Search Results (3,619)

Relict fern species, confined to microhabitats with stable historical conditions, are especially vulnerable to climate change. The Alboran Arc hosts a unique relict fern flora, including Culcita macrocarpa, Diplazium caudatum, and Pteris incompleta, and functions as a major Pleistocene refuge. This study assesses the population trends and climate sensitivity of these species in Los Alcornocales Natural Park using annual abundance time series for a decade, empirical survival projections, and principal component analysis to identify key climatic drivers. Results reveal distinct climate response clusters among populations, though intra-specific variation highlights the importance of local conditions. Climate change is already impacting population viability, especially for P. incompleta, which shows high sensitivity to rising maximum temperatures and prolonged heatwaves. Climate-driven models forecast more severe declines than empirical ones, particularly for C. macrocarpa and P. incompleta, with the latter showing a projected collapse by the mid-century. In contrast, D. caudatum exhibits moderate vulnerability. Crucially, the divergence between models underscores the impact of conservation efforts: without reinforcement and reintroduction actions, projected declines would likely be more severe. These results project a decline in the populations of the studied ferns, highlighting the urgent need to continue implementing both in situ and ex situ conservation measures. Full article

The placement of hydraulic elements in existing pool-type fishways to make them more suitable for Cyprinid fish is an issue of increasing interest in fishway research. Hydrodynamic characteristics and fish behavior at the representative pool of the fishway with bottom orifices and notches were assessed at the Dagdelen hydropower plant in the Ceyhan River Basin, Türkiye. Three-dimensional velocity measurements were taken in the pool of the fishway using an Acoustic Doppler velocimeter. The measurements were taken with and without a brush block at two different vertical distances from the bottom, which were below and above the level of bristles tips. A computational fluid dynamics (CFD) analysis was conducted for the studied fishway. The numerical model utilized Large Eddy Simulation (LES) combined with the Darcy–Forchheimer law, wherein brush blocks were represented as homogenous porous media. Our results revealed that the relative submergence of bristles in the brush block plays a very important role in velocity and Reynolds shear stress (RSS) distributions. After the placement of the submerged brush block, flow velocity and the lateral RSS component were reduced, and a resting area was created behind the brush block below the bristles’ tips. Fish movements in the pool were recorded by underwater cameras under real-time operation conditions. The heatmap analysis, which is a 2-dimensional fish spatial presence visualization technique for a specific time period, showed that Capoeta damascina avoided the areas with high turbulent fluctuations during the tests, and 61.5% of the fish presence intensity was found to be in the low Reynolds shear regions in the pool. This provides a clear case for the real-world ecological benefits of retrofitting existing pool-weir fishways with such flexible hydraulic elements. Full article

Negative Ion Source Neutral beam Injection (NNBI), as a critical auxiliary heating system for magnetic confinement fusion devices, directly affects the plasma heating efficiency of tokamak devices through the reliability of its beam source system. The single-shot experiment constitutes a significant experimental program for NNBI. This study addresses the frequent equipment failures encountered by the NNBI beam source system during a cycle of experiments, employing fault tree analysis (FTA) to conduct a systematic reliability assessment. Utilizing the AutoFTA 3.9 software platform, a fault tree model of the beam source system was established. Minimal cut set analysis was performed to identify the system’s weak points. The research employed AutoFTA 3.9 for both qualitative analysis and quantitative calculations, obtaining the failure probabilities of critical components. Furthermore, the F-V importance measure and mean time between failures (MTBF) were applied to analyze the system. This provides a theoretical basis and practical engineering guidance for enhancing the operational reliability of the NNBI system. The evaluation methodology developed in this study can be extended and applied to the reliability analysis of other high-power particle acceleration systems. Full article

