Search Results (3,155)

The HEROn magazine was created as an innovation project by the S-TEAM team for the 2024/2025 SUBMERGED season of the FIRST^® LEGO^® League Challenge category. The primary aim of the HEROn project was to implement game-based learning methods to enhance environmental awareness, particularly concerning the protection of our water resources. This initiative is designed to engage individuals from ages 9 to 99 in a creative and enjoyable manner. At the core of the HEROn project is a well-known game that challenges players to find the differences between two photos. This activity not only provides entertainment but also educates participants about the importance of protecting and preserving the aquatic environment. By discovering subtle differences between images, players become more attuned to environmental issues, which promotes a deeper understanding and appreciation of water conservation. The chapters of the HEROn magazine are thoughtfully organised into themes, each focusing on various aspects of water’s importance, its protection, and sustainable usage. Additionally, a random sample of participants was surveyed to gather opinions and feedback on HEROn magazine as part of the project and this research. This feedback is invaluable for assessing the magazine’s impact and for improving future editions to better serve the goals of raising environmental consciousness. The online HEROn questionnaire consisted of 10 items and employed a 5-point Likert scale for responses. Data were collected over a three-month period (28 January–28 April 2025), with 630 Hungarian respondents participating in the survey. The HEROn magazine was generally well received, with mean scores ranging from 4.2 to 4.6. Age-group differences were examined using nonparametric Kruskal–Wallis tests, with Dunn–Bonferroni post hoc comparisons. These analyses show statistically significant differences between adults (30–89) and the younger cohorts for aggregated awareness, design/engagement, and branding measures, while teenagers (9–15) and young adults (16–29) did not differ significantly from each other. The Find-the-Difference game showed the greatest variability across groups, with young adults giving the lowest mean. Full article

In window tracking mode, stray light and detector readout noise can submerge star spot signals in star sensor images. The resulting degradation reduces centroid extraction accuracy and may even cause extraction failure, thereby preventing precise attitude determination. This study uses the self-supervised spatiotemporal denoising model ASTERIS as the baseline. ASTERIS integrates 3D spatiotemporal inputs with a global attention mechanism for joint noise modeling, thereby providing stronger denoising and restoration capability than conventional methods such as multi-frame stacking. However, ASTERIS lacks adaptive compensation for subpixel jitter in on-orbit star images and has difficulty preserving the high-frequency morphology of star spots, affecting denoising performance and centroiding accuracy. To address these limitations, this study introduces two improvements: First, frame-by-frame spatial deformable convolution is incorporated into the decoder upsampling stage to adaptively compensate for subpixel offsets, actively suppress background noise, and lower the parameter count. Second, a complex-valued frequency domain loss with a high-frequency weighted mask is designed to jointly constrain the amplitude and phase spectra, thereby preserving high-frequency star spot details. Experimental results show that, for star images with extremely low signal-to-noise ratios, the proposed method improves the peak signal-to-noise ratio by approximately 17.8 dB and reduces the centroid localization error to approximately 0.1 pixels. This performance is substantially better than that of the original ASTERIS model, which improves the peak signal-to-noise ratio by approximately 9.5 dB and yields an error of approximately 0.4 pixels, and the multi-frame stacking method, which improves the peak signal-to-noise ratio by approximately 6.0 dB and yields an error of approximately 0.5 pixels. Under the simulated strong noise conditions considered in this study, the proposed method achieves effective centroid extraction, demonstrating its potential for on-orbit star sensor data processing. Future work will further address its engineering deployment. Full article

