Deep Learning for In-Orbit Cloud Segmentation and Classification in Hyperspectral Satellite Data

This article explores the latest Convolutional Neural Networks (CNNs) for cloud detection aboard hyperspectral satellites. The performance of the latest 1D CNN (1D-Justo-LiuNet) and two recent 2D CNNs (nnU-net and 2D-Justo-UNet-Simple) for cloud segmentation and classification is assessed. Evaluation criteria include precision and computational efficiency for in-orbit deployment. Experiments utilize NASA's EO-1 Hyperion data, with varying spectral channel numbers after Principal Component Analysis. Results indicate that 1D-Justo-LiuNet achieves the highest accuracy, outperforming 2D CNNs, while maintaining compactness with larger spectral channel sets, albeit with increased inference times. However, the performance of 1D CNN degrades with significant channel reduction. In this context, the 2D-Justo-UNet-Simple offers the best balance for in-orbit deployment, considering precision, memory, and time costs. While nnU-net is suitable for on-ground processing, deployment of lightweight 1D-Justo-LiuNet is recommended for high-precision applications. Alternatively, lightweight 2D-Justo-UNet-Simple is recommended for balanced costs between timing and precision in orbit.Comment: Hyperspectral Satellite Data, Cloud Segmentation, Classification, Convolutional Neural Networks, Principal Component Analysi

Advanced Non-animal Models in Biomedical Research: Respiratory Tract Diseases

A study was initiated at the JRC to develop a current overview of available and emerging non-animal models in the field of Respiratory Tract Diseases. In a literature review, over 21,000 abstracts (11,636 non-cancer and 9,421 cancer) were scanned for relevant non-animal methods of respiratory disease. From this, a total of 284 publications were finally identified as being promising candidate methods according to a set of inclusion/exclusion criteria. In vitro cell and tissue cultures, human ex vivo, in silico approaches were chiefly considered. These methods have been collated into a catalogue of biomedical disease models that will form a key knowledge source for researchers, educators and national ethics and funding authorities. The availability of a centralised source of reviewed methods will contribute to extend the requirements of EU Directive 2010/63/EU on the protection of animals used for scientific purposes to biomedical science. Simple cell culture models using immortalised cell lines are long-established, are inexpensive and quick, however they poorly reflect complex disease mechanism observed in vivo. The emerging use of more physiologically-relevant models of disease, such a 3D human tissue cultures, spheroids, organoids, and microfluidic /’lung on a chip’ based systems shows immense promise for the development of in vitro model systems that can more accurately mimic human respiratory diseases. This review shows that, while simple models are still prominent and have their uses, research focus has, in the past 5 years, shifting towards increasingly sophisticated bioengineering approaches that recapitulate lung development, anatomy and physiologic functions in vitro. Such approaches hold the promise of more human-relevant disease models that can be used to elucidate mechanism of disease and aid in the development of new therapies.JRC.F.3-Chemicals Safety and Alternative Method

Advanced Non-animal Models in Biomedical Research: Breast Cancer

The European Commission's Joint Research Centre (JRC) has undertaken a study to review available and emerging non-animal models in the field of breast cancer. In this literature review around 120,000 scientific papers on breast cancer were screened and from those a total of 935 models were identified as being the most representative and promising. These models are based mainly on techniques that use cells and tissues cultured in the laboratory (in vitro), computer modelling and simulation (in silico) or cells and tissues explanted from a patient (ex vivo). This study has produced a unique and highly curated knowledge base that contains detailed descriptions of 935 non-animal models being used for breast cancer research. It is freely available to download and can serve the needs of multiple stakeholders: researchers, educators, funding bodies, and support the implementation of Directive 2010/63/EU on the protection of animals used for scientific purposes.JRC.F.3-Chemicals Safety and Alternative Method