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Twelve ITER-like plasma-facing units made of tungsten were exposed in the WEST tokamak divertor, with three plasma-facing units (PFUs) significantly overexposed to plasma heat flux: one sharp-edged PFU (vertical misalignment h = 0.8 mm) and two chamfered PFUs (h =0.6 mm and 0.3 mm, respectively). This paper describes the first temperature analysis obtained with a very high spatial resolution infrared camera (pixel size ∼ 0.1 mm) on the misaligned PFU edges and shows the consistency obtained on the parallel heat flux derived from these measurements. The analysis is focused on the hottest areas of the PFU misaligned leading edges, since the temperature detection threshold of the VHR camera is high (Tthreshold,BB ≈ 370 °C). The heat flux parallel to the magnetic field lines is assessed by matching the toroidal temperature profile in the vicinity of the leading edge with 3D finite element modelling. The tungsten emissivity assumed in this study is 0.6, which is consistent with laboratory measurements for damaged PFUs. For the three PFUs studied (with different vertical misalignments, incident angles, geometries), the derived parallel heat flux is similar, and consistent with independent measurements by a Fiber Bragg grating embedded in a graphite PFU at another toroidal location, giving confidence in future experiments using the same settings. [ABSTRACT FROM AUTHOR]

Objective: To retrospectively compare semi-automated and manual volume measurements of malignant liver tumours and inter- and intra-observer variability using commercially available software.Methods: This study was performed on 60 consecutive patients with untreated liver metastases (30) and HCCs (30), i.e. 92 lesions (49 metastases, 43 HCCs) using hepatic MDCT. Lesion volumes were manually measured independently by two radiologists and semi-automatically by the same two radiologists and a technician. Those measurements were repeated on 20 patients (10 metastases and 10 HCCs) a week later. An independent operator timed all the measurements. Using the Spearman correlation coefficient and Bland-Altman plots, statistical analyses were performed.Results: Liver lesion volumes obtained with semi-automated and manual methods were well correlated (Spearman, r = 0.98 and 0.91). Their agreement was high for intra-observer measurements with the semi-automated method (Spearman, r = 0.91 and 0.94). The agreement was lower for inter-observer measurements with both methods (Spearman, r = 0.87 for semi-automated and 0.91 for manual). The semi-automated method significantly reduced the post-processing duration (23s ± 19s vs. 33s ± 11s, p value <0.0001).Conclusion: In our study, semi-automated volume analysis of malignant liver tumours correlated well with the manual method. Furthermore, the semi-automated volume analysis was significantly quicker. [ABSTRACT FROM AUTHOR]

During the 2019 C4 experimental campaign of the WEST (W Environment in Steady-state Tokamak) (France), the infrared diagnostic produced more than seven terabytes of uncompressed video data. Constraints on the computer infrastructure required for storage, backup, and especially offline access to infrared videos made the use of a compression algorithm mandatory. This paper proposes an innovative method to compress infrared videos with controlled temperature precision. This compression method is based on a controlled averaging of the video that maximizes the compression potential of standard lossless video codecs such as H264/AVC or HEVC. The combination of the loss introduction algorithm and the H264/AVC lossless video codec obtains the best compression ratio in the range of 8 to 41 with a maximum temperature error of 2 °C. This method also outperforms the JPEG-LS algorithm in terms of compression ratio and image quality for the same temperature precision., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Photovoltaic (PV) energy generation plays a crucial role in the energy transition. Small-scale, rooftop PV installations are deployed at an unprecedented pace, and their safe integration into the grid requires up-to-date, high-quality information. Overhead imagery is increasingly being used to improve the knowledge of rooftop PV installations with machine learning models capable of automatically mapping these installations. However, these models cannot be reliably transferred from one region or imagery source to another without incurring a decrease in accuracy. To address this issue, known as distribution shift, and foster the development of PV array mapping pipelines, we propose a dataset containing aerial images, segmentation masks, and installation metadata (i.e., technical characteristics). We provide installation metadata for more than 28000 installations. We supply ground truth segmentation masks for 13000 installations, including 7000 with annotations for two different image providers. Finally, we provide installation metadata that matches the annotation for more than 8000 installations. Dataset applications include end-to-end PV registry construction, robust PV installations mapping, and analysis of crowdsourced datasets., (© 2023. The Author(s).)

We demonstrate levels of skill for forecasts of seasonal-mean wind speed and solar irradiance in Europe, using seasonal forecast systems available from the Copernicus Climate Change Service (C3S). While skill is patchy, there is potential for the development of climate services for the energy sector. Following previous studies, we show that, where there is skill, a simple linear regression-based method using the hindcast and forecast ensemble means provides a straightforward approach for producing calibrated probabilistic seasonal forecasts. This method extends naturally to using a larger-scale feature of the climate, such as the North Atlantic Oscillation, as the climate model predictor, and we show that this provides opportunities to improve the skill in some cases. We further demonstrate that, on seasonal-average and regional (e.g. national) average scales, wind and solar power generation are highly correlated with single climate variables (wind speed and irradiance). The detailed non-linear transformations from meteorological quantities to energy quantities, which are essential for detailed simulation of power system operations, are usually not necessary when forecasting gross wind or solar generation potential at seasonal-mean regional-mean scales. Together, our results demonstrate that where there is skill in seasonal forecasts of wind speed and irradiance, or a correlated larger-scale climate predictor, skilful forecasts of seasonal mean wind and solar power generation can be made based on the climate variable alone, without requiring complex transformations. This greatly simplifies the process of developing a useful seasonal climate service., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2022 Published by Elsevier B.V.)

The authors report a case of a 76-year-old man, with not past history of abnormal bleeding, who suffered an acute, recurrent, intestinal haemorrhage from extensive angiodysplasia of the colon. Intestinal bleeding and angiodysplasia were associated with a von Willebrand's disease. Genetic analysis showed a point mutation in arginine 611 of the mature von Willebrand's factor subunit (A1 loop) confirming a von Willebrand's disease type 2.