Corydalis yanhusuo W. T. Wang, commonly known as Yanhusuo, is an important and rare medicinal plant resource in China. Its habitat integrity is facing severe challenges due to climate change and human activities. Establishing an integrative quality zoning system for this species is of significant practical importance for resource conservation and adaptive management. This study integrates multiple data sources, including 121 valid distribution points, 37 environmental factors, future climate scenarios (SSP126 and SSP585 pathways for the 2050s and 2090s), and measured content of tetrahydropalmatine (THP) from 22 sampling sites. A predictive framework for habitat suitability and spatial distribution of effective components was constructed using a multi-model coupling approach (MaxEnt, ArcGIS spatial analysis, and co-kriging method). The results indicate that the MaxEnt model exhibits high prediction accuracy (AUC > 0.9), with the dominant environmental factors being the precipitation of the wettest quarter (404.8~654.5 mm) and the annual average temperature (11.8~17.4 °C). Under current climatic conditions, areas of high suitability are concentrated in parts of Central and Eastern China, including the Sichuan Basin, the middle–lower Yangtze plains, and coastal areas of Shandong and Liaoning. In future climate scenarios, the center of suitable areas is predicted to shift northwestward. The content of THP is significantly correlated with the mean diurnal temperature range, temperature seasonality, and the mean temperature of the wettest quarter (p < 0.01). A comprehensive assessment identifies the Yangtze River Delta region, Central China, and parts of the Loess Plateau as the optimal integrative quality zones. This research provides a scientific basis and decision-making support for the sustainable utilization of C. yanhusuo and other rare medicinal plants in China. Full article

Forestry carbon sinks play a crucial role in mitigating climate change and protecting ecosystems, significantly contributing to the development of carbon trading systems. Remote sensing technology has become increasingly important for monitoring carbon sinks, as it allows for precise measurement of carbon storage and ecological changes, which are vital for forecasting carbon prices. Carbon prices fluctuate due to the interaction of various factors, exhibiting non-stationary characteristics and inherent uncertainties, making accurate predictions particularly challenging. To address these complexities, this study proposes a method for predicting carbon trading prices influenced by multiple factors. We introduce a Decomposition (DECOMP) module that separates carbon price data and its influencing factors into trend and cyclical components. To manage non-stationarity, we propose the KAN with Multi-Domain Diffusion (KAN-MD) module, which efficiently extracts relevant features. Furthermore, a Wave-MH attention module, based on wavelet transformation, is introduced to minimize interference from uncertainties, thereby enhancing the robustness of the model. Empirical research using data from the Hubei carbon trading market demonstrates that our model achieves superior predictive accuracy and resilience to fluctuations compared to other benchmark methods, with an MSE of 0.204% and an MAE of 0.0277. These results provide reliable support for pricing carbon financial derivatives and managing associated risks. Full article

Background/Objectives: Gut microbiota research has gained momentum in recent years broadening knowledge of microbial components and their potential effects on health and well-being. Strong association between explicit microbes and metabolic diseases associated with obesity and type 2 diabetes mellitus, gastrointestinal disorders, neurodegenerative diseases, and even cancers have been established. Akkermansia muciniphila is a budding next-generation probiotic that plays an important role in systemic metabolism, intestinal health, and immune regulation, establishing strong implications for its use as a potent therapeutic intervention in diverse diseases. This project aimed at evaluating whether bacterial cell extracts of VH Akkermansia muciniphila (Vidya Strain; VS) can stimulate insulin secretion in INS-1 pancreatic beta cells and GLP-1 secretion in NCI-H716 human L-cells, both established in vitro models for studying metabolic regulation. Methods: Cultured VH Akkermansia muciniphila extracts were administered in a dose-dependent manner on INS-1 cells, and glucose-stimulated insulin secretion (GSIS) was measured via ELISA. Treated Human L-cell lines (NCI-H716) were analyzed for GLP-1 secretion. Results: Our study demonstrated that VH Akkermansia muciniphila extracts modestly increase insulin secretion from INS-1 beta cells and, more notably, induce a robust, dose-dependent rise in GLP-1 secretion from NCI-H716 L-cells, with the highest dose achieving over a 2000% increase comparable to glutamine. Conclusions: These findings suggest that VH A. muciniphila extracts may offer metabolic benefits by enhancing GLP-1 release, highlighting their potential for managing type 2 diabetes and obesity. Full article

