Search Results (94)

Introduction: Estuaries are among the most productive ecosystems in the world, holding great ecological and economic importance. As transitional zones between rivers and the sea, they experience abrupt abiotic changes linked to the tidal cycle, as well as seasonal changes related to greater river discharge during periods of higher rainfall. Therefore, salinity and temperature are key factors in structuring communities. These estuarine areas are recognized as nursery grounds, offering an abundance of food and shelter from predators, which creates ideal conditions for juvenile growth. Objective: Intense heatwaves were recorded in northern Spain during 2021 and 2022. This study aimed to understand how environmental factors influence the daily and seasonal dynamics of epibenthic communities and to compare these results with those obtained 40 years ago. Methodology: The epibenthic community in the Minho River estuary was assessed between September 2021 and August 2022 during spring tides at both low tide and high tide. Five trawls were carried out at each tide using a 2-meter-wide beam trawl. Several physical and chemical parameters were evaluated during the sampling process. Results: A total of 10,527 demersal fish and epibenthic crustaceans belonging to 21 species were caught in the sampling area. The structure of epibenthic assemblages was heavily influenced by tidal regimes. Assemblages at low tide had a greater number of taxa. In contrast, high-tide assemblages exhibited significantly higher diversity and evenness. Significant differences were observed between the spring/summer and winter assemblages. A SIMPER analysis revealed that Carcinus maenas contributed most to assemblage dissimilarity, both seasonally and by tide. Furthermore, Echiichthys vipera and Platichthys flesus were the species that contributed most to assemblage dissimilarity in both 1982 and 2021–2022. Conclusions: Compared with historical data, the rise in temperature and salinity, coupled with reduced water flow, has caused a profound restructuring of benthopelagic communities. This is driven by a significant increase in the marine character of the habitat. Substantial taxonomic turnover is evident, characterized by reductions in abundance and increases in the number of taxa sampled, as well as in diversity and evenness. Full article

The increasing demand for reliable and high-performance electric vehicle (EV) batteries requires precise and defect-free welding of battery components. Conventional Gaussian laser beam welding faces challenges such as keyhole instability, spattering, porosity, and brittle intermetallic compound formation, particularly in dissimilar Al-Cu joints. These issues significantly affect the electromechanical performance and durability of battery connections. Beam shaping technology has emerged as a core method for improving weld quality, process stability, and efficiency in laser welding, making laser beam welding increasingly vital for high-volume production of e-mobility components. This review systematically evaluates recent advancements in laser beam shaping for laser welding, especially static beam configurations, such as core-ring profiles, flat top, elliptical, and shaped beams; emphasis has been placed on how altering the intensity distribution influences the challenges associated with conventional welding and emerges as an effective solution to address these challenges. By tailoring the spatial energy distribution, beam shaping improves control of heat input, stabilizes melt pool dynamics, and enhances microstructural uniformity. Static beam shaping, compatible with cost-effective near-infrared continuous-wave laser systems, is already being adopted in industry, whereas dynamic beam shaping remains at an earlier stage of industrial maturity. This review highlights key welding challenges in EV battery manufacturing, evaluates beam shaping strategies as practical solutions, and identifies future research directions for large-scale industrial implementation. Full article

Natural wetland loss constitutes a primary threat to waterbirds worldwide, increasingly forcing them to rely on expanding artificial wetlands. Extensive underground coal mining across the North China Plain has created numerous subsidence wetlands, which could serve as important alternative habitats for migratory and wintering waterbirds. However, the effects of different management regimes on waterbirds in these novel artificial wetlands remain poorly understood, hindering effective strategies for reconciling human development with waterbird conservation. Here, we conducted a long-term field survey (2017–2025) of wintering waterbirds across 15 subsidence wetlands under four distinct human management regimes in the Huaibei coal mining area. We recorded 22,712 waterbirds of 45 species. We found that high-intensity aquaculture and floating photovoltaic systems were associated with reduced waterbird diversity, increased community dissimilarity, altered species composition, and the loss of multiple threatened species from survey records. We also found that ecological aquaculture and unutilized wetlands may serve as favorable habitats as alternatives to natural wetlands. Our findings demonstrate that subsidence wetlands can provide vital wintering habitats when managed sustainably, but intensive development severely compromises their conservation value. Future research should integrate habitat variables and year-round surveys to optimize management strategies for these expanding artificial ecosystems. Full article

