Search Results (146,493)

Hamatocaulis vernicosus and Calliergonella cuspidata commonly co-occur in base-rich fens, reflecting overlapping ecological niches. While C. cuspidata is a widespread and ecologically plastic fen species often associated with eutrophicated wetlands, H. vernicosus is a habitat-specialist species of conservation concern. This study investigated the competitive interactions between these two moss species and the role of microhabitat conditions in their coexistence. A reciprocal transplant experiment was conducted in a natural, rich fen in southeastern Lithuania using replicated experimental plots across different microtopographic and hydrological conditions. Species cover and spread were monitored to assess competitive performance following transplantation. The results showed that under wet conditions, H. vernicosus was able to expand into surrounding areas and successfully compete with C. cuspidata. In contrast, C. cuspidata showed limited spread within H. vernicosus patches under wet conditions and was gradually displaced. An advantage of C. cuspidata was observed only in hummocky microtopographic settings. These findings indicate that stable hydrological conditions maintaining microhabitat heterogeneity promote the coexistence of both species. Alterations in the water regime may reduce the competitive ability and long-term persistence of H. vernicosus, highlighting the importance of hydrology-focused management for its conservation. Full article

Although the Eastern Mediterranean Sea is a hotspot for marine bioinvasions, the accurate identification and monitoring of non-indigenous species (NIS) remain impeded by the ambiguous morphologies of species and limited regional genetic data. This study applied an integrative approach, combining morphological identification with DNA barcoding, to assess the taxonomy and expansion of bivalves from the genera Isognomon and Malleus in the Eastern Mediterranean Sea. Specimens were collected from a broad range of habitats, including marinas, ship hulls, reefs, and marine caves. Phylogenetic analyses revealed two distinct Isognomon species in the region: I. bicolor, frequently associated with artificial substrates and showing evidence of multiple introductions, and I. aff. legumen, restricted to cryptic natural habitats. A single species of Malleus cf. regula was also detected, clustering with sequences from neighboring Mediterranean regions. The study highlights the limitations of morphology-based taxonomy and the urgent need to enhance genetic reference databases, particularly with sequences from areas of nativity. As NIS increasingly expand from anthropogenic habitats into natural ecosystems, validated data are essential for risk assessment and conservation management. Full article

This study assessed the impact of the dietary inclusion of Prosopis laevigata pods (PLPs) on growth performance, carcass traits, and the metabolomic profiles of liver and meat in finishing lambs. A total of 28 crossbred lambs (38 ± 5 kg body weight) were allocated to one of two treatments: a control diet (0 g PLP/kg dry matter, n = 14; CONT) and a diet supplemented with 300 g PLP/kg dry matter (DM) (n = 14; PS). Growth performance was monitored over 25 days. Animals were assigned to a randomized design, and data were analyzed using the General Linear Model (GLM) procedure. Compared with the control diet, PLP inclusion (300 g/kg DM) reduced total body weight gain (p = 0.04) and worsened feed conversion efficiency. Lambs on the control diet also displayed a significantly greater (p = 0.02) rump perimeter. In contrast, lambs fed the 300 g PLP/kg DM diet showed a marked increase (p < 0.05) in the longissimus thoracis et lumborum (LTL) muscle area. Principal component analysis revealed a distinct separation between treatment groups based on the identified metabolites. Liver metabolomic data accounted for 30.6% of the total variability, while meat samples accounted for 45.7%. A total of 21 and 23 metabolites exhibited positive correlations in liver and meat, respectively. Notably, PLP supplementation influenced several metabolic pathways (p < 0.05), including the biosynthesis of unsaturated fatty acids, fatty acid biosynthesis, and sulfur metabolism in both liver and meat. Additionally, phenylalanine metabolism was specifically affected (p < 0.05) in the liver, while steroid biosynthesis was altered (p < 0.05) in meat. Overall, the inclusion of PLPs in the diet of finishing lambs resulted in notable changes to the liver and meat metabolomes, particularly in pathways associated with fatty acid biosynthesis. Although PLP supplementation reduced overall growth performance, it did not negatively impact carcass quality traits; hence, we recommend the inclusion of 300 g PLP/kg DM in finishing lamb diets. Full article

