Search Results (287)

Background: Severe obesity is associated with chronic low-grade inflammation, dysglycemia, and higher periodontitis risk. Sleeve gastrectomy (SG) is now a dominant bariatric procedure and reliably improves weight and metabolic status yet reported oral and periodontal trajectories after surgery remain heterogeneous. Objective: To synthesize SG-centered evidence on periodontal outcomes, oral and gut microbiome remodeling, and mechanistic pathways that may link postoperative physiology to the gut–oral axis. Methods: We conducted a structured narrative review guided by SANRA principles using targeted searches of PubMed/MEDLINE, Web of Science, Scopus, and Embase, complemented by citation chaining of key reviews and mechanistic anchor papers; evidence was organized into clinical, oral microbiome, gut microbiome, and mechanistic gut–oral axis streams and interpreted with a pragmatic evidence hierarchy. Results: Small prospective SG cohorts suggest bleeding on probing (BOP), gingival indices, and sometimes probing depth (PD) may improve in some patients, particularly alongside weight loss, improved glycemic control, and lower systemic inflammatory burden, whereas clinical attachment level (CAL) and longer-term structural trajectories remain mixed; mixed-procedure syntheses also report early deterioration in some settings. Oral microbiome findings after bariatric surgery are site- and time-dependent, and salivary signals do not necessarily mirror subgingival plaque, whereas gut microbiome remodeling and bile acid signaling changes are more consistently reported and provide plausible but indirect mediator candidates. At the same time, reflux, vomiting, salivary changes, diet patterning, medications, and periodontal care can modify or counteract potential periodontal benefits and may increase competing risks such as caries or erosive tooth wear. Conclusions: The SG–gut–oral axis-periodontal pathway is a biologically plausible working hypothesis rather than a proven causal pathway in humans. The present evidence for any periodontal benefit relies mainly on small observational cohorts and is most credibly demonstrated for inflammatory, not structural, endpoints. Full article

Benggang (Benggang), a typical landform characterized by severe erosion and a geohazard in the red-soil hilly regions of southern China, is characterized by a fragmented texture, irregular boundaries, and high similarity to background objects such as bare soil and roads, which poses a dual challenge of “multiscale variability + strong noise” for automated identification at regional scales. To address insufficient information from a single modality and the limited representation of cross-scale features, this study proposes a dual-stream feature-fusion network (DF-Net) for multisource data consisting of a digital orthophoto map (DOM) and a digital elevation model (DEM). The method adopts ResNeSt50d as the backbone of the two branches: on the DOM side, a Canny-edge channel is stacked to enhance high-frequency boundary information; on the DEM side, derived terrain factors, including slope, aspect, curvature, and hillshade, are introduced to provide morphological constraints. In the cross-modal fusion stage, a multiscale sparse attention fusion module is designed, which acquires contextual information via multiwindow average pooling and suppresses noise interference through top-K sparsification. In the decision stage, a multibranch ensemble is employed to improve classification stability. Taking Anxi County, Fujian Province, as the study area, a coregistered dataset of GF-2 (1 m) DOM and ALOS (12.5 m) DEMs is constructed, and a zonal partitioning strategy is adopted to evaluate the model’s generalization ability. The experimental results show that DF-Net achieves 97.44% accuracy, 85.71% recall, and an 82.98% F1 score in the independent test zone, outperforming multiple mainstream CNN/transformer classification models. This study indicates that the strategy of “multimodal feature enhancement + sparse attention fusion” tailored to Benggang erosional landforms can significantly improve recognition performance under complex backgrounds, providing technical support for rapid Benggang surveys and governance-effectiveness assessments. Full article

