30 research outputs found

    Is the meiofauna a good indicator for climate change and anthropogenic impacts?

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    Our planet is changing, and one of the most pressing challenges facing the scientific community revolves around understanding how ecological communities respond to global changes. From coastal to deep-sea ecosystems, ecologists are exploring new areas of research to find model organisms that help predict the future of life on our planet. Among the different categories of organisms, meiofauna offer several advantages for the study of marine benthic ecosystems. This paper reviews the advances in the study of meiofauna with regard to climate change and anthropogenic impacts. Four taxonomic groups are valuable for predicting global changes: foraminifers (especially calcareous forms), nematodes, copepods and ostracods. Environmental variables are fundamental in the interpretation of meiofaunal patterns and multistressor experiments are more informative than single stressor ones, revealing complex ecological and biological interactions. Global change has a general negative effect on meiofauna, with important consequences on benthic food webs. However, some meiofaunal species can be favoured by the extreme conditions induced by global change, as they can exhibit remarkable physiological adaptations. This review highlights the need to incorporate studies on taxonomy, genetics and function of meiofaunal taxa into global change impact research

    Review of thermo-physical properties, wetting and heat transfer characteristics of nanofluids and their applicability in industrial quench heat treatment

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    The success of quenching process during industrial heat treatment mainly depends on the heat transfer characteristics of the quenching medium. In the case of quenching, the scope for redesigning the system or operational parameters for enhancing the heat transfer is very much limited and the emphasis should be on designing quench media with enhanced heat transfer characteristics. Recent studies on nanofluids have shown that these fluids offer improved wetting and heat transfer characteristics. Further water-based nanofluids are environment friendly as compared to mineral oil quench media. These potential advantages have led to the development of nanofluid-based quench media for heat treatment practices. In this article, thermo-physical properties, wetting and boiling heat transfer characteristics of nanofluids are reviewed and discussed. The unique thermal and heat transfer characteristics of nanofluids would be extremely useful for exploiting them as quench media for industrial heat treatment

    <em>Euclid</em>: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field

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    \ua9 The Authors 2025.The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientists alone is infeasible. As a result, machine learning algorithms, particularly convolutional neural networks (CNNs), have been used as an automated method of detecting strong lenses, and have proven fruitful in finding galaxy-galaxy strong lens candidates, such that the usage of CNNs in lens identification has increased. We identify the major challenge to be the automatic detection of galaxy-galaxy strong lenses while simultaneously maintaining a low false positive rate, thus producing a pure and complete sample of strong lens candidates from Euclid with a limited need for visual inspection. One aim of this research is to have a quantified starting point on the achieved purity and completeness with our current version of CNN-based detection pipelines for the VIS images of EWS. This work is vital in preparing our CNN-based detection pipelines to be able to produce a pure sample of the &gt;100 000 strong gravitational lensing systems widely predicted for Euclid. We select all sources with VIS IE &lt; 23 mag from the Euclid Early Release Observation imaging of the Perseus field. We apply a range of CNN architectures to detect strong lenses in these cutouts. All our networks perform extremely well on simulated data sets and their respective validation sets. However, when applied to real Euclid imaging, the highest lens purity is just ∼11%. Among all our networks, the false positives are typically identifiable by human volunteers as, for example, spiral galaxies, multiple sources, and artifacts, implying that improvements are still possible, perhaps via a second, more interpretable lens selection filtering stage. There is currently no alternative to human classification of CNN-selected lens candidates. Given the expected ∼105 lensing systems in Euclid, this implies 106 objects for human classification, which while very large is not in principle intractable and not without precedent

    <em>Euclid</em>: The Early Release Observations Lens Search Experiment

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    \ua9 The Authors 2025. We investigated the ability of the Euclid telescope to detect galaxy-scale gravitational lenses. To do so, we performed a systematic visual inspection of the 0.7 deg2 Euclid Early Release Observations data towards the Perseus cluster using both the high-resolution IE band and the lower-resolution YE, JE, and HE bands. Each extended source brighter than magnitude 23 in IE was inspected by 41 expert human classifiers. This amounts to 12 086 stamps of 1000 7 1000. We found 3 grade A and 13 grade B candidates. We assessed the validity of these 16 candidates by modelling them and checking that they are consistent with a single source lensed by a plausible mass distribution. Five of the candidates pass this check, five others are rejected by the modelling, and six are inconclusive. Extrapolating from the five successfully modelled candidates, we infer that the full 14 000 deg2 of the Euclid Wide Survey should contain 100 000+-7030000000 galaxy-galaxy lenses that are both discoverable through visual inspection and have valid lens models. This is consistent with theoretical forecasts of 170 000 discoverable galaxy-galaxy lenses in Euclid. Our five modelled lenses have Einstein radii in the range 000 . 68 &lt; θE &lt; 100 . 24, but their Einstein radius distribution is on the higher side when compared to theoretical forecasts. This suggests that our methodology is likely missing small-Einstein-radius systems. Whilst it is implausible to visually inspect the full Euclid dataset, our results corroborate the promise that Euclid will ultimately deliver a sample of around 105 galaxy-scale lenses

    Quilotórax Chylothorax

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    O quilotórax, normalmente secundário a doenças malignas, trauma, doenças congênitas, infecções e trombose da veia cava superior, é uma causa pouco freqüente de derrame pleural. O diagnóstico e tratamento precoces são importantes no sentido de prevenir a mais temida conseqüência do quilotórax, a má nutrição e conseqüente comprometimento do estado imunológico.<br>Chylothorax, an uncommon cause of pleural effusion, is usually secondary to malignancy, trauma, congenital diseases, infections and superior vena cava thrombosis. The early diagnosis and treatment are important to prevent the most fearful consequence of chylothorax, the malnutrition with a compromised immunological status
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