Carnivorous plants possess highly specialized trap structures that enable the acquisition of nutrients from captured animals. This study investigated whether the aquatic environment influences the architecture of glandular emergences (tentacles) in the submerged form of Drosera intermedia. Morphometric analyses were performed on tentacles from plants growing in sandy terrestrial habitats, emergent wetland habitats, and submerged aquatic habitats. Significant differences in tentacle morphology were detected among habitat types. Emergent plants generally developed the largest tentacles and tentacle heads, whereas submerged plants exhibited shorter marginal tentacles and smaller glandular heads. In contrast, the shape of both marginal and central tentacle heads remained relatively stable across habitats, indicating stronger developmental conservation of this trait. Nevertheless, the submerged form differed significantly in the morphology of central tentacle heads. These results demonstrate that aquatic conditions substantially modify the structure of carnivorous emergences, revealing pronounced phenotypic plasticity in the carnivorous syndrome of D. intermedia. The reduction in tentacle size under submerged conditions may reflect altered functional demands associated with prey capture, changes in mucilage effectiveness, and the mechanical constraints imposed by the aquatic environment. However, differences in light availability, nutrient status, and other habitat characteristics may also contribute to the observed patterns. At the same time, the persistence of glandular structures indicates the retention of the carnivorous apparatus despite prolonged submergence. This study highlights the remarkable developmental flexibility of D. intermedia and provides new evidence that trap morphology in carnivorous plants may be highly responsive to environmental conditions. Full article

This study reports cellulase production by Bacillus paralicheniformis using Plumeria alba leaf powder under submerged fermentation with a focus on systematic bioprocess optimization. Physical parameters were first optimized using a one-factor-at-a-time (OFAT) approach, followed by optimization of yeast extract, MgSO₄ and (NH₄)₂SO₄ via a central composite design (CCD) and response surface methodology (RSM). An artificial neural network (ANN) with a 5:3:1 network trained by the Levenberg–Marquardt algorithm further improved prediction of carboxylmethylcellulase (CMCase) and filter paper cellulase (FPase) activities. This study is the first to exploit Plumeria alba leaf powder as an untapped, low-cost lignocellulosic substrate for cellulase production by B. paralicheniformis and uniquely benchmarks RSM against ANN-based modeling to identify superior predictive frameworks for bioprocess optimization. Under optimized conditions (24 h, 4% w/v substrate, 1% v/v inoculum), the maximum FPase and CMCase activities reached 60.53 IU/mL/min and 332.10 IU/mL/min respectively. Partial characterization showed optimum FPase and CMCase activities at 50 °C and 70 °C, respectively, at pH 7.5. Enzymes also showed activation by NaCl and some select solvents while tolerating a broad range of metal ions. The enzymatic hydrolysis of P. alba biomass released 59.42 mg/mL total reducing sugars after 8hr, confirming efficient saccharification from a low-cost feedstock. The ANN model (R² = 97.59% for CMCase; 85.95% for FPase) outperformed RSM (R² = 85.95% and 78.25%, respectively), while radial basis function optimization reached 99.99%. These findings highlight B. paralicheniforms cellulase as a promising biocatalyst for biorefinery applications and demonstrate the value of integrating RSM and ANN for process optimization. Full article

Plant communities in reservoir drawdown zones experience highly altered hydrological regimes, and responses of locally dominant species shape the biodiversity and restoration trajectories of these artificial wetlands. The water-level fluctuation zone (WLFZ) of the Three Gorges Reservoir (TGR) is exposed to alternating flooding and drought, which strongly constrains both its vegetation and the biodiversity that depends on it. Cynodon dactylon dominates the herbaceous cover of the TGR WLFZ, but evidence on its stress responses remains fragmented across single-site studies. Following a PRISMA 2020 literature search and screening procedure, we synthesized 169 effect sizes from 12 qualifying experimental studies, covering biomass and morphological traits, photosynthetic gas-exchange parameters, chlorophyll content, and oxidative-stress indicators. Effect sizes were calculated as natural log response ratios (lnRR) and pooled with random-effects models; shallow and deep flooding were compared using subgroup analyses with bootstrap 95% confidence intervals. Flooding effects varied with water depth. Shallow flooding increased total biomass (+47.2%), whereas deep flooding reduced plant height (−46.5%) and root length (−22.3%). Plant height showed significant between-group heterogeneity (Q_between = 5.60, p = 0.045), indicating sensitivity to submergence depth. Flooding also increased malondialdehyde content (MDA) by 31.7%, whereas peroxidase activity (POD), superoxide dismutase activity (SOD), and photosynthetic gas-exchange parameters showed no consistent responses. Drought effects on total biomass, plant height, and total chlorophyll were non-significant, although inference was limited by a few drought-related entries. Deep flooding, therefore, appears to be a stronger constraint than drought for Cynodon dactylon in the TGR WLFZ, mainly through morphological suppression and increased oxidative damage. Given the dominant role of this species in the herbaceous layer, its depth-dependent decline is relevant both for biodiversity conservation in this artificial wetland and for elevation-based restoration planning. Full article