Extreme rainfall events can trigger widespread landsliding and fluvial erosion, exerting a disproportionate influence on sediment production and landscape evolution in mountainous watersheds. However, hillslope–channel coupling during individual extreme events remains poorly quantified due to the scarcity of event-scale topographic observations. This study investigates event-scale hillslope–channel coupling by quantifying landslide-driven hillslope erosion and channel incision associated with Typhoon Morakot (2009) in the Sinwulu River watershed, southeastern Taiwan. High-resolution pre- and post-event digital surface models (DSMs) were reconstructed using an aerial structure-from-motion multi-view stereo (SfM–MVS) photogrammetry workflow and corrected for canopy height to derive meter-scale topographic changes. Hillslope and channel domains were delineated, and linked hillslope–channel units were used to examine spatial relationships between erosion processes and topographic and hydraulic factors. Results indicate that landslide erosion dominated sediment production during the event with watershed-average erosion of 544.35 mm, while channel responses exhibited strong spatial contrasts, with pronounced incision in upstream reaches and substantial deposition downstream of major knickpoints. Event-scale analysis provides evidence for a strong correspondence between channel incision and hillslope landslide erosion, whereas correlations with commonly used hydraulic proxies such as unit stream power are comparatively weaker. These findings highlight the value of event-scale topographic measurements for elucidating transient hillslope–channel coupling processes during extreme rainfall events. Full article

The proliferation of intelligent sensor networks in urban surveillance and remote sensing has triggered the explosive growth of unstructured visual sensor data. Accurately retrieving targets from these massive streams based on complex cross-modal user intents remains a critical bottleneck for efficient intelligent perception. Composed Image Retrieval (CIR) addresses this by enabling retrieval via a multi-modal query that combines a reference image with semantic control signals. However, existing methods often struggle with abstract instructions in real-world scenarios. Consequently, models often suffer from feature distribution shifts due to focus ambiguity, as well as semantic erosion caused by highly entangled visual and textual features. To address these challenges, we propose a geometry-based Selective Orthogonal Projection Network (SOP). First, the Selective Focus Recovery module quantifies instruction uncertainty via information entropy and calibrates shifted query features to the true target distribution using structural consistency regularization. Second, to ensure data fidelity, we introduce Orthogonal Subspace Projectionand Geometric Composition Fidelity. These mechanisms employ Gram–Schmidt orthogonalization to decouple features into a constant visual base and an orthogonal modification increment, restricting semantic modifications to the null space. Extensive experiments on FashionIQ, Shoes, and CIRR datasets demonstrate that SOP significantly outperforms SOTA methods, offering a novel solution for efficient large-scale sensor data retrieval and analysis. Full article

While dissolution dominates the genesis of karst systems, physical erosion processes also play a significant role in their development. Lowering of the water table exposes caves to vadose conditions, reducing roof-supporting buoyancy and potentially leading to catastrophic conduit ceiling failure and cave collapse. The locations and extents of collapse areas are not always identifiable at the landscape surface. High-resolution topographic data derived from LiDAR were used to develop a digital elevation model (DEM) that isolates areas that may have sustained episodes of cave collapse and improves our understanding of past hydrogeological and geomorphological conditions of the system. Cave level delineation from LiDAR data was used to assign elevations to cave entrances. Spatial susceptibility to past collapse was evaluated using a weighted multi-criteria analysis that integrated terrain slope, proximity to mapped cave entrances, and distance to surface streams. Areas identified as having a high likelihood of collapse spatially coincide with cave level contacts and known karst windows and terraces, indicating that this replicated methodology is effective as an initial survey tool for identifying collapse-prone areas in karst landscapes. Full article

Ecological restoration has emerged as a critical tool for addressing ecosystem degradation worldwide. The Stream Quantification Tool (SQT) represents a significant advancement in stream restoration methodology, providing a standardized framework for quantifying stream functions and evaluating project outcomes. We investigated relationships between salamander abundance and physicochemical parameters from the SQT (nitrogen, turbidity, temperature, and composite SQT physicochemical score) across 16 streams in the upstate region of South Carolina. Stream salamanders can be reliable bioindicators due to their philopatric nature, longevity, and stable populations, making them valuable for assessing stream restoration effectiveness. Six salamander species (n = 394 individuals) were identified across 14 streams where salamanders were present. N-mixture models were used to analyze abundance patterns while accounting for imperfect detection. Turbidity was the strongest negative predictor of salamander abundance, followed by nitrogen. Removal of an agriculturally impacted stream with elevated turbidity substantially altered model rankings, making the null model top-ranked, followed by nitrogen, composite physicochemical score, and temperature. These findings demonstrate turbidity’s critical role in salamander abundance. Management practices should prioritize erosion and sediment control solutions for salamander conservation. For SQT biological monitoring, we recommend focusing on turbidity and nitrogen as key parameters affecting salamander abundance in stream assessments. Full article

