Found 10488 publications. Showing page 393 of 420:
2025
Fungus-farming termites cultivate a Termitomyces fungus monoculture in enclosed gardens (combs) free of other fungi, except during colony declines, where Pseudoxylaria spp. stowaway fungi appear and take over combs. Here, we determined Volatile Organic Compounds (VOCs) of healthy Macrotermes bellicosus nests in nature and VOC changes associated with comb decay during Pseudoxylaria takeover. We identified 443 VOCs and unique volatilomes across samples and nest volatilomes that were mainly composed of fungus comb VOCs with termite contributions. Few comb VOCs were linked to chemical changes during decay, but longipinocarvone and longiverbenone were only emitted during comb decay. These terpenes may be involved in Termitomyces defence against antagonistic fungi or in fungus-termite signalling of comb state. Both comb and Pseudoxylaria biomass volatilomes contained many VOCs with antimicrobial activity that may serve in maintaining healthy Termitomyces monocultures or aid in the antagonistic takeover by Pseudoxylaria during colony decline. We further observed a series of oxylipins with known functions in the regulation of fungus germination, growth, and secondary metabolite production. Our volatilome map of the fungus-farming termite symbiosis provides new insights into the chemistry regulating complex interactions and serves as a valuable guide for future work on the roles of VOCs in symbioses.
2025
prismAId is an open-source tool designed to streamline systematic literature reviews by leveraging generative AI models for information extraction. It offers an accessible, efficient, and replicable method for extracting and analyzing data from scientific literature, eliminating the need for coding expertise. Supporting various review protocols, including PRISMA 2020, prismAId is distributed across multiple platforms – Go, Python, Julia, R – and provides user-friendly binaries compatible with Windows, macOS, and Linux. The tool integrates with leading large language models (LLMs) such as OpenAI’s GPT series, Google’s Gemini, Cohere’s Command, and Anthropic’s Claude, ensuring comprehensive and up-to-date literature analysis. prismAId facilitates systematic reviews, enabling researchers to conduct thorough, fast, and reproducible analyses, thereby advancing open science initiatives.
2025
2025
Analysis of source regions and transport pathways of sub-micron aerosol components in Europe
It is important to study aerosols and their origins, as they pose various negative health and environmental impacts. In this study, we combined year-long datasets from 15 different countries with Trajectory Statistical Methods (TSMs) for the first time at this comprehensive scale. We found possible source regions and seasonal variations of various particulate matter (PM) components in Europe, including total organic aerosol (OA), biomass burning OA (BBOA), oxygenated OA (OOA), ammonium (NH4), nitrate (NO3), and sulphate (SO4). We found that for all of the studied components, Eastern Europe was among the highest contributors. For NO3, other important source regions were Northern France and the Benelux, while for SO4 there were significant contributions from the Mediterranean region. We also compared our measurement-based model with simulated concentrations of an atmospheric chemistry transport model (CAMx). We observed a satisfactory agreement in regions where we had sufficient coverage with air pollution monitoring stations. The main deviations for OA were found around the Po Valley, where CAMx consistently estimated higher concentrations, while the TSM analysis did not highlight it as a hotspot because long-term monitoring datasets in this region are lacking. CAMx also underestimated the concentrations around Poland, mainly from residential burning. Our results provide opportunities to refine European emission inventories and deliver valuable information on long-range transported air pollutants. This work suggests that policies mitigating air pollution in Eastern Europe and the Benelux could help improve overall air quality in entire Europe more efficiently.
2025
Transboundary pollution by heavy metals and POPs
Meteorological Synthesizing Centre – East (MSC-E)
2025
2025
Oceans pull carbon from air; world not ready to scale up technologies - India Today
Some emissions, especially from aviation, shipping and heavy industry, are nearly impossible to eliminate entirely.