This study presents a simulation-based multiphysics design, modeling, and adaptive control framework for a dual-propulsion unmanned aerial underwater vehicle intended for aerial, near-surface, and fully submerged operation. The proposed platform uses four aerial rotors for flight and six underwater thrusters for submerged maneuvering, allowing medium-dependent actuation in air and water. Separate aerial and underwater six-degrees-of-freedom models are formulated and connected through a smooth altitude-dependent coordination strategy for the simplified near-surface region. Computational fluid dynamics is used to estimate submerged drag forces, while finite element analysis evaluates pressure-hull structural integrity at a depth of 20 m. At 0.2 m/s, the predicted horizontal and vertical drag forces are 1.62 N and 3.92 N, corresponding to quadratic damping coefficients of 40.5 and 98.0 N·s²/m². The FEA results show that PMMA provides a safety factor of 7.8, with a maximum displacement of 0.53 mm under hydrostatic loading. An adaptive backstepping controller with projected gain tuning, disturbance compensation, and constrained actuator allocation is developed. MATLAB/Simulink simulations demonstrate bounded trajectory tracking under nominal conditions, 20% parametric uncertainty, modeled disturbances, and a 0.5 m/s ocean current. Full article

Single-photon detection is a promising approach for low–slow–small Unmanned Aerial Vehicle (UAV) detection, holding great value in urban air defense and security monitoring. In complex urban environments, intense non-uniform building clutter and multi-echo aliasing easily submerge weak target signals, severely limiting traditional single-photon systems under low signal-to-background ratios. To address this, this paper proposes an urban-oriented detection strategy based on a free-running single-photon array, and designs a dual-optimized pulse position modulation laser detection and range image enhancement algorithm. By establishing temporal correlations via pulse sequence convolution, the algorithm effectively isolates weak UAV echoes from strong background clutter to break through detection limitations. Compared with the popular Markov correction method that often suppresses overlapping weak targets under strong reflections, the proposed method significantly improves small-target feature retention, successfully balancing background elimination and detection sensitivity. Field tests and quantitative evaluations demonstrate that the system reliably eliminates building clutter and achieves stable continuous tracking of weak UAV signals within 1.5 km, providing a highly robust and effective technical solution for urban low-altitude surveillance. Full article

Pectinases are a group of enzymes widely applied in agri-food processes. This study aimed to isolate and characterize pectinase-producing yeasts and yeast-like fungi from soil and humus samples collected in a Moroccan argan forest, a region characterized by arid to semi-arid climatic conditions, with emphasis on screening and evaluating their pectinolytic activity. Among nine isolated strains, four exhibited detectable pectinolytic activity on pectin agar medium. Two promising isolates were molecularly identified by ITS region sequencing as Coniochaeta pulveracea PX765016 and Coniochaeta ligniaria PX765017. Notably, C. pulveracea PX765016 showed the highest pectinolytic potential, with a pectinolytic degradation index of 4.2 on pectin agar. This strain also exhibited maximal pectinase production after 96 h of submerged fermentation in YEPD medium under optimized conditions of pH 4, 30–35 °C, and 0.5% (w/v) pectin. The crude enzyme obtained under these conditions exhibited a specific activity of 559.90 ± 11.62 U/mg. The enzyme was subsequently subjected to sequential purification comprising ammonium sulfate precipitation, dialysis, and gel filtration chromatography on a Sephadex G-100 column, yielding a 2.99-fold purification with a final recovery of 14%. The purified enzyme exhibited optimal activity at pH 6.0 and 40–55 °C, with a reaction time of 20 min. Kinetic analysis of pectin hydrolysis revealed a Michaelis–Menten constant (Km) of 7.33 mg pectin per mL and a maximum reaction velocity (Vmax) of 1666.7 U/mg. To the best of our knowledge, this is the first report of pectinase production by a member of the genus Coniochaeta, and the first characterization of pectinase activity from C. pulveracea. Full article

