Search Results (214)

This study presents a high-resolution, multi-proxy palaeoenvironmental reconstruction of the Tövises fen at Pocsaj, Hungary, utilising lithostratigraphical, geochemical, malacological, and palynological analyses supported by radiocarbon dating. The sedimentary sequence documents the transition from a Late Glacial fluvial system (c. 19,000–16,000 cal BP) to a cut-off meander and subsequent oxbow lake, eventually evolving into a peat-forming fen. Malacological and palynological data reveal the co-occurrence of cold-tolerant Late Pleistocene elements and the early appearance of thermomesophilous taxa at the onset of the Holocene. This suggests that the favourable microclimate of the adjacent loess-covered high bank and the humid alluvial plain functioned as a cryptic refugium for temperate broad-leaved trees and associated fauna during the Late Glacial. Anthropogenic impact is traceable from the Mesolithic, characterised by Corylus management, intensifying through Neolithic agriculture to a peak during the Roman Imperial Period. Geochemical markers in the upper peat sequence reflect increased biomass and medieval habitation, while recent malacofaunal shifts indicate progressive desiccation. Despite modern drainage attempts, the Tövises fen remains a biodiversity hotspot of high conservation value, preserving relict wetland communities. Full article

Accurate and reproducible delineation of stream bankfull geometry remains a persistent challenge in environmental planning. To address this gap, we developed the Cross-Sections and Dimensions Tool, a semi-automated, slope-based method for extracting stream cross-sections and estimating bankfull width, elevation and depth using high-resolution elevation data. The tool applies a configurable slope threshold to identify bank edges, generates perpendicular cross-sections from a stream centreline, and stores all outputs in a structured geodatabase to ensure transparency and reproducibility. Validation against manually delineated bankfull polygons across 191 km of stream length in Greater Melbourne, Australia, demonstrated strong spatial agreement, with an average F1 score (a measure of prediction-observation overlap) of 74% and a mean absolute error of 0.64 m in bankfull elevation. The tool was most reliable in larger streams (Strahler order 5 and above) with low to moderate vegetation canopy cover (<80%). We also investigated the practical visibility limits of small or indistinct channels typically encountered by human mappers and verified that the tool did not produce unrealistic channel delineations. This approach advances geomorphic feature extraction by grounding bankfull delineation in deterministic geometry rather than hydrological recurrence or data-driven modelling. In practice, it enables scalable, transparent, and repeatable analysis of stream morphology for ecological assessment, infrastructure planning, and waterway management. Full article

The mathematical characterization of non-stationary signals remains a significant challenge, particularly when impulsive components are obscured by high-dimensional noise and structural coupling. This paper proposes an application-driven mathematical methodology for a learnable discrete wavelet transform (LDWT) that combines classical multi-resolution analysis with task-optimized data-driven adaptivity. Rather than introducing entirely new foundational theory, our approach strategically relaxes constraints from orthogonal wavelet theory within the non-perfect reconstruction filter bank framework, enabling controlled spectral decomposition optimized for supervised fault diagnosis. We introduce a specialized regularization term based on the half-band property to ensure spectral complementarity and minimize cross-band correlation, while a Jacobian-based stabilization approach is formulated to ensure the convergence of filter coefficients during optimization. The proposed algorithmic architecture, LDBRFnet, features a dual-branch encoder system designed to capture the mathematical synergy between sub-band-level global statistics and time-domain local morphology. This dual-view representation effectively mitigates feature leakage and overconfidence in classification. Theoretical analysis and numerical experiments demonstrate that the learned filters satisfy the frequency-shift property and maintain robust spectral partitioning even under low signal-to-noise ratios. Validation on complex vibration datasets confirms that the framework achieves superior diagnostic accuracy (over 95.5%) and computational efficiency, reducing model parameters by 96.7% compared to state-of-the-art baselines. This work provides a generalizable mathematical approach for adaptive signal decomposition and robust pattern recognition in interdisciplinary applications. Full article