The Atlantic blue crab (Callinectes sapidus) has rapidly expanded across the Mediterranean Sea, forming self-sustaining populations in coastal and transitional ecosystems. Its ecological plasticity, high reproductive potential, and tolerance to wide salinity and temperature ranges have enabled a rapid basin-wide colonization, particularly evident in Italian lagoons and estuaries. This invasion has generated substantial ecological alterations, such as predation on bivalves, competition with native decapods, and disruptions of trophic dynamics, as well as significant economic losses for fisheries and aquaculture sectors, especially in northern Adriatic clam-farming areas. Social perceptions vary widely, and management actions remain fragmented, limiting the effectiveness of control and mitigation efforts. This review analyzes the scientific and gray literature published from its first Mediterranean records to 2025, synthesizing evidence on the species’ distribution, ecological impacts, socio-economic consequences, and existing regulatory responses, with a focus on the Mediterranean basin and Italy. Studies on consumers’ and fishers’ perceptions are examined to identify emerging opportunities for sustainable utilization. By integrating ecological and socio-economic dimensions, the review outlines priority knowledge gaps and management needs, providing a science-based framework to support coordinated monitoring, adaptive control strategies, and potential valorization pathways consistent with the EU Green Deal, the Blue Economy, and Circular Bioeconomy principles. Full article

Earthquake Early Warning (EEW) systems based on on-site measurements enable ultra-rapid alerts by exploiting the time gap between the arrival of P-waves and the subsequent damaging S-waves. A central challenge is the reliable estimation of impending ground motion using only the earliest portion of the signal. This study investigates a site-specific methodology based on the S/P amplitude ratio for near-real-time seismic acceleration estimation at the Iași stations, Romania, in a region dominated by Vrancea intermediate-depth seismicity. Using 50 strong-motion records from the European Strong-Motion (ESM) database, a local calibration coefficient of k = PGA_S/PGA_P = 6.2 was derived for the Iași area, consistent with its soft-soil conditions and with values reported for comparable sedimentary environments worldwide. A regional analysis confirms that the S/P ratio is primarily governed by local site effects, requiring station-level calibration. The methodology was experimentally validated through shaking-table tests using real P-wave recordings. Predicted S-wave peak ground accelerations exhibit no systematic bias, with a median relative error of +2.0% and dispersion consistent with the intrinsic log-normal variability of the S/P ratio. The results demonstrate that a locally calibrated S/P ratio provides a robust and physically grounded basis for rapid seismic acceleration estimation in on-site EEW systems. Full article

In recent years, with the widespread application of shortwave infrared (SWIR) spectroscopy in mineral identification and hydrothermal alteration studies, an increasing number of studies have attempted to integrate SWIR spectral data with machine learning approaches to fully exploit mineralization-related discriminative information embedded in high-dimensional spectral datasets. In this study, the Zhunuo porphyry copper deposit in Tibet was selected as the research target. SWIR drill core spectral data were systematically acquired, and a random forest (RF) machine learning model was applied to full-band SWIR spectra (1300–2500 nm) to conduct integrated analyses of copper grade regression and mineralization discrimination. A total of 2140 drill core samples were measured, with three replicate measurements per sample, yielding 6420 spectra. After standardized preprocessing and interpolation resampling, a unified spectral feature dataset was constructed for regression and classification analyses. SWIR spectral data are characterized by a large number of bands, strong inter-band correlations, and relatively limited sample sizes; under such conditions, model generalization ability and stability become critical factors in method selection. Based on ensemble learning, the random forest model constructs multiple decision trees and aggregates their predictions through voting or averaging, effectively reducing model variance and mitigating overfitting, and is therefore well suited for high-dimensional, small-sample, and highly correlated geological spectral datasets. In porphyry copper systems, the spectral characteristics of hydrothermal alteration minerals and mineralization intensity commonly exhibit complex nonlinear relationships, which can be effectively captured by random forest models without requiring predefined functional forms. The regression results indicate that accurate quantitative prediction of copper grade based solely on SWIR spectral data remains limited. In contrast, when a threshold-based binary classification was introduced using an industrial cutoff grade of 0.2% Cu, the model achieved an overall accuracy of 75%, an F1 score of 0.69, and an area under the ROC curve (AUC) of 0.80, demonstrating strong mineralization discrimination capability and stability. Overall, the integration of SWIR spectroscopy with machine learning methods provides an efficient, reliable, and geologically interpretable technical approach for early-stage exploration and detailed drill core interpretation in porphyry copper deposits. Full article