Old trees function as enduring ecological legacies that preserve historical biodiversity within intensively human-modified landscapes, yet the relative influence of environmental versus anthropogenic drivers on their diversity remains unclear. Here, we aim to disentangle the joint effects of climate, urbanization intensity and cultural preservation on old-tree density and community composition. We analyzed a province-wide census of 21,733 old-tree individuals across 115 counties in Shanxi Province, China, encompassing species origin (native vs. nonnative) and growth form (trees vs. shrubs). Old-tree density was assessed using spatial simultaneous autoregressive error models, while compositional dissimilarity was quantified using generalized dissimilarity modeling. In total, 131 species were recorded, with four dominant species comprising more than 75% of all individuals. Old-tree density increased with mean annual temperature, human population density, and cultural heritage abundance, but declined sharply with cropland coverage. Driver importance varied among groups: native species were primarily governed by climatic conditions, nonnative species by land-use intensity, and tree-form old trees were positively associated with cultural heritage abundance, an effect absent in shrub-form old trees. Compositional dissimilarity was driven mainly by climatic gradients and spatial distance, with additional contributions from human-related variables, particularly for nonnative assemblages. Our findings demonstrate that climate and spatial processes establish the regional framework of old-tree community composition, while cultural and demographic contexts promote local retention of old trees. By explicitly integrating ecological filters with socio-cultural drivers, this study advances old-tree research through a large-scale empirical framework, providing both scientific insight and socially relevant guidance for conservation under land-use intensification and climate warming. Full article

Ensuring friction stir welding (FSW) joint quality typically relies on ultrasonic testing (UT) and radiographic testing (RT), but achieving complete coverage is challenging, and echo-based defect discrimination becomes difficult in dissimilar joints. Laser ultrasonics is a promising non-contact technique that remotely assesses weld quality and provides high spatial resolution at the generation and detection points. This study establishes a laser-ultrasonic method for defect detection in dissimilar Cu–Al FSW joints. Slit-like artificial defects (0.1–2.5 mm deep in 5 mm thick plates) were introduced at the Al-side interface of specimens fabricated with an Al-offset tool. Experiments and numerical simulations were used to evaluate wave modes and irradiation configurations, focusing on intensity-attenuation ratios of specific wave types, including longitudinal and Rayleigh waves. On the non-slit surface, attenuation of reflected longitudinal waves enabled detection of defects ≥0.5 mm deep. On the slit surface, Rayleigh-wave attenuation allowed identification of defects as shallow as 0.1 mm, although slit-side irradiation may be less practical during joining. These results demonstrate that defect identification in dissimilar materials can be achieved by evaluating wave-intensity attenuation rather than relying solely on the presence of reflected echoes, suggesting potential for implementing laser ultrasonics in in-process monitoring of FSW joints. Full article

This study investigates the role of leaf shape in detecting disease in tomato plants, grounded in the observation that plant leaves often undergo structural changes in response to infection. Healthy and diseased tomato leaves are characterized by extracting shape signature features from images and analyzing their spectral characteristics. Leaf images were captured using a Sony ZV-E10 Mark II mirrorless camera equipped with a Sigma 16 mm f/1.4 DC DN lens. Each leaf was placed flat on a matte white surface under a controlled overhead photography setup. The camera was mounted at a fixed height on a tripod, and uniform illumination was achieved using two symmetrically positioned LED spotlight lamps, minimizing shadows and glare. The dataset comprises 200 samples: 100 healthy and 100 diseased tomato leaves, representing a range of morphological and pathological variations. Three primary shape metrics were extracted from the images to characterize the structural differences: (1) the Centroid Contour Distance measured the radial distances from the leaf centroid to its outer contour; (2) the Hausdorff Distance quantified the geometric dissimilarity between contours; and (3) the Dice Similarity Index assessed the degree of overlap. In addition, spectral characteristics were derived from the RGB channels: mean intensities of red, green, blue, and the Excess Green Index. Results show that both shape and spectral features are valuable for detecting plant diseases: PCA shows clustering patterns between the two classes of leaves, and correlation analysis highlights the relationship between several pairs of geometric and color features. In conclusion, shape is an essential aspect of plant health, as it reflects the structural changes that occur as a result of disease. Full article