This paper provides a comparative analysis of the economic crises in Argentina and Lebanon to derive policy-relevant lessons for the design of IMF-supported adjustment programs in fragile economies. Using a structured comparative case study approach, the study examines crisis dynamics, policy responses, and socioeconomic outcomes across both countries, with particular attention given to exchange rate collapse, banking sector distress, public debt, inflation, unemployment, and poverty. The findings suggest that programs centered primarily on macroeconomic stabilization and fiscal austerity, without adequate attention to institutional capacity, social protection, and debt restructuring, risk deepening economic contraction and social vulnerability. The Argentine experience shows that IMF-supported adjustment in institutionally fragile environments may fail to restore confidence or deliver sustainable recovery when reform sequencing is weak and complementary domestic policies are absent. For Lebanon, where the crisis is deeper and compounded by governance failures and geopolitical instability, IMF engagement appears necessary but insufficient on its own. The paper concludes that a sustainable recovery requires a hybrid strategy combining external financial support with country-specific reforms, including exchange rate unification, banking sector restructuring, debt resolution, stronger governance, and targeted social protection. Full article

Urban districts along major rivers are undergoing rapid transformation, yet long-term evidence on how redevelopment reshapes land cover and vegetation structure remains limited in post-socialist cities. This study examines the spatio-temporal evolution of land use and land cover (LULC) and vegetation dynamics along the Sava River corridor in Belgrade from 1990 to 2024. CORINE Land Cover (CLC) datasets were combined with Landsat-derived NDVI and MSAVI time series, while high-resolution Esri Wayback imagery was used for visual interpretation and qualitative corroboration of the detected land-cover and vegetation patterns. Beyond conventional NDVI/LULC assessments, the study integrates multi-decadal spectral trends with functional vegetation structure classification to evaluate canopy continuity and ecological configuration under contrasting redevelopment models. Results reveal a pronounced divergence between the two riverbanks. The left bank (New Belgrade) maintains stable land-cover composition and consistently higher NDVI and MSAVI values, indicating preserved green infrastructure and sustained canopy continuity. In contrast, the right bank (Belgrade Waterfront) experienced substantial land-cover conversion after 2006, with a statistically significant decline in vegetation greenness (NDVI −0.020 dec⁻¹, p < 0.001) and a marked increase in impervious surfaces. MSAVI-based functional classes indicate a shift from mixed low vegetation to predominantly sealed land, while tree canopy remained persistently low throughout redevelopment. The findings demonstrate measurable ecological simplification and canopy loss, even where nominal green areas remain present. By providing a rare multi-decadal, spatially explicit comparison of two contrasting planning paradigms within the same river corridor, the study contributes new empirical evidence on how governance and redevelopment models shape riparian ecological trajectories and sustainable urbanism in post-socialist cities. Strengthening blue-green infrastructure and restoring native riparian vegetation are essential for enhancing climate resilience and ensuring long-term riverfront sustainability. Full article

The Digital Elevation Model (DEM), a crucial data source for waterlogging simulations, significantly influences the accuracy of the results. In complex urban environments, low-resolution DEMs cannot accurately capture the depressional characteristics of city roads or water levels during river floods, leading to distorted urban flooding simulations. To this end, this study developed a novel technique to refine the public 30 m resolution DEM to 1 m resolution for the urban area. The method establishes a zero-flood-depth baseline by correcting the elevations of key elements to improve the accuracy of urban inundation simulations. This is achieved through a semi-automated vector–raster integration workflow, which includes (1) road elevation correction that classifies road vectors, samples elevation at end points, and applies linear interpolation to depict roads as depressions and (2) waterway elevation correction that raises riverbed levels to match adjacent banks, simulating a pre-flood critical state. Polk County in Florida, USA, and the Central Business District (CBD) in Beijing, China, were selected as the research areas. In Polk County, we directly verified its accuracy using the official 1m LiDAR DEM. The results show that the mean error (ME), the root mean square error (RMSE), and the Standard Deviation (SD) improved by approximately 9%, 20%, and 65%, respectively, compared with previous methods. In Beijing, we used a volume matching algorithm to simulate urban flood depths under different rainfall scenarios, indirectly validating the results by comparing the simulated inundation volumes with the theoretical rainfall amounts. The refinement of the DEM significantly improved the topological accuracy of the river channels and the reliability of flood depths, and we analyzed two types of water accumulation behavior patterns. Overall, this study innovatively integrates public raster and vector data, utilizing known attribute information to refine public datasets and construct a highly precise water accumulation model. Full article

