Found 9791 publications. Showing page 389 of 392:
CompSafeNano project: NanoInformatics approaches for safe-by-design nanomaterials
The CompSafeNano project, a Research and Innovation Staff Exchange (RISE) project funded under the European Union's Horizon 2020 program, aims to advance the safety and innovation potential of nanomaterials (NMs) by integrating cutting-edge nanoinformatics, computational modelling, and predictive toxicology to enable design of safer NMs at the earliest stage of materials development. The project leverages Safe-by-Design (SbD) principles to ensure the development of inherently safer NMs, enhancing both regulatory compliance and international collaboration. By building on established nanoinformatics frameworks, such as those developed in the H2020-funded projects NanoSolveIT and NanoCommons, CompSafeNano addresses critical challenges in nanosafety through development and integration of innovative methodologies, including advanced in vitro models, in silico approaches including machine learning (ML) and artificial intelligence (AI)-driven predictive models and 1st-principles computational modelling of NMs properties, interactions and effects on living systems. Significant progress has been made in generating atomistic and quantum-mechanical descriptors for various NMs, evaluating their interactions with biological systems (from small molecules or metabolites, to proteins, cells, organisms, animals, humans and ecosystems), and in developing predictive models for NMs risk assessment. The CompSafeNano project has also focused on implementing and further standardising data reporting templates and enhancing data management practices, ensuring adherence to the FAIR (Findable, Accessible, Interoperable, Reusable) data principles. Despite challenges, such as limited regulatory acceptance of New Approach Methodologies (NAMs) currently, which has implications for predictive nanosafety assessment, CompSafeNano has successfully developed tools and models that are integral to the safety evaluation of NMs, and that enable the extensive datasets on NMs safety to be utilised for the re-design of NMs that are inherently safer, including through prediction of the acquired biomolecule coronas which provide the biological or environmental identities to NMs, promoting their sustainable use in diverse applications. Future efforts will concentrate on further refining these models, expanding the NanoPharos Database, and working with regulatory stakeholders thereby fostering the widespread adoption of SbD practices across the nanotechnology sector. CompSafeNano's integrative approach, multidisciplinary collaboration and extensive stakeholder engagement, position the project as a critical driver of innovation in NMs SbD methodologies and in the development and implementation of computational nanosafety.
Elsevier
2025
The complex and dynamic nature of airborne fine particulate matter (PM2.5) has hindered understanding of its chemical composition, sources, and toxic effects. In the first steps of a larger study, here, we aimed to elucidate relationships between source regions, ambient conditions, and the chemical composition in water extracts of PM2.5 samples (n = 85) collected over 16 months at an observatory in the Yellow Sea. In each extract, we quantified elements and major ions and profiled the complex mixtures of organic compounds by nontarget mass spectrometry. More than 50,000 nontarget features were detected, and by consensus of in silico tools, we assigned a molecular formula to 13,907 features. Oxygenated compounds were most prominent, followed by mixed nitrogenated/oxygenated compounds, organic sulfates, and sulfonates. Spectral matching enabled identification or structural annotation of 43 substances, and a workflow involving SIRIUS and MS-DIAL software enabled annotation of 74 unknown per- and polyfluoroalkyl substances with primary source regions in China and the Korean Peninsula. Multivariate modeling revealed seasonal variations in chemistry, attributable to the combination of warmer temperatures and maritime source regions in summer and to cooler temperatures and source regions of China in winter.
2025
2025
Intrusion Detection Systems (IDS) are critical in safeguarding network infrastructures against malicious attacks. Traditional IDSs often struggle with knowledge representation, real-time detection, and accuracy, especially when dealing with high-throughput data. This paper proposes a novel IDS framework that leverages machine learning models, streaming data, and semantic knowledge representation to enhance intrusion detection accuracy and scalability. Additionally, the study incorporates the concept of Digital Sovereignty, ensuring that data control, security, and privacy are maintained according to national and regional regulations. The proposed system integrates Apache Kafka for real-time data processing, an automatic machine learning pipeline (e.g., Tree-based Pipeline Optimization Tool (TPOT)) for classifying network traffic, and OWL-based semantic reasoning for advanced threat detection. The proposed system, evaluated on NSL-KDD and CIC-IDS-2017 datasets, demonstrated qualitative outcomes such as local compliance, reduced data storage needs due to real-time processing, and improved adaptability to local data laws. Experimental results reveal significant improvements in detection accuracy, processing efficiency, and Sovereignty alignment.
Elsevier
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.
