the symbolism of the tree with a twofold aim. First, and more extensively, it explores the process of secularization that transformed the understanding of life and wisdom in the early modern period through a comparative analysis of the symbolism of the tree in Augustine, Sabunde, and Descartes. Second, it offers a brief reflection on the contemporary world, the legacy of modernity, in which the human condition has come to be represented by figures that contrast sharply with the symbolism of the tree: the castaway, the vagabond, and the tourist. Drawing on the symbolism of the tree and the thought of Augustine, Sabunde, and Descartes, the article examines three fundamental dimensions of human existence: self-knowledge; the human relationship with nature, with others, and with God; and, finally, the articulation between the active and the contemplative life. Full article

Onshore power supply (OPS) can reduce emissions from auxiliary engines during port stays, but limited electrical capacity and investment resources require vessel prioritisation. This study develops the Index for the Prioritisation of Onshore Power Implementation (ILAPP) and applies it to ferry and Ro-Ro traffic at the Port of Algeciras. The dataset comprised 3901 valid calls by 27 vessels during two periods in 2026; 25 vessels were retained for energy, emissions and EU Emissions Trading System (EU ETS) modelling. ILAPP integrated six criteria: call frequency, navigation fuel consumption, cumulative berth time, net CO₂ reduction through OPS, gross tonnage and EU ETS exposure. Weights from a five-member expert panel were combined with objective CRITIC weights. A 60/40 expert–CRITIC configuration was selected after comparison with alternative hybrid schemes. Under the central scenario, OPS demand reached 18.32 GWh and yielded a net reduction of 11,370.11 tCO₂, equivalent to 77.5% of conventional at-berth emissions. Total modelled CO₂-related EU ETS allowance exposure for eligible vessels was approximately EUR 1.72 million, while displaced at-berth emissions represented EUR 0.74 million in potentially avoided allowance obligations. Kattegat ranked first, followed by Tanger Express, Villa de Agaete, Nápoles and Wasa Express. Temporal agreement was weak, although Kattegat remained first in both periods and in the aggregated sample. The results show that call frequency alone is insufficient and that correlated energy, environmental and regulatory criteria require balanced weighting. ILAPP provides a transparent vessel-level first-stage framework for identifying short-term and structural OPS priorities, while final investment decisions require additional technical, electrical and economic assessment. Full article

Vegetation dynamics are highly sensitive to climate variability and constitute a key indicator of ecosystem condition, particularly in arid and semi-arid environments where field observations are often limited. This study investigated the spatiotemporal dynamics of vegetation and their relationships with climatic factors in the Quaraqum Watershed during 2001–2022 using multi-source remote sensing datasets. Vegetation dynamics were characterized using the Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery, Land Surface Temperature (LST) was obtained from MODIS products, and precipitation data were obtained from the CHIRPS dataset. Spatial and temporal patterns and trends were examined using Geographic Information System (GIS) techniques, while the relationships between NDVI and climatic variables were quantified using Pearson correlation and multiple linear regression analyses. The results revealed a pronounced west-to-east decrease in precipitation accompanied by increasing temperature across the watershed. Annual precipitation reached maximum values of 389.20 mm in 2019 and 370.79 mm in 2009, whereas the lowest values, 172.50 mm and 171.50 mm, were recorded in 2008 and 2021, respectively. Spring was the wettest season, whereas summer was the driest. Vegetation cover was highest in spring and exhibited an increasing long-term trend, while autumn and winter showed the lowest vegetation cover and declining trends. Correlation analysis revealed a strong positive relationship between NDVI and precipitation and a weaker negative relationship between NDVI and LST. These results suggest that precipitation availability was more strongly associated with vegetation variability than thermal conditions. Multiple regression analysis further indicated that precipitation was the primary climatic variable explaining annual NDVI variability, while the inclusion of LST did not substantially increase the explained variance of the model. Overall, these findings highlight the dominant role of moisture availability in shaping vegetation dynamics in the Quaraqum Watershed, with thermal conditions representing an additional environmental factor affecting vegetation responses. Full article