Coral reefs in the South China Sea (SCS) are critical for regional marine biodiversity and ecosystem services but face escalating threats from climate change and anthropogenic stressors. However, a holistic evaluation of habitat suitability spanning the distinct environmental gradients from low-latitude deep-water atolls to high-latitude marginal reefs remains limited. This study utilized high-resolution remote sensing data and the MaxEnt (Maximum Entropy) model combined with Principal Component Analysis (PCA) to systematically map potential habitat suitability and elucidate the multi-scale environmental drivers shaping the realized niche of SCS corals. The results revealed significant spatial heterogeneity characterized by a distinct “High South, Low North” latitudinal gradient, with Unsuitable areas dominating 85.5% of the study region, followed by Marginally Suitable habitats at 5.0%, while the northern Nansha Islands were identified as the core distribution area with the highest suitability and continuity. Minimum Phosphate (Min. Phos.) concentration and Sea Surface Temperature (SST) were identified as the core environmental factors determining the spatial distribution of coral reefs in the South China Sea. The optimal environmental ranges were identified as: SST between 28.52 °C and 29.41 °C, water depth shallower than 34 m, extremely low phosphate (0–0.005 mmol/m³), and low cumulative thermal stress (DHW < 0.83 °C-weeks). Crucially, PCA further quantified two potential climate refugia: low-latitude thermal refugia in the southern Nansha Islands, characterized by high environmental stability, and high-latitude marginal refugia in the Beibu Gulf, which offer physical buffering against warming, while necessitating targeted efforts to mitigate the risks of habitat degradation and eutrophication driven by intensifying anthropogenic activities These findings challenge the traditional conservation view relying solely on high-latitude migration, advocating for a climate-resilient spatial planning strategy that prioritizes strict protection of southern biodiversity source banks while enhancing the connectivity of northern marginal stepping stones. Full article

The structural characterization of GG-rich DNA sequences in presence of metal ions provides essential insight into quadruplex stability and ion-dependent conformational specifics. We report the crystal structure of the GG-quadruplex formed by the sequence GGGGTTTTGGGG in the presence of Zn²⁺, K⁺, and Na⁺. It was deposited in the RCSB Protein Data Bank under the accession code 9FTA. The structure was determined by single-crystal X-ray diffraction at a resolution of 2.49 Å in the space group P2₁2₁2₁. It reveals a parallel-stranded, two-G-tetrad stabilized by K⁺ ions within the central channel, while Na⁺ and Zn²⁺ occupy peripheral and groove-associated sites. Zn²⁺ ions are engaged in noncanonical coordination interactions with phosphate oxygens and structured water molecules, contributing to lattice stabilization and subtle adjustments in groove dimensions. The T4 loop forms a compact, ordered motif that contributes to crystal packing rather than intramolecular G4 stabilization. The presence of mixed cations produces a sole lattice architecture mediated by ions that provides structural insight into how bivalent and monovalent metals mutually modulate G-quadruplex topology. These results suggest a basis for understanding the specific ion effects on G4 structures and may direct the design of metal open DNA architectures. Full article

The genus Auricularia holds significant ecological importance due to its role in wood decaying and notable economic value as both an edible and medicinal resource. This study investigates the diversity of Auricularia species in Colombian Andes using an integrative approach. Species identification was based on macromorphological and micromorphological characteristics, alongside molecular analyses employing ITS and LSU markers. A total of 184 sequences of 81 specimens and 30 species were used to construct a phylogenetic tree including RPB2 marker sequences taken from GenBank. The results revealed six Auricularia species in the Colombian Andes: A. subglabra, A. cornea, A. fuscosuccinea, A. nigricans, A. brasiliana, and the newly described A. ibaguensis. This study provides morphological descriptions, distribution records, and interspecific distinctions, aligning these taxa with four out of the five recognized Auricularia species complexes. Novel sequences deposited in GenBank enhance taxonomic resolution, particularly within the A. cornea complex. These findings contribute new insights into the taxonomy of Auricularia in the Colombian Andes and emphasize the need for further research on Neotropical species, which may show significant differences from taxa in other biogeographic regions. Full article

