Onychophorans, also known as velvet worms, possess a pair of simple lateral eyes, and are a key lineage with regard to the evolution of vision. They resemble ancient Cambrian forms, and are closely related to arthropods, which boast an unrivalled diversity of eye designs. Nonetheless, the visual capabilities of onychophorans have not been well explored. Here, we assessed the spatial resolution of the onychophoran using behavioural experiments, three-dimensional reconstruction, anatomical and optical examinations, and modelling. Exploiting their spontaneous attraction towards dark objects, we found that can resolve stimuli that have the same average luminance as the background. Depending on the assumed contrast sensitivity of the animals, we estimate the spatial resolution to be in the range 15-40 deg. This results from an arrangement where the cornea and lens project the image largely behind the retina. The peculiar ellipsoid shape of the eye in combination with the asymmetric position and tilted orientation of the lens may improve spatial resolution in the forward direction. Nonetheless, the unordered network of interdigitating photoreceptors, which fills the whole eye chamber, precludes high-acuity vision. Our findings suggest that adult specimens of cannot spot or visually identify prey or conspecifics beyond a few centimetres from the eye, but the coarse spatial resolution that the animals exhibited in our experiments is likely to be sufficient to find shelter and suitable microhabitats from further away. To our knowledge, this is the first evidence of resolving vision in an onychophoran.
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http://dx.doi.org/10.1242/jeb.175802 | DOI Listing |
PLoS One
January 2025
Department of Computer Science, Khalifa University, Abu Dhabi, UAE.
A methodology is proposed, which addresses the caveat that line-of-sight emission spectroscopy presents in that it cannot provide spatially resolved temperature measurements in non-homogeneous temperature fields. The aim of this research is to explore the use of data-driven models in measuring temperature distributions in a spatially resolved manner using emission spectroscopy data. Two categories of data-driven methods are analyzed: (i) Feature engineering and classical machine learning algorithms, and (ii) end-to-end convolutional neural networks (CNN).
View Article and Find Full Text PDFPLoS One
January 2025
Kansai Research Center, Forestry and Forest Products Research Institute, Kyoto City, Kyoto Prefecture, Japan.
Soil imaging in the field and laboratory has greatly advanced our understanding of plant root systems. Soil fungi function as important plant symbionts and decomposers of complex organic material in soil environments. For fungal hyphae, however, the application of soil imaging remains scarce, limiting our understanding of hyphal systems in soil.
View Article and Find Full Text PDFPLoS One
January 2025
UK Centre for Ecology and Hydrology, Crowmarsh Gifford, Wallingford, United Kingdom.
Surface water plays a vital role in the spread of infectious diseases. Information on the spatial and temporal dynamics of surface water availability is thus critical to understanding, monitoring and forecasting disease outbreaks. Before the launch of Sentinel-1 Synthetic Aperture Radar (SAR) missions, surface water availability has been captured at various spatial scales through approaches based on optical remote sensing data.
View Article and Find Full Text PDFSci Adv
January 2025
School of GeoSciences, University of Edinburgh, James Hutton Road, Edinburgh EH9 3FE, UK.
Whether metazoan diversification during the Cambrian Radiation was driven by increased marine oxygenation remains highly debated. Repeated global oceanic oxygenation events have been inferred during this interval, but the degree of shallow marine oxygenation and its relationship to biodiversification and clade appearance remain uncertain. To resolve this, we interrogate an interval from ~527 to 519 Ma, encompassing multiple proposed global oceanic oxygenation events.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Faculty of Technical Chemistry, Institute of Chemical Technologies and Analytics, Technische Universität Wien, Vienna 1060, Austria.
Atomic force microscopy-infrared spectroscopy (AFM-IR) is a photothermal scanning probe technique that combines nanoscale spatial resolution with the chemical analysis capability of mid-infrared spectroscopy. Using this hybrid technique, chemical identification down to the single molecule level has been demonstrated. However, the mechanism at the heart of AFM-IR, the transduction of local photothermal heating to cantilever deflection, is still not fully understood.
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