Seagrass meadows are important blue carbon habitats, but their patchy distribution in intertidal zones makes accurate UAV mapping difficult under shallow water cover and complex sediment backgrounds. This study developed a fine-grained semantic segmentation framework with explainability analysis to improve intertidal seagrass extraction from high-resolution UAV visible and multispectral imagery. Exposed seagrass (ESG) and shallow-submerged seagrass (SSG) were mapped separately to represent two observable intertidal states. Visible bands, multispectral bands, and vegetation indices were used as model inputs. U-Net and DeepLabV3+ served as baseline models, while UPerNet-ConvNeXtV2-Tiny was tested under the same settings. Kernel SHAP and permutation importance were used to assess feature contributions. UPerNet-ConvNeXtV2-Tiny achieved the best performance, with an overall accuracy (ACC), mean Intersection over Union (mIoU), and F1 score of 97.45%, 94.63%, and 97.23%, respectively. It outperformed the baseline models in suppressing background interference, preserving patch morphology, and reducing omission errors in weak response and boundary areas, while demonstrating better cross-scenario applicability in independent test areas. Explainability analysis showed that model discrimination was mainly associated with red and green-related features, especially RGB-R, MS-R, MS-G, RGB-G, and NGRDI. ESG and SSG showed different feature dependence patterns, indicating that high-resolution UAV imagery can support accurate seagrass mapping and reveal spectral differences between intertidal seagrass states. These findings provide a practical framework for UAV-based intertidal seagrass mapping and monitoring and offer guidance for feature selection and model explainability analysis. Full article

Mediterranean rivers experience various pressures that cause native fish populations to decline. This is the case of Achondrostoma asturicense, a threatened endemic species recently classified as "endangered" (EN) by the Portuguese Red Book. In northeastern Portugal, the main populations occur in the Carvalhais (Tua basin), Maçãs, and Angueira (Sabor basin) rivers. This study aimed to evaluate the effect of small weirs on the distribution, abundance, and habitat use of A. asturicense populations along the longitudinal gradient of River Angueira. Three river zones (Z1 to Z3) affected by small weirs were selected along the watercourse. In each zone, four sampling sites were distributed relative to the weir, as follows: A1—200 m downstream; A2—immediately downstream; A3—under the influence of the reservoir; and A4—200 m upstream (reference). Sampling was carried out in three seasons: winter, spring, and summer 2025. Physical–chemical (water), hydromorphological (habitats), and biological (fish) elements were assessed in accordance with the protocols of the Water Framework Directive. The results revealed the worst water quality in the summer season due to flow reduction, dissolved oxygen depletion, elevated conductivity, and high nutrient (N, P) concentrations, leading to eutrophication phenomena. The distribution and abundance of A. asturicense were negatively influenced by the presence of small weirs, which were dominated by the non-native species Lepomis gibbosus. PERMANOVA analysis (two-way, p < 0.05) identified significant differences (Pseudo-F = 28.349, p < 0.05) between sampling sites and river zones, and paired similarity analysis tests (ANOSIM; one-way, p < 0.05) confirmed that these differences occur only between the weir reservoir (A3) and the remaining sampling sites. A. asturicense showed a maximum length (Lmax) of 135 mm, isometric growth only in the upstream zone (Z1), and significant differences in body condition (0.75 < K < 0.84). This species showed a preference for rheophilic habitats, with coarse substrate and diversity of currents and distinct cover mainly guaranteed by submerged aquatic macrophytes. A. asturicense populations are severely affected in the River Angueira by habitat fragmentation, riparian degradation, pollution, invasive alien species (e.g., L. gibbosus, P. clarkii, N. vison), and climate change, justifying the development of mitigation and restoration measures for the conservation of natural habitats and native threatened species. Full article