Biological invasions provide a unique window into community assembly. While classic theory predicts that native species must differentiate their niches to coexist with an invader, the actual outcomes under intense pressure are complex. Our study examines community reassembly under extreme pressure from the invasive ant Solenopsis invicta. We found that while native species do differentiate themselves from the invader, the overwhelming competition constrains this process, forcing survivors into a narrow, shared functional space. This constrained niche differentiation produces a pattern of community-level functional convergence, a process where functionally dissimilar communities become more similar under intense environmental filtering, as survivors are forced into a narrow, shared niche space. The capacity for these rapid, adaptive niche shifts is rooted in intraspecific trait variation (ITV). We also identified a dynamic feedback loop through density-dependent phenotypic plasticity in the invader. By showing how the foundational process of niche differentiation leads to a convergent outcome under extreme pressure, our work clarifies the rules of community assembly in an increasingly invaded world. Full article

Monitoring and tracking the long-term dynamics of vineyard coverage and fresh grape production can support sustainable agricultural planning under evolving climate, market, and land-use pressures. This study presents a comprehensive, data-driven analysis of global viticulture trends from 1961 to 2023, integrating the official statistical database of the Food and Agriculture Organization of the United Nations (FAOSTAT) for grape-producing countries. We applied statistical trend analysis (Mann–Kendall test), Random Forest regression modeling, cross-correlation functions, and dissimilarity analysis to examine patterns and drivers of change in vineyard area, production volume, yield efficiency, and land-use intensity. Our results reveal a significant global decoupling of production from vineyard areas, driven by increasing yields and technological intensification, particularly in rapidly expanding table grape markets in Asia. While traditional European wine regions are reducing vineyard coverage, emerging producers such as China and India are achieving high production with improved land efficiency. Production volume emerged as the dominant predictor of vineyard-harvested areas, while climatic factors, urbanization, and socio-economic dynamics also exerted significant influence. Our findings point to growing polarization in production amounts, alongside convergence in yield and management efficiency across countries. These findings contribute to the understanding of global viticulture transformation and provide insights into optimizing land-use strategies for sustainable grape production under climate change and market evolution. Full article

Tropical cyclones (TCs) rank among the most destructive natural hazards globally, with core damaging potential originating from regions of intense wind shear and steep wind speed gradients within the eyewall and spiral rainbands. Accurately characterizing these fine-scale structural features is therefore critical for understanding TC intensity evolution, wind hazard distribution, and disaster mitigation. Recently, the deep learning-based downscaling methods have shown significant advantages in efficiently obtaining high-resolution wind field distributions. However, existing methods are mainly used to downscale general wind fields, and research on downscaling extreme wind field events remains limited. There are two main difficulties in downscaling TC wind fields. The first one is that high-quality datasets for TC wind fields are scarce; the other is that general deep learning frameworks lack the ability to capture the dynamic characteristics of TCs. Consequently, this study proposes a novel deep learning framework, CycloneWind, for downscaling TC surface wind fields: (1) a high-quality dataset is constructed by integrating Cyclobs satellite observations with ERA5 reanalysis data, incorporating auxiliary variables like low cloud cover, surface pressure, and top-of-atmosphere incident solar radiation; (2) we propose CycloneWind, a dynamically constrained Transformer-based architecture incorporating three wind field dynamical operators, along with a wind dynamics-constrained loss function formulated to enforce consistency in wind divergence and vorticity; (3) an Adaptive Dynamics-Guided Block (ADGB) is designed to explicitly encode TC rotational dynamics using wind shear detection and wind vortex diffusion operators; (4) Filtering Transformer Layers (FTLs) with high-frequency filtering operators are used for modeling wind field small-scale details. Experimental results demonstrate that CycloneWind successfully achieves an 8-fold spatial resolution reconstruction in TC regions. Compared to the best-performing baseline model, CycloneWind reduces the Root Mean Square Error (RMSE) for the U and V wind components by 9.6% and 4.9%, respectively. More significantly, it achieves substantial improvements of 23.0%, 22.6%, and 20.5% in key dynamical metrics such as divergence difference, vorticity difference, and direction cosine dissimilarity. Full article