The availability of water resources has significantly decreased in recent years. Therefore, it is essential to design comprehensive management strategies at the watershed level. This study included a methodological novelty by combining morphometric analysis with multicriteria analysis to prioritize sub-watersheds in the Las Flores Watershed (LFW), located in Chiapas, Mexico. The LFW catchment area covers 2517.96 km² and was divided into 29 sub-watersheds. Morphometric analysis, based on physical characteristics (shape, stream network, and relief), allows us to infer the level of susceptibility to erosion of a watershed. However, to improve the prioritization of sub-watersheds, the erosion rate (EA) was estimated using the Universal Soil Loss Equation (USLE), as well as rainfall intensity and curve number. The results show that sub-watersheds SW₂₀ and SW₁₅ have the highest predicted EA values, that is, 234.76 and 222.10 t ha⁻¹, respectively. The final prioritization framework established that the sub-watersheds classified as very high priority were SW₂₀, SW₂₈, SW₁₅, SW₂₁, and SW₀₉, covering an area of 734.19 km², corresponding to 29.16% of the total area of LFW. Therefore, in these sub-watersheds, the immediate implementation of water regulation structures and conservation practices is required to minimize their susceptibility to water erosion. Full article

Shoreline variations in closed-basin lakes are closely linked to hydrological fluctuations and long-term changes in water balance, making them important indicators of environmental change. This study analyzes historical shoreline dynamics in Lake Van (Türkiye), the world’s largest soda lake, and provides scenario-based shoreline projections for 2032 and 2042 to support hydrological assessment and water-related management. Multi-temporal Landsat satellite images from 1982, 1992, 2002, 2012, and 2022 were processed using the Digital Shoreline Analysis System (DSAS 5.0) to quantify shoreline retreat and accretion, while future shoreline positions were estimated using the Kalman filter model. The results show pronounced spatial variability, with the most significant shoreline retreat observed in the Çelebibağ and Karahan regions, where sediment supplied by major inflowing streams contributes to shoreline instability through reworking and redistribution rather than stable accretion. Net shoreline movement values reached −2580.1 m for erosion and up to 1700 m for accretion. Model projections indicate an increasing trend of shoreline retreat by 2032 and 2042, accompanied by localized accretion zones. These hydrological-driven shoreline changes have potential implications for littoral habitats, water–land interactions, and human use of the shoreline, including fisheries infrastructure. The study demonstrates the value of integrating remote sensing and statistical forecasting for monitoring shoreline dynamics in closed-basin lake systems. Full article

This study examines the erosion potential of earthen spillways under the growing risks posed by changing climate and extreme flood events, which threaten the stability and safety of dam infrastructure. Specifically, it employs a machine learning approach to evaluate how readily available spillway width and stream power can predict erosion potential. Site-specific erosion prediction methods are often costly and time-consuming because they rely on extensive field investigations and physical modeling. To address these challenges, this research employs multiple machine learning algorithms, including logistic regression, Support Vector Machine, and Random Forest, on existing data to classify spillways as erodible or non-erodible cases. The Random Forest model demonstrated the best predictive performance, achieving 82.7% accuracy on the test dataset. To further interpret the reliability of model predictions, a Bayesian probability analysis was performed, revealing that when the model predicts erosion, there is a 59% probability that the dam will actually experience erosion. These results highlight how integrating existing datasets with machine learning and probabilistic reasoning can enhance dam safety assessment by considering the accuracy, efficiency, and reliability of spillway erosion predictions. Full article