IEEE (Institute of Electrical and Electronics Engineers)
2025
Methane in Svalbard (SvalGaSess)
Methane is a powerful greenhouse gas whose emission into the atmosphere from Arctic environments is increasing in response to climate change. At present, the increase in atmospheric methane concentrations recorded at Ny-Ålesund and globally threatens the Paris Agreement goal of limiting warming to 2 degrees, preferably 1.5 degrees, by increasing the need for abatements. However, our understanding of the physical, chemical and biological processes that control methane in the Arctic are strongly biased towards just a few lowland sites that are not at all like Svalbard and other similar mountainous, ice-covered regions. Svalbard can therefore be used to better understand these locations. Svalbard’s methane stocks include vast reserves of ancient, geogenic methane trapped beneath glaciers and permafrost. This methane supplements the younger, microbial methane mostly produced in waterlogged soils and wetlands during the summer and early winter. Knowledge about the production, removal and migration of these two methane sources in Svalbard’s complex landscapes and coastal environments has grown rapidly in recent years. However, the need to exploit this knowledge to produce reliable estimates of present-day and future emissions of methane from across the Svalbard landscape is now paramount. This is because understanding these quantities is absolutely necessary when we seek to define how society must adjust in order to better manage greenhouse gases in Earth’s atmosphere
2025
2025
A case study of the effect of permafrost peat on fires in the Arctic using Sentinel-5P data
Elsevier
2025
2025
VKM has assessed the positive and negative effects on biodiversity were sterile salmon to be used in Norwegian aquaculture. Triploidisation is assessed as the most effective method for sterilising fish, but it can affect the welfare and health of the fish.
Several other techniques for producing sterile salmon are being tested, but it is too early to determine whether they can be used in large-scale farming.
This is the key message in a knowledge summary VKM has prepared for the Norwegian Environment Agency.
Background
Escaped farmed salmon poses a major threat to wild salmon in Norway. hey can interbreed with wild salmon, genetically alter them, and make the populations less adaptable and more vulnerable to disease and environmental changes. A possible solution to the problem may be to use sterile salmon in farming.
To date, only triploidisation has been tested. Newly fertilised eggs are given a hydrostatic pressure shock, thereby retaining an extra set of chromosomes which render the fish sterile. This method is currently the only one tested on a large scale. Triploidisation is effective but can also pose health and welfare challenges to fish.
Methods
VKM has reviewed available scientific literature regarding methods that can be used to produce sterile salmon. VKM has assessed whether these methods work as well, or better, than triploidy and whether they are likely to have fewer negative effects on fish welfare. Assessments have also been made of whether farmed fish treated with other sterilisation methods pose a greater or lesser threat to wild salmon than traditional farmed salmon.
VKM has looked at the possibilities for further development of the triploidisation technique and has also assessed various methods currently being tested for producing sterile fish. Some of these are still at the laboratory-testing stage, while others are approaching trials with release into sea-pens. VKM has grouped the different methods based on whether they cause permanent changes in the genome (so-called "knock-out" of important genes) or whether the changes only result in temporary blocking or downregulation of gene expression (so-called "knock-down").
Results
VKM concludes that triploidisation remains the most effective method and that there are possibilities to further develop this methodology through targeted breeding and adjustments in how the fish are kept. These measures can potentially solve the challenges for fish health and welfare. Using pure triploid female lines can also reduce some of the other challenges by preventing spawning interactions in rivers and reducing disease transmission to wild salmon.
Alternative sterilisation methods, such as gene editing, vaccination, and temporary downregulation of proteins for gonad development using antisense oligomers and egg immersion, are promising but still under development.
VKM assesses that methods causing permanent changes in the genome of diploid fish have a higher inherent risk than methods that only affect gene expression.
Hope in egg-bathing
Perhaps the most promising technique for safe production of sterile salmon is to add synthetic oligonucleotides to the eggs at an early stage, thereby preventing germ cell development without causing any inheritable changes. Such oligonucleotides can be injected into the eggs or absorbed by the eggs through bathing (immersion) in a special solution.
"Especially the method involving targeted 'tools,' such as oligonucleotides that prevent germ cell development and can be added to the eggs in a water bath, seems promising," says Johanna Bodin, member of the Panel for Genetically Modified organisms and spokesperson for the report.
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2025
Skogens helsetilstand i Norge. Resultater fra skogskadeovervåkingen i 2023
Skogens helsetilstand påvirkes i stor grad av klima og værforhold, enten direkte ved tørke, frost og vind, eller indirekte ved at klimaet påvirker omfanget av soppsykdommer og insektangrep. Klimaendringene og den forventede økningen i klimarelaterte skogskader gir store utfordringer for forvaltningen av framtidas skogressurser. Det samme gjør invaderende skadegjørere, både allerede etablerte arter og nye som kan komme til Norge i nær framtid. I denne rapporten presenteres resultater fra skogskadeovervåkingen i Norge i 2023 og trender over tid for følgende temaer:
(i) Landsrepresentativ skogovervåking;
(ii) Intensiv skogovervåking;
(iii) Overvåking av bjørkemålere i Troms og Finnmark;
(iv) Barkbilleovervåkingen 2023: økende fangster – særlig i stormrammede områder;
(v) Søk etter Ips-arter utenfor det nordvestlige hjørnet av granas utbredelse i Europa;
(vi) Askeskuddsyke;
(vii) Andre spesielle skogskader i 2023.