With the development of various new types of instrumental aroma sensing technologies, there is a need for methodologies that help developers and users evaluate the performance of the different devices. This study introduces a simple method that uses standard coffee beverages, reproducible worldwide, thus allowing users to compare aroma sensing devices and technologies globally. Eight different variations of commercial coffee capsules were used to brew espresso coffees (40 mL), consisting of either Arabica coffee or a blend of Robusta and Arabica coffee, covering a wide range of sensory attributes. The AlphaMOS Astree electronic tongue (equipped with sensors based on chemically modified field-effect transistor technology) and the AlphaMOS Heracles NEO and the Volatile Scout3 electronic noses (both using separation technology based on gas chromatography) were used to describe the taste and odor profiles of the freshly brewed coffee samples and also to compare them to the various sensory characteristics declared on the original packaging, such as intensity, roasting, acidity, bitterness, and body. Linear discriminant analysis (LDA) results showed that these technologies were able to classify the samples similarly to the pattern of the coffees based on the human sensory characteristics. In general, the arrangement of the different coffee types in the LDA results—i.e., the similarities and dissimilarities in the types based on their taste or smell—was the same in the case of the Astree electronic tongue and the Heracles electronic nose, while slightly different arrangements were found for the Scout3 electronic nose. The results of the Astree electronic tongue and those of the Heracles electronic nose showed the taste and smell profiles of the decaffeinated coffees to be different from their caffeinated counterparts. The Heracles and Scout3 electronic noses provided high accuracies in classifying the samples based on their odor into the sensory classes presented on the coffee capsules’ packaging. Despite the technological differences in the investigated devices, the introduced coffee test could assess the similarities in the taste and odor profiling capacities of the aroma fingerprinting technologies. Since the coffee capsules used for the test can be purchased all over the world in the same quality, these coffees can be used as global standard samples during the comparison of different devices applying different measurement technologies. The test can be used to evaluate instrumentational and data analytical developments worldwide and to assess the potential of novel, cost-effective, accurate, and rapid solutions for quality assessments in the food and beverage industry. Full article

Sulfur (S) fertilizer is routinely applied together with other macronutrients by farmers across all regions to improve grain yield and quality, but its distinct effects on grain yield and aroma intensity in fragrant rice remain inadequately studied, especially when applied under varying existing soil S levels. This study aimed to determine the effects of S fertilizer application on grain yield and aroma intensity (2-Acetyl-1-Pyrroline, 2AP) in fragrant rice grown under varying soil S levels (very low, low, and medium). The premium Thai fragrant rice cultivar KDML105 was grown under field conditions during two cropping seasons in 2021 and 2022 in Surin province, northeastern Thailand. Sulfur fertilizer in the form of (NH4)₂SO₄ was applied at 0, 30, 60, 90, and 120 kg S ha⁻¹ at one time with the basal fertilizers phosphorus (P) and potassium (K) under varying soil S levels, using the same protocol in both cropping seasons. Plant growth parameters were evaluated at the tillering stage, and grain samples were harvested at maturity to evaluate grain yield and aroma intensity. The results showed that applying S at rates between 60 and 90 kg ha⁻¹ to soils with very low and low S increased grain yield from 4 to 20% compared to no S application, while no effect of S application was observed for the medium soil S level. The results were primarily attributed to the number of tillers and panicles per hill and the 1000-grain weight in both cropping seasons. Dissimilar effects of S application rates and soil S level were found for grain 2AP content. There was a higher grain 2AP content in the low and medium soil S levels compared to very low S, but the pattern varied according to the S application rate. Applying the appropriate rate of S fertilizer can significantly improve rice productivity, especially when cultivated under S-deficient soil, and higher soil S levels can promote the grain 2AP content of fragrant rice. Full article

Morocco, like many nations undergoing significant economic and social transformation, is experiencing rapid urbanization alongside an ongoing rural exodus. This, coupled with the country’s diverse climate and heterogeneous geography, warrants a detailed exploration of urbanization’s effect on surface climate. Utilizing the Simple Biosphere (SiB2) model’s simulated surface temperature, this study analyses summer’s urban heat structure of seven Moroccan urban areas and their surroundings, assessing the urban impact on surface temperature at the city center, and the intensity and spatial distribution of the urban heat island (UHI) effect at different spatial resolutions. Results show wide-ranging dissimilarities in urban thermal profiles, with the maximum UHI intensity recorded at 8.7 °C in the Dakhla peninsula. Urban heat sink (UHS) effects were observed in six of the seven studied cities, with Marrakech being the exception, only exhibiting UHI effects. A more detailed examination of the thermal profile in Rabat’s metropole at a finer scale, using Landsat-observed land surface temperature (LST), yields additional insights into UHI characteristics, and the findings are contrasted with the existing literature to provide broader insights. The implications of this study strongly resonate within the Moroccan context and its neighboring regions with similar environmental and socio-economic features and should aid in the development of sustainable regional urban planning. Full article