Morphological variability on Mediterranean embayed sandy beaches is largely driven by wave storms and episodic sediment inputs from local streams during intense rainfall. While storm impacts are well documented, the combined influence of stream discharge, wave forcing and morphological response remains poorly understood. This study examines these interactions at Castell beach, one of the few non-urbanised, stream-fed embayed beaches on the northwestern Mediterranean, during two high-energy storms with heavy rainfall: December 2019 and January 2020 (Storm Gloria). Morphological changes in the subaerial and submerged beach, and stream dynamics were assessed using repeated RTK–GNSS surveys, orthophotos and echo-sounder bathymetry. Results show the stream mouth shifted along the beach (east, central or west) during heavy rainfall episodes depending on wave direction and pre-existing topography, tending toward more wave-sheltered zones. The storms induced contrasting responses: the first caused slight subaerial accretion, whereas Storm Gloria produced subaerial erosion and nearshore sediment deposition from both beach and stream sources. This material was subsequently reworked and reincorporated into the subaerial beach under calmer conditions, with full recovery by February 2022. These findings highlight the role of stream–wave interactions in sediment dynamics and the capacity of highly protected embayed beaches to adapt to extreme events. Full article

A macrotidal estuary with mountain-stream inputs (MEMSs) is characterized by strong hydrodynamic forcing, high turbidity, and complex channel morphology. This study combines field measurements (2005–2020) with a 2D hydrodynamic–sediment model to examine estuarine turbidity maximum (ETM) dynamics, erosion–deposition patterns, and the effects of engineering interventions in the Jiaojiang Estuary (JJE). Results show that the coupled influence of upstream floods and downstream macrotides produces highly seasonal and spatially variable water–sediment processes: mountain-stream floods exhibit sharp hydrodynamic fluctuations, and the estuary displays pronounced tidal-wave deformation. Over the 15-year observation period, the riverbed experienced alternating erosion (up to −3.5 m) and deposition (up to +4.2 m), with net erosion of 0.5–1.2 m occurring in most Ling River sections during high-discharge years. The ETM migrated about 30 km during spring tides, with near-bed suspended sediment concentrations reaching 50–60 kg/m³. Human activities—particularly historical sand mining—modified channel geometry and sediment composition, intensifying the exchange between bed material and suspended sediment and facilitating the formation and migration of the ETM. Extreme events further enhanced geomorphic adjustment: the post-Lekima (2019) flood produced maximum scour of −5.8 m in the upper Ling River and deposition of +3.2 m in the Jiaojiang main channel within weeks. Channel curvature and junction morphology strongly controlled flood-level distribution. Model experiments indicate that lowering shoal elevations and widening the cross-section at key constrictions can effectively reduce flood levels. Collectively, these findings clarify the morphodynamic evolution mechanisms of a MEMS system and provide quantitative guidance for flood-mitigation and estuarine-management strategies. Full article

Local scour around support structures has remained a critical barrier to tidal stream turbine deployment in energetic marine channels since loss of embedment and bearing capacity has undermined stability and delayed commercialization. This review identifies key mechanisms, practical implications, and forward-looking strategies related to local scour. It highlights that rotor operation, small tip clearance, and helical wakes can significantly intensify near-bed shear stress and erosion relative to monopile foundations without turbine rotation. Scour behavior is compared across monopile, tripod, jacket, and gravity-based foundations under steady flow, reversing tides, and combined wave and current conditions, revealing their influence on depth and morphology. The review further assesses coupled interactions among waves, oscillatory currents, turbine-induced flow, and seabed response, including sediment transport, transient pore pressure, and liquefaction risk. Advances in prediction methods spanning laboratory experiments, high-fidelity simulations, semi-empirical models, and data-driven techniques are synthesized, and mitigation strategies are evaluated across passive, active, and eco-integrated approaches. Remaining challenges and specific research needs are outlined, including array-scale effects, monitoring standards, and integration of design frameworks. The review concludes with future directions to support safe, efficient, and sustainable turbine deployment. Full article