This paper presents a secure 2.4 GHz frequency shift keying (FSK) transmitter front-end with minimal overhead on the data stream using analog obfuscation techniques applied to the modulated waveform. An off-chip true random number generator (TRNG) unit is used to generate the required key for the encryption. Moving away from traditional FSK schemes, which benefit from constant local oscillator (LO) frequency within the channel, the proposed secure FSK scheme shifts the LO frequency in very small steps using an innovative capacitor-bank structure with a calibrated digitally controlled oscillator (DCO). The proposed capacitor bank uses a combination of parallel switches and series capacitors to minimize the impact of the layout parasitics on the minimum capacitor in the bank, thereby reliably creating sub-fF unit capacitors. When combined with the proposed capacitor bank, the cross-coupled CMOS LC voltage-controlled oscillator (VCO) forms a digitally controlled oscillator (DCO). The post-layout simulation results of the DCO reveal that the proposed scheme can achieve a resolution of <20 kHz for the LO frequency shifting while maintaining the phase-noise performance. The reported phase shift allows an equivalent entropy > 6 bits in the implemented analog-inspired secure transmitter front-end. Full article

Direct methods provide a model-free approach to solving the crystallographic phase problem and deliver unbiased atomic structures. However, conventional iterative projection algorithms such as Hybrid Input–Output (HIO) face two critical challenges: discontinuous density modification at the protein-solvent boundary and inaccurate molecular envelope reconstruction that fails to account for trapped solvent, particularly in crystals with solvent content approaching the lower limits of direct phasing applicability. We introduced four continuous iterative projection algorithms, including our improved continuous version, which implements smooth density modification at protein-solvent interfaces. To address envelope inaccuracy, we developed a two-step refined reconstruction scheme using sequential large-radius and small-radius Gaussian filters to identify trapped solvent molecules within surface cavities and internal channels. This scheme enhances the performance of both continuous and classical algorithms, including HIO, the difference map, and our improved versions. Benchmarking on 28 protein structures (solvent contents 55–78%, resolutions 1.46–3.2 Å, reported R-factor less than 0.22) showed that the refined envelope scheme increased average success rates of continuous algorithms by 45.7% and classical algorithms by 60.5%. The performance of continuous algorithms and improved classical algorithms proved comparable to the well-established HIO algorithm, forming a top-tier group that exceeded other classical algorithms. Integrating a genetic algorithm co-evolution strategy further enhanced average success rates by approximately 2.5-fold and accelerated convergence through population-wide information sharing. Although the success rate correlates with solvent content, our strategy improved success probability at any given solvent level, extending the practical boundaries of direct methods. The high success rate enabled averaging of multiple independent solutions, which reduced mean phase error by approximately 6.83° and yielded atomic models with backbone root-mean-square deviation (RMSD) typically below 0.5 Å relative to structures reported in the Protein Data Bank (PDB). This work introduces novel algorithms, a refined envelope reconstruction methodology, and an effective optimization strategy with genetic algorithm evolution. The complete framework enhances the capability and reliability of direct methods for phasing protein crystals with limited solvent content and provides a toolkit for addressing challenging cases in structural biology. Full article

Cryo-electron microscopy (cryo-EM) has revolutionized structural virology, enabling routine structure determination at 2–4 Å resolution, with exceptional cases reaching 1.56 Å. The structural diversity of viruses across vertebrate, plant, and insect hosts provides fundamental insights into infection mechanisms, host–pathogen coevolution, and therapeutic target identification. However, analysis of Electron Microscopy Data Bank entries reveals notable disparities in structural coverage: among 11,717 eukaryotic virus structures (excluding bacteriophages), vertebrate viruses constitute 97.6% (n = 11,432) of deposited entries, while plant viruses (1.0%; n = 117) and insect viruses (1.4%; n = 168) remain significantly underrepresented. This bias stems from distinct technical barriers including size limitations for giant viruses exceeding 200 nm, the loss of asymmetric information during symmetry-imposed processing, and the morphological complexity of filamentous and pleomorphic viruses. Each barrier has driven the development of specialized methodological solutions: block-based local refinement overcomes through-focus variations in giant viruses, cryo-electron tomography (cryo-ET) validates and reveals asymmetric features lost in symmetrized reconstructions, and subtomogram averaging enables structural analysis of pleomorphic assemblies. This review synthesizes recent methodological advances, critically evaluates their capacity to address specific technical barriers, and proposes strategies for expanding structural investigations across underrepresented host systems to achieve comprehensive understanding of viral structural biology. Full article