This study evaluates the stability and failure probability of rock slopes at Mount Uhud, Madinah, Saudi Arabia, with particular attention to a representative slope in the densely populated southern part. A combined deterministic–probabilistic approach was adopted using a two-dimensional, nonlinear elastoplastic finite element model to capture realistic slope behavior. Uncertainty in key geomechanical parameters—slope angle, cohesion, and internal friction angle—was quantified through Li’s Point Estimate Method, resulting in $n^3$ probabilistic simulations. Slope performance was assessed in terms of both factor of safety (FoS) and probability of failure (Pf). Deterministic analysis yielded a factor of safety of 0.813, while probabilistic simulations produced a factor of safety range between 0.468 and 1.052, with a mean value of approximately 0.73. The corresponding probability of failure was estimated at about 5.16%. Sensitivity analysis indicates that cohesion and internal friction angle exert the strongest influence on stability outcomes. Although the slope shows noticeable sensitivity to reductions in these parameters, the overall probability of failure remains relatively low under current conditions. The results demonstrate that integrating deterministic and probabilistic analyses provides a robust basis for evaluating rock slope reliability in complex geological environments, particularly in rapidly urbanizing mountainous areas such as Mount Uhud. Full article

With the core advantages of high energy efficiency, high power density, and reliable operation, high-voltage permanent magnet motors have become the mainstream development direction of modern motor technology. However, the risk of demagnetization caused by excessive temperature increases in permanent magnets has become a key bottleneck restricting motor performance and operational reliability, which makes research on the flow and heat transfer characteristics of motor cooling systems of great engineering value. Taking the 710 kW high-voltage permanent magnet motors as the research object, this study established a global flow field mathematical model covering the internal and external air duct cooling systems of the motor based on the theories of computational fluid dynamics and numerical heat transfer, and systematically analyzed the flow characteristics and distribution laws of cooling air. The thermal–fluid coupling numerical method was employed to simulate the temperature field of the motor, and the overall temperature distribution of the motor, temperature gradient of key components, and maximum temperature value were accurately obtained. To verify the validity of the established model, a test platform for the cooling system performance was designed and built. Measuring points for wind speed, air temperature, and component temperature were arranged at key positions, such as the stator radial ventilation ducts, and experimental tests were conducted under the rated operating conditions. The results show that the flow field distribution of the internal and external air ducts of the motor is reasonable and that the cooling air flows uniformly, with the external and internal circulating air volumes reaching 1.2 m³/s and 0.6 m³/s, respectively, which meets the heat dissipation requirements. The maximum temperature of 95 °C occurs in the stator winding area, and the maximum temperature of the permanent magnets is controlled within the safe range of 65 °C. The simulation results were in good agreement with the experimental data, with an average relative error of only 4%, which fell within the engineering allowable range, thus verifying the accuracy and reliability of the established global model and thermal–fluid coupling calculation method. This study reveals the thermal–fluid coupling transfer mechanism of high-voltage permanent magnet motors and provides a theoretical basis and engineering reference for the optimal design, precise temperature rise control, and reliability improvement of motor cooling systems. Full article

To investigate the rationality of water-use efficiency in agroforestry systems within this region, this study utilised the medicinal and edible plant Sophora japonica cv.jinhuai as a foundation. Five mixed planting models were established, incorporating Ardisia gigantifolia, Melicope pteleifolia, Camellia limonia, Belamcanda chinensis, Isatidis radix, and Pilea basicordata. Water-use efficiency (WUE) was analysed by measuring the carbon-stable isotope composition (δ¹³C) of plant leaves. Compared to previous studies that primarily focused on δ¹³C in single species or simple composite systems, this research innovatively evaluates the water-use efficiency (WUE) performance of different composite patterns and their impact on system stability at both the species and system levels, integrating the theory of fitness differentiation. Results indicate that the ranges of δ¹³C and WUE for the five mixed cropping systems were −27.0633‰ to 31.2188‰ and 27.7191 to 50.0365 μmol/mol, respectively. WUE ranking was: Sophora japonica cv.jinhuai—Camellia limonia—Pilea basicordata (SCP) > Sophora japonica cv.jinhuai—Camellia limonia (SC) > Sophora japonica cv.jinhuai—Belamcanda chinensis + Isatidis radix (SBI) > Sophora japonica cv.jinhuai—Melicope pteleifolia (SM) > Sophora japonica cv.jinhuai—Ardisia gigantifolia (SA). At the species level, the Sophora japonica cv.jinhuai—Camellia limonia—Pilea basicordata (SCP) composite planting model is better suited to karst arid environments, while the Sophora japonica cv.jinhuai—Ardisia gigantifolia (SA) composite planting model exhibits lower overall plant water-use efficiency (WUE) and weaker drought resistance. At the system level, Sophora japonica cv. jinhuai exhibited significantly higher water-use efficiency (WUE) than understory medicinal plants in most composite patterns, with pronounced differences in species fitness and poor system stability. The Sophora japonica cv.jinhuai-Camellia limonia-Pilea basicordata (SCP) model exhibited the highest WUE. Furthermore, no significant difference in WUE was observed between Sophora japonica cv.jinhuai and Pilea basicordata, indicating relatively high fitness matching and good coordination in water use. These species can coexist stably, suggesting promising application potential in karst arid environments. Therefore, this study not only evaluated the water-use performance of each species within the composite model but also identified SCP as the most suitable agroforestry configuration for karst regions from a system stability perspective. This provides a scientifically grounded basis for optimising agroforestry practices in these areas, integrating both species-level and system-level perspectives. It should be clarified that the WUE calculated based on δ¹³C in this study is a relative indicator rather than an absolute physiological measurement. Its reliability depends on the core assumptions and parameter settings of the isotope model. Full article