Kinmen Island, historically known as Quemoy, holds significant historical and geopolitical importance due to its strategic location in the Taiwan Strait, just a few kilometers from the Chinese mainland. This study presents the first comprehensive assessment of soil erosion and deposition on Kinmen, providing a scientific foundation for future land conservation and sustainable development initiatives. It also addresses the underrepresentation of small-island environments in soil erosion modeling by adapting the Revised Universal Soil Loss Equation (RUSLE) and Unit-Stream-Power-based Erosion Deposition (USPED) models for coarse-textured soils under limited rainfall conditions, offering insights into the reliability and limitations of these models in such contexts. The rainfall–runoff erosivity factor (${\mathrm{R}}_{\mathrm{m}}$) was derived from precipitation data at four stations, while soil samples from ten locations were analyzed for the Soil Erodibility Factor (${\mathrm{K}}_{\mathrm{m}}$). Topographic factors, including the Slope Length and Steepness ($\mathrm{LS}$) and the Topographic Sediment Transport (${\mathrm{LS}}_{\mathrm{T}}$) factors, were computed from a 20 m DEM (Digital Elevation Model), and the Cover-Management Factor ($\mathrm{C}$) was obtained from land use classification. The RUSLE estimated a mean soil erosion rate of 2.17 Mg ha⁻¹ year⁻¹, while the USPED results varied with parameterization, ranging from 0.87 to 3.79 Mg ha⁻¹ year⁻¹ for erosion and 1.39 to 6.51 Mg ha⁻¹ year⁻¹ for deposition. The results were compared with studies from the neighboring Fujian Province and contextualized through two field expeditions. This pioneering research advances the understanding of erosion and deposition processes in a strategically located island environment and supports evidence-based policies for land conservation, contributing to SDG 15 (Life on Land) and SDG 13 (Climate Action). Full article

The residues of rice production could be used as a mulch to reduce the effects of rill erosion on long and steep hillslopes. However, there is a need to identify the most effective size of this residue to apply as a countermeasure of rill erosion, exploring its effect on hydraulic variables. Several investigations have focused on the anti-erosive effects of other crop residues, while experiences on rice straw applications to reduce rill erosion are still lacking. To fill this gap, this study has measured the variability in flow velocity, stream power and the resulting soil loss in a rill covered by rice straw. Flume experiments simulating rill erosion have been carried out comparing soil loss among treatments with rice straw (dose of 3 tonnes ha⁻¹ and lengths between 20 and 70, 80 and 130, or 140 and 190 mm) and a non-mulched control. Moreover, a multiple regression model that predicts soil loss for a rill cover with rice straw of a given length has been proposed. The application of rice straw reduced the soil loss by at least 20% compared to bare soils. The most suitable size of the applied straw was 90 to 130 mm, which reduces soil loss by 45%. Finer straw (20 to 70 mm) did not significantly improve the soil’s resistance to rill erosion. The beneficial effects of straw must be ascribed to the reduction in flow velocity due to the presence of straw, as shown by accurate power equations regressing the soil loss to this variable. In spite of some limitations (small experimental scale, local environmental conditions, and low incorporation level of the substrate), the results are useful for land managers and hydrologists for soil conservation in hillslopes subjected to intense rill erosion and with similar climatic and hydrological and geomorphological conditions as the case study. Full article

Climate change has intensified torrential rainfall and floods, causing frequent floodplain inundation with erosion and deposition. Large-scale waterfront facilities such as park golf courses are highly vulnerable, requiring systematic hydraulic safety evaluation. We simulated a recent flood in the Musim Stream using a two-dimensional FaSTMECH model to assess floodplain safety. The model showed excellent reproducibility (RMSE = 0.0176 m, NSE = 0.95 for depth; RMSE = 0.016 m/s, NSE = 0.87 for velocity). Flood risk indices—flood intensity (FI) and flood hazard rating (FHR)—and erosion–deposition indices—transient erosion and deposition index (TEDI) and steady erosion and deposition index (SEDI)—were applied. FI values were in the range of 0.3–6.4 (median 2.8) and FHR was in the range 0.7–10.2 (median 3.0), indicating that most floodplain areas exceeded the “high” to “extreme” risk range. TEDI was in the range of 0.004–4.15 (mean = 0.60), while SEDI was in the range of 0.001–5.59 (mean = 2.12). High TEDI values (0.6–0.9) occurred in curved and contracted sections, corresponding to observed erosion zones, whereas high SEDI values (0.8–1.0) were concentrated in the main channel. These results demonstrate that the indices effectively quantify and visualize floodplain risk, providing a practical basis for the design, placement, and maintenance of floodplain facilities. Full article