Geomorphological change is a fundamental consequence of high-magnitude flood events, as extreme hydraulic forcing can rapidly reshape river channels, redistribute sediment, and alter floodplain connectivity. This study applies multi-temporal UAS-based Structure-from-Motion (SfM) photogrammetry to quantify flood-induced geomorphological changes along two representative reaches of the Lilas River (Evia Island, Central Greece) affected by the extreme August 2020 flash flood. High-resolution aerial surveys were conducted prior to the event (June 2018) and shortly after the flood (September 2020), producing Digital Surface Models (DSMs) and orthomosaics with a ground sampling distance of ~2.5 cm. Differential DSM analysis reveals pronounced spatial heterogeneity in erosion and deposition, with net erosional lowering locally exceeding 7 m and depositional aggradation reaching up to ~5 m after accounting for vegetation effects. Channel widening was the dominant response, with cross-sectional widths increasing by a factor of three to nine at selected locations, driven primarily by lateral bank erosion. The results highlight the strong interaction between extreme hydrological forcing, loose alluvial sediments, vegetation removal, and human interventions such as roads and engineered terraces. The study demonstrates how repeatable UAS–SfM workflows can provide quantitative evidence to support post-flood assessment, guide infrastructure adaptation, and inform river restoration and flood risk management in Mediterranean catchments prone to extreme events. Full article

Reservoir bank collapse is a critical geological hazard during the operation of large-scale water conservancy projects, controlled by unique hydrodynamic mechanisms induced by reservoir impoundment, and differs significantly from ordinary landslides. Traditional risk assessment methods, however, often struggle to achieve effective integration between macro-regional zoning and micro-mechanical analysis. Against this limitation, this study proposes a GIS-integrated multi-scale risk screening framework to achieve the preliminary integration of qualitative regional evaluation and quantitative site-specific analysis. Compared with traditional multi-scale studies, the innovations of this research are as follows: (1) a customized GIS component was developed to realize semi-automatic profile extraction from high-resolution DEMs and batch Bishop stability calculations, overcoming the bottleneck of spatializing micro-models over large areas; (2) a “bottom-up” dynamic feedback mechanism was established, utilizing the quantitative safety factor from site-specific evaluations as an explicit indicator for the conservative screening correction of the macro-regional risk map. Applied to the Xiluodu Reservoir, this framework illustrates a potential multi-scale approach for cross-scale risk screening driven by physical–mechanical mechanisms. This provides both a global perspective and a localized physical basis, offering a strategic screening tool for reservoir management. By linking failure mechanisms directly to spatial impacts, the framework provides a plausible conservative feedback rule for risk-informed decision-making in complex reservoir settings. Full article

Mudstone badlands are critical hotspots of erosion and sediment yield, and their rapid morphological changes serve as an ideal site for studying erosion processes. This study used high-resolution Unmanned Aerial Vehicle (UAV) photogrammetry to monitor erosion patterns on a mudstone badland platform in southwestern Taiwan over a 22-month period. Five UAV surveys conducted between 2017 and 2018 were processed using Structure-from-Motion photogrammetry to generate time-series digital surface models (DSMs). Topographic changes were quantified using DSMs of Difference (DoD). The results reveal intense surface lowering, with a mean erosion depth of 34.2 cm, equivalent to an average erosion rate of 18.7 cm yr⁻¹. Erosion is governed by a synergistic regime in which diffuse rain splash acts as the dominant background process, accounting for approximately 53% of total erosion, while concentrated flow drives localized gully incision. Morphometric analysis shows that erosion depth increases nonlinearly with slope, consistent with threshold hillslope behavior, but exhibits little dependence on the contributing area. Plan and profile curvature further influence the spatial distribution of erosion, with enhanced erosion on both strongly concave and convex surfaces relative to near-linear slopes. The gully network also exhibits rapid channel adjustment, including downstream meander migration and associated lateral bank erosion. These findings highlight the complex interactions among hillslope processes, gully dynamics, and base-level controls that govern badland landscape evolution and have important implications for erosion modeling and watershed management in high-intensity rainfall environments. Full article