NIBIO
2025
Atmospheric ammonia (NH3) is a key transboundary air pollutant that contributes to the impacts of nitrogen and acidity on terrestrial ecosystems. Ammonia also contributes to the atmospheric aerosol that affects air quality. Emission inventories indicate that NH3 was predominantly emitted by agriculture over the 19th and 20th centuries but, up to now, these estimates have not been compared to long-term observations. To document past atmospheric NH3 pollution in south-eastern Europe, ammonium (NH) was analysed along an ice core extracted from Mount Elbrus in the Caucasus, Russia. The NH ice-core record indicates a 3.5-fold increase in concentrations between 1750 and 1990 CE. Remaining moderate prior to 1950 CE, the increase then accelerated to reach a maximum in 1989 CE. Comparison between ice-core trends and estimated past emissions using state-of-the-art atmospheric transport modelling of submicron-scale aerosols (FLEXPART (FLEXible PARTicle dispersion) model) indicates good agreement with the course of estimated NH3 emissions from south-eastern Europe since ∼ 1750 CE, with the main contributions from south European Russia, Türkiye, Georgia, and Ukraine. Examination of ice deposited prior to 1850 CE, when agricultural activities remained limited, suggests an NH ice concentration related to natural soil emissions representing ∼ 20 % of the 1980–2009 CE NH level, a level mainly related to current agricultural emissions that almost completely outweigh biogenic emissions from natural soil. These findings on historical NH3 emission trends represent a significant contribution to the understanding of ammonia emissions in Europe over the last 250 years.
2025
Metaller, PCB, PAH og dioksiner i mose i Sør-Varanger. Moseundersøkelser 2008, 2015 og 2020
I 2008 samlet Svanhovd Miljøsenter inn mose ved 11 lokaliteter i grenseområdene mot Russland som NILU analyserte for 11 metaller, PCB, PAH og dioksiner. Formålet var å undersøke om det var andre kilder til forurensning i grenseområdene enn gruvedrift og smelteverksindustri. Prøvetaking og analyse ble gjentatt av NILU i 2015 og 2020, men kun for 60 (2015) og 56 (2020) metaller. For spormetallene Ni, Cu, Co og As er det et klart mønster med forhøyede konsentrasjoner nedstrøms Nikel og Zapolyarnyj. Organiske miljøgifter viser lave konsentrasjoner.
NILU
2025
Climatic feedbacks and ecosystem impacts related to dust in the Arctic include direct radiative forcing (absorption and scattering), indirect radiative forcing (via clouds and cryosphere), semi-direct effects of dust on meteorological parameters, effects on atmospheric chemistry, as well as impacts on terrestrial, marine, freshwater, and cryospheric ecosystems. This review discusses our recent understanding on dust emissions and their long-range transport routes, deposition, and ecosystem effects in the Arctic. Furthermore, it demonstrates feedback mechanisms and interactions between climate change, atmospheric dust, and Arctic ecosystems.
Frontiers Media S.A.
2025
2025
At the same time Arctic ecosystems experiences rapid climate change, at a rate four times faster than the global average, they remain burdened by long-range transported pollution, notably with legacy polychlorinated biphenyls (PCBs). The present study investigates the potential impact of climate change on seabird exposure to PCB-153 using the established Nested Exposure Model (NEM), here expanded with three seabird species, i.e. common eider (Somateria mollissima), black-legged kittiwake (Rissa tridactyla) and glaucous gull (Larus hyperboreus), as well as the filter feeder blue mussel (Mytulis edulis). The model's performance was evaluated using empirical time trends of the seabird species in Kongsfjorden, Svalbard, and using tissue concentrations from filter feeders along the northern Norwegian coast. NEM successfully replicated empirical PCB-153 concentrations, confirming its ability to simulate PCB-153 bioaccumulation in the studied seabird species within an order of magnitude. Based on global PCB-153 emission estimates, simulations run until the year 2100 predicted seabird blood concentrations 99% lower than in year 2000. Model scenarios with climate change-induced altered dietary composition and lipid dynamics showed to have minimal impact on future PCB-153 exposure, compared to temporal changes in primary emissions of PCB-153. The present study suggests the potential of mechanistic modelling in assessing POP exposure in Arctic seabirds within a multiple stressor context.
Royal Society of Chemistry (RSC)
2025
2025
2025