Smoking is a major risk factor for bladder cancer and postoperative complications. Therefore, urological guidelines strongly recommend smoking cessation. Notwithstanding, many patients continue to smoke beyond the time of diagnosis. By using the qualitative methodology, this study aimed to explore barriers, facilitators, and recommendations related to the intensive smoking cessation Gold Standard Programme (GSP) from the multi-perspective view of patients treated with transurethral resection of the bladder tumour (TURBT), their relatives, and clinicians. We conducted semi-structured individual interviews with eight patients, four relatives, and six clinicians in the urology setting. Data were analysed using the Framework Method. All participants perceived the GSP positively. Across the three groups, five categories emerged describing barriers and facilitators: perceptions of the GSP, pragmatic factors, health-related factors, psychological factors, and relational and communicative factors. Similarly, recommendations were represented in two categories: the GSP and pragmatic factors. While facilitators were relatively similar across the three groups, barriers were dissimilar or contradictory. The clinicians expressed the most challenges related to relational and communicative factors. The patients mainly had recommendations related to the GSP, while the clinicians’ recommendations focused on pragmatic factors for conducting the GSP. The potential involvement of relatives needs to be further investigated. Full article

Existing infrared small target detection methods often fail due to limited exploitation of spatiotemporal information, leading to missed detections and false alarms. To address these limitations, we propose a novel framework called Spatial–Temporal Fusion Detection (STFD), which synergistically integrates three original components: gradient-enhanced spatial contrast, adaptive temporal intensity accumulation, and temporal regional contrast. In the temporal domain, we introduce Temporal Regional Contrast (TRC), the first method to quantify target-background dissimilarity through adaptive region-based temporal profiling, overcoming the rigidity of conventional motion-based detection. Concurrently, Regional Intensity Accumulation (RIA) uniquely accumulates weak target signatures across frames while suppressing transient noise, addressing the critical gap in detecting sub-SNR-threshold targets that existing temporal filters fail to resolve. For spatial analysis, we propose the Gradient-Enhanced Local Contrast Measure (GELCM), which innovatively incorporates gradient direction and magnitude coherence into contrast computation, significantly reducing edge-induced false alarms compared with traditional local contrast methods. The proposed TRC, RIA, and GELCM modules complement each other, enabling robust detection through their synergistic interactions. Specifically, our method achieves significant improvements in key metrics: SCRG increases by up to 36.59, BSF improves by up to 9.48, and AUC rises by up to 0.027, reaching over 0.99, compared with the best existing methods, indicating a substantial enhancement in detection effectiveness. Full article

Background: The physical activity of different groups of individuals results in the rearrangement of microbiota composition toward a symbiotic microbiota profile. This applies to both healthy and diseased individuals. Multiple myeloma (MM), one of the more common hematological malignancies, predominantly affects older adults. Identifying an appropriate form of physical activity for this patient group remains a challenge. The aim of this study was to investigate the impact of a 6-week Nordic walking (NW) training program combined with a 10/14 time-restricted eating regimen on the gut microbiota composition of multiple myeloma patients. Methods: This study included healthy individuals as the control group (n = 16; mean age: 62.19 ± 5.4) and patients with multiple myeloma in remission (MM group; n = 16; mean age: 65.00 ± 5.13; mean disease duration: 57 months). The training intervention was applied to the patient group and consisted of three moderate-intensity sessions per week, individually tailored to the estimated physical capacity of each participant. The taxonomic composition was determined via 16S rRNA sequencing (V3–V9 regions). The microbiota composition was compared between the patient group and the control group. Results: The alpha and beta diversity metrics for species and genus levels differed significantly between the control and patient groups before the implementation of the NW program. In contrast, no differences were observed between the control and patient groups after the training cycle, indicating that the patients’ microbiota changed toward the pattern of the control group. This is confirmed by the lowest values of average dissimilarity between the MMB groups and the control at all taxonomic levels, as well as the highest one between the control group and the MMA patient group. The gut microbiota of the patients was predominantly represented by the phyla Firmicutes, Actinobacteria, Verrucomicrobia, Proteobacteria, and Bacteroidetes. Conclusions: The training, combined with time-restricted eating, stimulated an increase in the biodiversity and taxonomic rearrangement of the gut microbiota species. Full article