The relationship between water and sediment in the lower reaches of the Yellow River is uncoordinated, leading to frequent floods. In this area, the floodplain is situated below the main channel and embankment foundations, increasing the likelihood of overbank flooding. Ecological protective forests serve as a nature-based mitigation measure by reducing flow velocities along embankments and lowering the risk of structural failure during near-bank flood events. To assess the role of ecological protective forests, laboratory experiments were conducted, and field data informed parameterization and geometry selection. A total of 24 scenarios were designed, combining four forest arrangements (A1, A2, A3, and A4), two submergence degrees (H₀/H = 0.5 and 1.0), and three water and sediment conditions. Results show that sediment deposition increases with vegetation density. Under constant vegetation density and embankment-aligned flow, a larger along-flow to cross-flow spacing ratio promoted deposition upstream, whereas a smaller ratio extended deposition further downstream. Deposition thickness was greater under fully submerged conditions than under semi-submerged conditions. Among the arrangements, sediment deposition effectiveness followed the order A1 > A2 > A4 > A3, with arrangement A1 providing the strongest promotion of deposition. Under varying flow–sediment conditions, the A1 arrangement enhanced sediment deposition by 6.8% to 20.6%. Flow structure was also modified: under semi-submerged conditions, the vertical profile of longitudinal velocity approximated a logarithmic distribution, whereas full submergence produced a different profile due to combined drag from tree trunks and canopy. Vertical sediment concentration profiles were similar under both submerged states, with minimum values near the water surface and maximum concentrations near the bottom. These changes confirm that ecological protective forests contributed to reducing flow velocity and diminishing sediment transport capacity. Full article

This paper presents a full-scale case study on real-time corrosion monitoring in an underground reinforced-concrete potable water tank built in 1968. The study aims to demonstrate how continuous electrochemical monitoring can support durability assessment and predictive maintenance in ageing water-retaining infrastructure, where direct inspection is often limited and exposure conditions are spatially variable. Fourteen monitoring points were installed in beams, columns and domes subjected to different exposure conditions. Corrosion potential, concrete resistivity, corrosion current density and temperature were recorded every 3 h and used to assess the corrosion state of the reinforcement. The monitored durability indicators were reinforcement section loss, estimated from corrosion current density using Faraday’s law, and corrosion-induced crack-width evolution, used as a serviceability-related indicator for maintenance planning. The results show that beams remained predominantly passive, with corrosion current densities below 0.1 µA/cm² and incremental sectional losses below approximately 2 µm during the monitoring period. Columns showed the highest vulnerability, particularly at lower elevations subjected to prolonged immersion, with estimated incremental section losses reaching approximately 4–6 µm and a clear correlation between submerged time and corrosion progression. Domes exhibited intermediate behaviour, with occasional activation events associated with environmental fluctuations. A multivariable model combining resistivity and temperature was used to interpret corrosion kinetics, while Faraday-based section-loss estimates were coupled with empirical crack-width models to forecast serviceability indicators up to 2045. These forecasts are presented as scenario-based maintenance-support indicators rather than deterministic predictions of future damage, since corrosion propagation and crack development may evolve nonlinearly under changing exposure conditions. The proposed approach demonstrates how continuous corrosion monitoring can be linked to durability limit-state assessment, enabling risk-informed and performance-based maintenance of critical water infrastructure. Full article