2025
2025
Physics-Informed Deep Learning for Wind Downscaling over Oslo
Running a numerical weather model such as WRF at kilometre or sub-kilometre grid spacing over a regional domain is computationally expensive. We present physics-informed deeplearning models that ingest a single 9km WRF wind field and simultaneously predict two finer-scale wind fields at 3 km and 1 km resolution via dual decoder heads. Four representative architectures are benchmarked-Deep Residual U-Net (DeepRU), DEVINE, a bespoke 3-D Transformer, and a Fourier Neural Operator (FNO)-each trained with divergence-free, vorticity, and Navier-Stokes residual constraints plus Charbonnier and gradient perceptual losses. We train and validate our models on the city of Oslo for the year 2018. DeepRU achieves R2=0.94 (RMSE =0.050) at 3km and R2=0.89(RMSE=0.065) at 1 km. DEVINE, Transformer 3-D, and FNO yield 3 km scores of 0.91−0.93, with 1km scores lower by 0.02−0.08, illustrating the increased difficulty of finer-scale reconstruction. Physicsinformed losses improve all models compared to MSE-only baselines, and the residual architecture (DeepRU) remains most effective for this dual-scale task.
2025
Personalized approaches are required for stroke management due to the variability in symptoms, triggers, and patient characteristics. An innovative stroke recommendation system that integrates automatic predictive analysis with semantic knowledge to provide personalized recommendations for stroke management is proposed by this paper. Stroke exacerbation are predicted and the recommendations are enhanced by the system, which leverages automatic Tree-based Pipeline Optimization Tool (TPOT) and semantic knowledge represented in an OWL Ontology (StrokeOnto). Digital sovereignty is addressed by ensuring the secure and autonomous control over patient data, supporting data sovereignty and compliance with jurisdictional data privacy laws. Furthermore, classifications are explained with Local Interpretable Model-Agnostic Explanations (LIME) to identify feature importance. Tailored interventions based on individual patient profiles are provided by this conceptual model, aiming to improve stroke management. The proposed model has been verified using public stroke dataset, and the same dataset has been utilized to support ontology development and verification. In TPOT, the best Variance Threshold + DecisionTree Classifier pipeline has outperformed other supervised machine learning models with an accuracy of 95.2%, for the used datasets. The Variance Threshold method reduces feature dimensionality with variance below a specified threshold of 0.1 to enhance predictive accuracy. To implement and evaluate the proposed model in clinical settings, further development and validation with more diverse and robust datasets are required.
2025
Sb-PiPLU: A Novel Parametric Activation Function for Deep Learning
The choice of activation function—particularly non-linear ones—plays a vital role in enhancing the classification performance of deep neural networks. In recent years, a variety of non-linear activation functions have been proposed. However, many of these suffer from drawbacks that limit the effectiveness of deep learning models. Common issues include the dying neuron problem, bias shift, gradient explosion, and vanishing gradients. To address these challenges, we introduce a new activation function: Softsign-based Piecewise Parametric Linear Unit (Sb-PiPLU). This function offers improved non-linear approximation capabilities for neural networks. Its piecewise, parametric design allows for greater adaptability and flexibility, which in turn enhances overall model performance. We evaluated Sb-PiPLU through a series of image classification experiments across various Convolutional Neural Network (CNN) architectures. Additionally, we assessed its memory usage and computational cost, demonstrating that Sb-PiPLU is both stable and efficient in practical applications. Our experimental results show that Sb-PiPLU consistently outperforms conventional activation functions in both classification accuracy and computational efficiency. It achieved higher accuracy on multiple benchmark datasets, including CIFAR-10, CINIC-10, MWD, Brain Tumor, and SVHN, surpassing widely-used functions such as ReLU and Tanh. Due to its flexibility and robustness, Sb-PiPLU is particularly well-suited for complex image classification tasks.
2025
2025
2025
An important prerequisite for accurately characterizing economic exposure from climate change at the national scale is a spatial inventory of economic activity and value creation. Current options for such inventories are limited, being either spatially precise but economically bounded sector-specific or owner-specific datasets, or gridded gross domestic product (GDP) products with coarse spatial resolution and inadequate sectoral resolution. To address these limitations, we develop a map of national GDP with high spatial and sectoral resolution. We stress this with meter-scale flood hazard maps to characterize GDP at risk from flooding. We further couple this to a macroeconomic input–output analysis to use the new sectoral resolution to estimate the scope of indirect economic exposure to flood at a national scale.
2025
Environmental pollutants in the terrestrial and urban environment 2024
Samples from the urban terrestrial environment in the Oslo area were analysed for metals and a large number of organic environmental pollutants. The selected sample types that were analysed were soil, earthworm, fieldfare and sparrowhawk eggs, liver samples of brown rat, red fox and badger and blood serum from dog. Biomagnification potential was estimated based on detected data for relevant predator-prey pairs.
NILU
2025