There is limited published guidance available to help less experienced practitioners assess and manage shoulder conditions, including spasticity, after acquired central nervous system (CNS) lesions. To address this gap, 11 spasticity and dystonia experts convened in a 2023 meeting to build on existing guidance, provide consensus on best treatment practice, and develop expert recommendations to guide the diagnosis and treatment of complications of shoulder conditions following CNS lesions. Presentations by each expert on diagnosis and management were followed by discussion; consensus on assessment and treatment practices was identified and recommendations developed. The expert panel recommended an assessment approach structured using the following components: patient history, including interpretation of reported symptoms; observation of postures and pain responses; clinical examination with targeted tests for specific signs; diagnostic tests; and assessment of upper limb impairment, activity limitations, and participation restrictions. This assessment process and the recommended measures recognize the importance of identifying shoulder involvement in upper limb spasticity as part of the diagnostic process in shoulder conditions following CNS lesions. These recommendations provide a practical approach to diagnosis and treatment for clinicians who are less experienced in evaluating and treating such conditions, simplifying otherwise complicated clinical scenarios. Full article

Background: Preterm infants and their families face a challenging experience during their stay in the neonatal intensive care unit (NICU). Family-centered care emphasizes the importance of welcoming parents, involving them in their baby’s daily care, and supporting the development of parenting skills. NICU staff should support parents in understanding their baby’s needs and in strengthening the parent–infant bond. Although many tools outline what parents should learn, there is a limited structured framework to monitor their involvement in the infant’s care. Tracking parental participation in daily caregiving activities could support professionals in effectively guiding families, ensuring a smoother transition to discharge. Aims: The aim of this study was to evaluate the adherence to and effectiveness of a structured tool for parental involvement in the NICU. This tool serves several key purposes: to track the progression and timing of parents’ autonomy in caring for their baby, to support parents in building caregiving competencies before discharge, and to standardize the approach of NICU professionals in promoting both infant care and family engagement. Methods: A structured template form for documenting parental involvement (“together TO-CARE template”, TTCT) was integrated into the computerized chart adopted in the NICU of Modena. Nurses were asked to complete the TTCT at each shift. The template included the following assessment items: parental presence; type of contact with the baby (touch; voice; skin-to-skin); parental involvement in care activities (diaper changing; gavage feeding; bottle feeding; breast feeding); and level of autonomy in care (observer; supported by nurse; autonomous). We evaluated TTCT uploaded data for very low birth weight (VLBW) preterm infants admitted in the Modena NICU between 1 January 2023 and 31 December 2024. Staff compliance in filling out the TTCT was assessed. The timing at which parents achieved autonomy in different care tasks was also measured. Results: The TTCT was completed with an average of one entry per day, during the NICU stay. Parents reached full autonomy in diaper changing at a mean of 21.1 ± 15.3 days and in bottle feeding at a mean of 48.0 ± 22.4 days after admission. The mean length of hospitalization was 53 ± 38 days. Conclusions: The adoption of the TTCT in the NICU is feasible and should become a central component of care for preterm infants. It promotes family-centered care by addressing the needs of both the baby and the family. Encouraging early and progressive parental involvement enhances parenting skills, builds confidence, and may help reduce post-discharge complications and readmissions. Furthermore, the use of a standardized template aims to foster consistency among NICU staff, reduce disparities in care delivery, and strengthen the support provided to families of preterm infants. Full article

Early evacuation during bushfires remains the safest strategy; however, in many realistic scenarios, timely evacuation is challenging, making safe sheltering a last-resort option to reduce risk compared to late evacuation attempts. However, most Australian homes in bushfire-prone areas are neither designed nor retrofitted to provide adequate protection against extreme bushfires, raising safety concerns. This study addresses this gap by investigating the concept of retrofitting a part of the residential buildings as attached safe rooms for sheltering and protection of valuables, providing a potential last-resort solution for bushfire-prone communities. Numerical simulations were conducted using the Fire Dynamics Simulator to assess heat transfer and internal temperature conditions in a representative residential building under bushfire exposure conditions. The study investigated the impact of the placement of the safe room relative to the fire front direction, failure of vulnerable building components, and the effectiveness of steel shutters in response to internal temperatures. The results showed that the strategic placement of safe rooms inside the building, along with adequate protective measures for windows, can substantially reduce internal temperatures. The findings emphasised the importance of maintaining the integrity of openings and the external building envelope, demonstrating the potential of retrofitted attached safe rooms as a last-resort solution for existing residential buildings in bushfire-prone areas where the entire building was not constructed to withstand bushfire conditions. Full article