Wolves (Canis lupus) have recolonized Belgium after more than a century of absence, raising concerns about interactions with livestock in densely populated regions such as Flanders. Empirical field-based documentation of wolf behavior near protected livestock in such landscapes remains limited. This study presents a short-term, descriptive camera-trap case study documenting wolf presence near a temporary sheep pasture protected by electric fencing and livestock guardian dogs (LGDs). Nineteen camera traps monitored the pasture perimeter within a military training area in northeastern Flanders over a 16-day period in September 2023. Sheep were present for 11 days and accompanied by six LGDs. Twenty-three wolf images were recorded, corresponding to eight distinct detection events. Wolves were detected shortly after fence installation and following sheep removal. Occasional close approaches and fence inspection behavior were observed, but no fence crossings or predation events occurred. Most wolf detections occurred when sheep and LGDs were absent, although wolves were also recorded near periods of human activity. Given the observational design, causal inference is not possible. The study provides baseline documentation of wolf–livestock–LGD interactions in a densely populated European landscape. Full article

The topographic shadow effect can cause surface reflectance distortions in the shadow areas of remote sensing images, particularly in complex mountainous areas. In this study, based on the difference in solar radiation received at the surface of sunlit and shadow areas, we introduced the shadow intensity, vegetation index, and band adjustment factors, and proposed a topographic shadow effect correction (TSEC) method. The method was then tested using eight Landsat 8 OLI scenes under different illumination conditions from two different regions. The results indicate that TSEC effectively corrected the topographic shadow effect. The corrected images exhibited good visual quality without obvious shadow pixels. Importantly, TSEC retained spectral information in sunlit areas while correcting spectral distortion in shadow areas, resulting in strong agreement between spectral curves of shady and sunny slopes. The method demonstrated high stability in normalized difference vegetation index (NDVI) correction, as the difference in NDVI before and after correction was less than 0.07 for the four scenes within the Changjiang study area. Moreover, the TSEC corrected the enhanced vegetation index (EVI) effectively, reducing an initial EVI difference of over 0.35 between the shady and sunny slopes to a maximum of 0.074 for the four scenes within the Wuyi Mountain study area. Relative to four established topographic correction models, the proposed method suppresses the over-correction phenomena typical of self-shadows and minimizes under-correction in cast shadows, resulting in stable overall correction results with few outliers. The TSEC provides a simple and effective method to correct the distorted reflectance in shadow areas using only image and DEM data, which can be adapted to complex mountainous areas and for images with different illumination conditions. Full article

This study investigates the characteristics of water and sediment evolution under the influence of the Datengxia Water Control Hub Project by analyzing its affected area, with a focus on the driving mechanisms of human activities on these processes. Utilizing hydrological data (1993–2022) from the Wuxuan and Dahuangjiangkou Stations, along with meteorological, land use, and population data, we applied the M–K (Mann–Kendall) trend test, Pettitt change point test, double mass curve method, and a random forest model. These methods were used to quantify the contributions of rainfall and human activities and to identify the dominant controlling factors. Model reliability was verified by comparing predicted and observed P-III (Pearson Type III distribution curve), enabling an assessment of water–sediment changes before and after the project’s construction. The results indicate that (1) both stations showed a non-significant declining trend in runoff and sediment load, with a human activity-induced change point detected in 2003; (2) human activities accounted for 93.18% and 92.38% of the reduction in runoff and sediment load at Wuxuan Station, and 74.44% and 54.33% at Dahuangjiangkou Station, respectively; (3) population density was the dominant factor for water–sediment changes at Wuxuan Station (influence weight: 0.41), while grassland area (0.41) and population density (0.40) primarily controlled runoff and sediment changes, respectively, at Dahuangjiangkou Station; (4) following project construction, the trend of the decreasing flood inundation extent with increasing frequency became more pronounced, and sediment deposition was concentrated mainly in the reservoir area and downstream reaches. The study confirms the dominant role of human activities in the basin’s water–sediment dynamics, and the established methodological framework provides a scientific basis for integrated watershed management and ecological conservation. Full article

