Improved marine debris detection in satellite imagery with automatic refinement of coarse hand annotations

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Shoreline protection systems composed of fibre-polymer composite structures immersed in seawater may efficiently contribute to mitigate impacts of climate change, such as more frequent and severe coastal flooding and storm surges, and significant rises of ...

Petroleum-based microplastic particles (MPs) are carriers of antimicrobial resistance genes (ARGs) in aquatic environments, influencing the selection and spread of antimicrobial resistance. This research characterized MP and natural organic particle (NOP) ...

Microplastics, especially aged microplastics can become vectors of metals from environment to organisms with potential negative effects on food chain. However, a few studies focused on the bioavailability of adsorbed metals and most studies related to aged ...

Humans are chronically exposed to airborne microplastics (MPs) by inhalation. Various types of polymer particles have been detected in lung samples, which could pose a threat to human health. Inhalation toxicological studies are crucial for assessing the e ...

The rates of tropical deforestation remain high, resulting in carbon emissions, biodiversity loss, and impacts on local communities. To design effective policies to tackle this, it is necessary to know what the drivers behind deforestation are. Since drive ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Detecting and quantifying marine pollution and macroplastics is an increasingly pressing ecological issue that directly impacts ecology and human health. Here, remote sensing can provide reliable estimates of plastic pollution by regularly monitoring and d ...

The study of non-contact manipulation in water, and the ability to robotically control floating objects has gained recent attention due to wide-ranging potential applications, including the analysis of plastic pollution in the oceans and the optimization o ...

Direct photolysis and indirect photolysis are important abiotic processes in aquatic environments through which plastics can be transformed physically and chemically. Transport of biodegradable plastics in water is influenced by vertical mixing and turbule ...

Enhancing the surface charge density and reducing the output impedance via innovative techniques are essential to accelerate the commercialization of triboelectric nanogenerators (TENGs). However, methods for increasing output performance have numerous lim ...

The management of plastic waste is a growing concern that can harm wildlife and ecosystems, and its end-of-life policies are key to mitigating plastic environmental impact. This work presents a decision-making methodology for the thermal and material valor ...

Tropical deforestation is a major environmental problem with severe consequences such as carbon emissions or biodiversity loss. While much research focuses on monitoring and mapping deforestation, less attention is paid to understanding the various reasons ...

Curvilinear structures are frequently observed in a variety of domains and are essential for comprehending neural circuits, detecting fractures in materials, and determining road and irrigation canal networks. It can be costly and time-consuming to manuall ...

Crop maps are crucial for agricultural monitoring and food management and can additionally support domain-specific applications, such as setting cold supply chain infrastructure in developing countries. Machine learning (ML) models, combined with freely-av ...

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really gener ...

In this paper, we propose and compare personalized models for Productive Engagement (PE) recognition. PE is defined as the level of engagement that maximizes learning. Previously, in the context of robot-mediated collaborative learning, a framework of prod ...

Author summaryIn recent years, the application of deep learning represented a breakthrough in the mass spectrometry (MS) field by improving the assignment of the correct sequence of amino acids from observable MS spectra without prior knowledge, also known ...

The goal of habitat suitability mapping is to predict the lo-cations in which a given species could be present. This is typically accomplished by statistical models which use envi-ronmental variables to predict species observation data. The relationship be ...

Artificial intelligence, particularly the subfield of machine learning, has seen a paradigm shift towards data-driven models that learn from and adapt to data. This has resulted in unprecedented advancements in various domains such as natural language proc ...

Improved marine debris detection in satellite imagery with automatic refinement of coarse hand annotations

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Composite engineering structures in seawater − Review of durability and environmental performance

Parity in bacterial communities and resistomes: Microplastic and natural organic particles in the Tyrrhenian Sea

Adsorption of Copper by Naturally and Artificially Aged Polystyrene Microplastics and Subsequent Release in Simulated Gastrointestinal Fluid

Inhalation of Microplastics—A Toxicological Complexity

Mapping drivers of tropical forest loss with satellite image time series and machine learning

Predicting the long-term collective behaviour of fish pairs with deep learning

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Large-scale detection of marine debris in coastal areas with Sentinel-2

Non-contact robotic manipulation of floating objects: exploiting emergent limit cycles

Photodegradation of biodegradable plastics in aquatic environments: Current understanding and challenges

High-performance triboelectric nanogenerator via photon-generated carriers for green low-carbon system

On the role of system integration in plastic waste management

Classification of Tropical Deforestation Drivers with Machine Learning and Satellite Image Time Series

Topologically Better Delineation of Curvilinear Structures

Using machine learning to generate an open-access cropland map from satellite images time series in the Indian Himalayan region

Why is the winner the best?

Personalized Productive Engagement Recognition in Robot-Mediated Collaborative Learning

Multienzyme deep learning models improve peptide de novo sequencing by mass spectrometry proteomics

Training Techniques for Presence-Only Habitat Suitability Mapping with Deep Learning

Breaking the Curse of Dimensionality in Deep Neural Networks by Learning Invariant Representations