Background: The anterior cerebral artery (ACA), a critical component of the cerebral arterial circle, exhibits substantial morphological variability. While previous studies have explored ACA morphology using cadaveric and imaging methods, a comprehensive meta-analysis incorporating the latest evidence is lacking. Methods: Following current guidelines, a systematic review and meta-analysis were performed across four major databases, supplemented by the gray literature and targeted journal searches. Ninety-nine studies, encompassing 85,316 patients, met the inclusion criteria. Statistical analyses were conducted using R, applying random effects models to estimate pooled prevalence and morphometric parameters. Results: The pooled prevalence of typical ACA morphology was 93.75%, whereas variants were noted in 6.25% of cases. The predominant variation identified was the accessory ACA (aACA) (1.99%), followed by unilateral absence of the A1 segment (1.78%), with the latter being more frequently recognized in imaging studies (p < 0.0001). Rare variants encompassed azygos ACA (azACA) (0.22%), fenestrated ACA (fACA) (0.02%), and bihemispheric ACA (bACA) (0.02%). The mean diameter and length of the A1 segment were measured at 2.10 mm and 14.24 mm, respectively. Hypoplasia of the A1 segment (<1 mm diameter) was recorded in 3.15% of cases. The influences of imaging modality, laterality, and population distribution on prevalence estimates were minimal. No significant publication bias was detected. Conclusions: Although infrequent, variants of the ACA possess significant clinical importance attributable to their correlation with aneurysm formation and the impairment of collateral circulation. The aACA and the absence of the A1 segment emerged as the most common variations. This meta-analysis presents an updated and high-quality synthesis of ACA morphology, serving as a valuable reference for clinicians and anatomists. Full article

Social network platforms have a big impact on the development of companies by influencing clients’ behaviors and sentiments, which directly affect corporate reputations. Analyzing this feedback has become an essential component of business intelligence, supporting the improvement of long-term marketing strategies on a larger scale. The implementation of powerful sentiment analysis models requires a comprehensive and in-depth examination of each stage of the process. In this study, we present a new comparative approach for several feature extraction techniques, including TF-IDF, Word2Vec, FastText, and BERT embeddings. These methods are applied to three multilingual datasets collected from hotel review platforms in the tourism sector in English, French, and Arabic languages. Those datasets were preprocessed through cleaning, normalization, labeling, and balancing before being trained on various machine learning and deep learning algorithms. The effectiveness of each feature extraction method was evaluated using metrics such as accuracy, F1-score, precision, recall, ROC AUC curve, and a new metric that measures the execution time for generating word representations. Our extensive experiments demonstrate significant and excellent results, achieving accuracy rates of approximately 99% for the English dataset, 94% for the Arabic dataset, and 89% for the French dataset. These findings confirm the important impact of vectorization techniques on the performance of sentiment analysis models. They also highlight the important relationship between balanced datasets, effective feature extraction methods, and the choice of classification algorithms. So, this study aims to simplify the selection of feature extraction methods and appropriate classifiers for each language, thereby contributing to advancements in sentiment analysis. Full article

The increasing complexity of modern control systems highlights the need for reliable and robust fault detection, isolation, and identification (FDII) methods, particularly in safety-critical and industrial applications. The study focuses on the FDII of multiplicative faults in a DC motor and its electronic amplifier. To simulate such scenarios, a complete laboratory platform was developed for real-time FDII, using relay-based switching and custom LabVIEW software 2009. This platform enables real-time experimentation and represents an important component of the study. Two estimation-based fault detection (FD) algorithms were implemented: the Sliding Window Algorithm (SWA) for discrete-time models and a modified Sliding Integral Algorithm (SIA) for continuous-time models. The modification introduced to the SIA limits the data length used in least squares estimation, thereby reducing the impact of transient effects on parameter accuracy. Both algorithms achieved high model output-to-measured signal agreement, up to 98.6% under nominal conditions and above 95% during almost all fault scenarios. Moreover, the proposed fault isolation and identification methods, including a decision algorithm and an indirect estimation approach, successfully isolated and identified faults in key components such as amplifier resistors (R₁, R₉, R₁₂), capacitor (C₈), and motor parameters, including armature resistance (R_a), inertia (J), and friction coefficient (B). The decision algorithm, based on continuous-time model coefficients, demonstrated reliable fault isolation and identification, while the reduced Jacobian-based approach in the discrete model enhanced fault magnitude estimation, with deviations typically below 10%. Additionally, the platform supports remote experimentation, offering a valuable resource for advancing model-based FDII research and engineering education. Full article