Maritime search and rescue (SAR) operations are challenged by vast search areas, poor visibility, and the time-critical nature of victim survival, particularly in dynamic coastal areas. This study presents an intelligent unmanned aerial vehicle (UAV) framework for real-time detection, tracking, and prioritization of people in distress at sea. Unlike existing UAV-based SAR systems that rely on visual sensing or offline human intervention, the proposed framework integrates RGB-thermal multimodal sensing and posture recognition to enhance victim prioritization and survivability estimation. Visual-thermal data support human posture detection, inference of physiological indicators, and autonomous UAV navigation. Metadata are transmitted to a ground control station to enable adaptive altitude control, trajectory rejoining, and multi-target prioritization. Field-inspired experiments in Quang Ninh Province, Vietnam demonstrated robust real-time performance, achieving 23 FPS with detection accuracy up to 84% for swimming subjects and over 50% for drowning postures. These findings demonstrate that Edge-AI-enabled UAVs can serve as a practical and efficient solution for maritime SAR, reducing response times and improving mission outcomes. Full article

This study examined the effects of environmental conditions, behavioral history, management practices, and personality traits on the operational performance of search and rescue (SAR) dogs and dogs admitted to SAR certification testing. Thirty-two handlers completed a questionnaire collecting demographic data, as well as information on their dogs’ behavioral history, management practices, and personality descriptors. Each dog–handler unit also undertook a search trial consisting of locating a hidden person in a wooded area, which was evaluated both by professional instructors and the handlers through ratings of critical behavioral indicators. Objective measurements were obtained through a weather station and GPS devices. Handlers described their dogs mainly in terms of work-relevant traits, such as socio-cognitive engagement, assertiveness, and arousal. The performance evaluation form was practical and efficient, though the Distraction parameter may require refinement, and handler ratings suggested a self-reporting bias. Temperature and wind speed were negatively associated with performance, whereas higher humidity was positively associated with it. Performance was also associated with litter size, age at adoption, dog experience, and management-related factors. Finally, speed, ground coverage, and a canine profile characterized by high arousal and reactivity were strong determinants of good search performance (|ρ| ≥ 0.3; p < 0.05). Although these findings require confirmation in larger samples, search performance appears to be a multifactorial construct shaped by the interplay of extrinsic and intrinsic factors. Defining the contribution of each factor could help optimize performance and dogs’ welfare. Full article

Background/Objectives: Low vaccination coverage and the persistence of zero-dose children remain the principal challenges for immunization efforts in Madagascar. To address these barriers, a socio-anthropological study was conducted to identify the determinants of both vaccination and non-vaccination in eight districts of the country. Methods: District selection was based primarily on immunization performance—specifically the proportion of zero-dose children—along with criteria of geographic and cultural diversity. A qualitative approach was employed, comprising 162 semi-structured individual interviews and 41 focus group discussions with key informants, including political–administrative, religious, and traditional authorities, healthcare workers, community health workers, and parents. Results: Overall, the benefits of vaccination were widely acknowledged by the population. Anti-vaccine rumors were found to be sporadic and, due to their provisional nature, potentially reversible even among those who relay them. Beyond conventional barriers such as scheduling constraints and limited accessibility, fluctuating motivation among community health workers and structural challenges affecting their work emerged as notable findings. Conversely, factors promoting vaccine acceptance were associated with trust in the vaccinators themselves and with a good understanding of vaccination-related issues, fostered through increased and context-specific sensitization efforts. Conclusions: In conclusion, no evidence was found to associate contexts such as rural settings or low-performing vaccination areas with lower vaccine acceptance. Similarly, anti-vaccine rumors were not confined to any particular category or group. Ultimately, the main obstacles are the prioritization of economic risk and concerns about potential side effects. The primary recommendation concerns strengthening awareness-raising efforts, while strengthening trust and improving the working conditions of community health workers. Full article