Seagrass meadows support critical coastal ecosystems, but corresponding species-level remote sensing data remain limited, particularly in the Arabian Gulf, where field spectral data for dominant taxa are extremely limited. We present the first multi-species spectral characterisation of three dominant seagrass species in the Kingdom of Bahrain—Halophila stipulacea (n = 46 spectra, 25 stations), Halodule uninervis (n = 34, 19 stations), and Halophila ovalis (n = 17, 8 stations)—measured with an ASD FieldSpec^® 4 Hi-Res spectroradiometer (Malvern Panalytical, Malvern, UK; 350–2500 nm) from samples collected across 29 geographic stations (52 species–station sampling units). All sample counts reported here underwent quality control. Kruskal–Wallis tests with Benjamini–Hochberg (BH) correction, Jeffries–Matusita (JM) distance, Hedges’ g, and linear discriminant analysis (LDA) were used to characterise inter-species differences. H. ovalis was clearly distinguished from both co-occurring species: the Hd. uninervis–H. ovalis pair showed a discriminating window of 692–1394 nm (mean |g| = 1.31, BH q = 0.000046), and that for the H. stipulacea–H. ovalis pair was 700–1376 nm (mean |g| = 1.21, BH q = 0.000285); the JM distances were 1.60–1.67. A secondary shortwave-infrared discriminating window (1607–1755 nm; mean |g| = 0.90, BH q = 0.006) was also identified for the Hd. uninervis–H. ovalis pair. The H. stipulacea–Hd. uninervis pair showed meaningful geometric separation (JM = 0.994) but no individually significant wavelengths at the available sample size. ASentinel-2-proxy LDA achieved 85.6% overall accuracy (balanced accuracy = 87.3%; macro area under the curve = 0.917), outperforming a Landsat-proxy model by 20 percentage points. For each species, both a best-overall index and a visible-range alternative optimised for submerged satellite remote sensing are reported. The primary indices achieved balanced accuracies of 0.877–0.924; the visible-range alternatives achieved 0.818–0.907. Performance degraded substantially under noise (σ ≥ 0.002: −7.5 percentage points [pp]) and wavelength misregistration (±2–3 nm shifts caused losses of 5.5–15.7 pp), calling for stringent calibration requirements. These results constitute the first multi-species spectral library for Kingdom of Bahrain seagrasses, supporting Sentinel-2-based species mapping in the Arabian Gulf. Full article

Cultivable fungi are important components of freshwater ecosystems, yet their diversity in Amazonian aquatic environments remains poorly explored. This study evaluated cultivable fungal communities associated with water, sediment, and submerged wood in the Negro, Solimões, and Tapajós Rivers, representing the major black-, white-, and clear-water systems of the Amazon basin, respectively. Samples were collected along 25 m transects, fungi were isolated on potato dextrose agar, grouped into morphotypes, and identified morphologically. Diversity was assessed using richness, Shannon, Simpson, Pielou, and Sørensen indices. Overall, 130 isolates and 75 morphotypes were recorded, with a predominance of morphotypes assigned to filamentous Ascomycota and widespread occurrence of Aspergillus and Penicillium. Solid substrates yielded greater fungal abundance and richness than water samples. Submerged wood from the Negro River showed the highest overall cultivable fungal abundance, whereas the Tapajós River showed the highest diversity in water and sediment and the highest richness in both substrates. The Solimões River showed stronger dominance by a limited number of morphotypes, particularly in submerged wood. Sørensen similarity values indicated low compositional overlap among rivers, especially for submerged wood communities, suggesting apparent differentiation among river-associated cultivable fungal assemblages. Together, these exploratory results suggest that substrate type, hydrochemical differences, and potential temporal effects may be associated with the structure of cultivable fungal communities in Amazonian rivers. Full article

Employing the WaveMIMO methodology, the present numerical study evaluates a submerged horizontal plate (SHP) device under the incidence of representative regular and realistic irregular waves associated with the sea state off the coast of Rio Grande, Brazil. The dual functionality of the SHP device is investigated, considering its operation as a breakwater (BW) and as a wave energy converter (WEC). The main focus of this study is to investigate the effects of numerical beach (NB) positioning on the hydrodynamic response of the SHP. The governing equations for mass, momentum, and volume fraction are solved using the finite volume method (FVM), while the water–air interaction is modeled through the volume of fluid (VOF) approach. The analysis assessed the influence of SHP length (L_p) using five different values. For the tested Rio Grande sea state, SHP geometry, two-dimensional numerical model, and adopted hydrodynamic indicators, the results show that the exclusive use of representative regular waves was not sufficient to reproduce the hydrodynamic trends obtained under realistic irregular waves. The SHP demonstrates its highest BW performance in reducing the significant wave height at 3L_p for representative regular waves and realistic irregular waves. As a WEC, it achieves its highest axial velocity at 3L_p for representative regular waves and 1.5L_p and 2L_p for realistic irregular waves. The performance of the SHP as BW-WEC is the highest at 3L_p for regular waves and 2.5L_p for realistic irregular waves. In contrast to previous work, in which the NB was kept at a fixed position, the present study indicates that the downstream computational-domain configuration, including the relative positioning between the SHP and the NB, is an important factor affecting the monitored hydrodynamic response and should be carefully defined in CFD wave-flume simulations. Full article