The arboreal rodent Oecomys catherinae, which has a wide geographic distribution across Brazilian biomes, provides a model for investigating environmental influences on morphological variation. We assessed craniodental differences between the Atlantic Forest and Cerrado biomes, as well as along latitudinal gradients, using 45 specimens from 18 localities. Linear morphometric analyses (21 measurements) revealed no significant sexual dimorphism, allowing for pooled analyses. Principal Component Discriminant Analysis (DAPC) confirmed significant morphological divergence between biomes (72% accuracy, p < 0.01). We identified bony palate length (BPL) as the most discriminating variable, with higher values in the Atlantic Forest, suggesting a possible dietary adaptation in response to ecological pressures. Latitudinal effects were modest (adjusted R² = 0.05) although significant (F_1,43 = 3.63; p = 0.03), with southern populations exhibiting larger cranial dimensions than northern ones. We conclude that biome type and latitude played important roles in shaping cranial morphology in O. catherinae populations. Full article

Mangrove forests are widely recognized for their effectiveness as carbon sinks and serve as critical ecosystems for mitigating the effects of climate change. Current research lacks comprehensive, large-scale carbon storage datasets for wetland ecosystems, particularly across Mexico and other understudied regions worldwide. Therefore, the objective of this study was to develop a high spatial resolution map of carbon stocks, encompassing both aboveground and belowground components, within the Marismas Nacionales system, which is the largest mangrove complex in northeastern Pacific Mexico. Our approach integrates primary field data collected during 2023–2024 and incorporates some historical plot measurements (2011–present) to enhance spatial coverage. These were combined with contemporary remote sensing data, including Sentinel-1, Sentinel-2, and LiDAR, analyzed using Random Forest algorithms. Our spatial models achieved strong predictive accuracy (R² = 0.94–0.95), effectively resolving fine-scale variations driven by canopy structure, hydrologic regime, and spectral heterogeneity. The application of Local Indicators of Spatial Association (LISA) revealed the presence of carbon “hotspots,” which encompass 33% of the total area but contribute to 46% of the overall carbon stocks, amounting to 21.5 Tg C. Notably, elevated concentrations of carbon stocks are observed in the central regions, including the Agua Brava Lagoon and at the southern portion of the study area, where pristine mangrove stands thrive. Also, our analysis reveals that 74.6% of these carbon hotspots fall within existing protected areas, demonstrating relatively effective—though incomplete—conservation coverage across the Marismas Nacionales wetlands. We further identified important cold spots and ecotones that represent priority areas for rehabilitation and adaptive management. These findings establish a transferable framework for enhancing national carbon accounting while advancing nature-based solutions that support both climate mitigation and adaptation goals. Full article

Ammonia (NH₃), as a vital component of the nitrogen cycle, exerts significant influence on the biosphere, air quality, and climate by contributing to secondary aerosol formation through its reactions with sulfur dioxide (SO₂) and nitrogen oxides (NO_x). Despite its critical environmental role, NH₃’s transient atmospheric lifetime and the variability in spatial and temporal distributions pose challenges for effective global monitoring and comprehensive impact assessment. Recognizing the inadequacies in current in situ measurement capabilities, this study embarked on an extensive analysis of NH₃’s temporal and spatial characteristics over East Asia, using the Infrared Atmospheric Sounding Interferometer (IASI) onboard the MetOp-B satellite from 2013 to 2024. The atmospheric NH₃ concentrations exhibit clear seasonality, beginning to rise in spring, peaking in summer, and then decreasing in winter. Overall, atmospheric NH₃ shows an annual increasing trend, with significant increases particularly evident in Eastern China, especially in June. The regional NH₃ trends within China have varied, with steady increases across most regions, while the Northeastern China Plain remained stable until a recent rapid rise. South Korea continues to show consistent and accelerating growth. East Asia demonstrates similar NH₃ emission characteristics, driven by farmland and livestock. The spatial and temporal inconsistencies between satellite data and global chemical transport models underscore the importance of establishing accurate NH₃ emission inventories in East Asia. Full article