Climatic anomalies are increasing in intensity and frequency due to rapid rates of global change, leading to increased extinction risk for many species. The impacts of anomalies are likely to vary between species due to different degrees of sensitivity and extents of local adaptation. Here, we used long-term butterfly monitoring data of 143 species across six European bioclimatic regions to show how species' population dynamics have responded to local or globally-calculated climatic anomalies, and how species attributes mediate these responses. Contrary to expectations, degree of apparent local adaptation, estimated from the relative population sensitivity to local versus global anomalies, showed no associations with species mobility or reproductive rate but did contain a strong phylogenetic signal. The existence of phylogenetically-patterned local adaptation to climate has important implications for forecasting species responses to current and future climatic conditions and for developing appropriate conservation practices.
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http://dx.doi.org/10.1038/s42003-022-03088-3 | DOI Listing |
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Department of Ophthalmology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou 450003, China.
COVID-19, caused by SARS-CoV-2, has presented formidable challenges to global health since its emergence in late 2019. While primarily known for respiratory symptoms, it can also affect the ocular surface. This review summarizes the effects of SARS-CoV-2 on ocular surface immunity and inflammation, focusing on infection mechanisms, immune responses, and clinical manifestations.
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Estonian Literary Museum, 51003 Tartu, Estonia.
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View Article and Find Full Text PDFSensors (Basel)
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Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Turin, Italy.
This study investigates the potential of deploying a neural network model on an advanced programmable logic controller (PLC), specifically the Finder Opta™, for real-time inference within the predictive maintenance framework. In the context of Industry 4.0, edge computing aims to process data directly on local devices rather than relying on a cloud infrastructure.
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Laboratory of Adaptive Lighting Systems and Visual Processing, Technical University of Darmstadt, Hochschulstr. 4a, 64289 Darmstadt, Germany.
Thermopile sensor arrays provide a sufficient counterbalance between person detection and localization while preserving privacy through low resolution. The latter is especially important in the context of smart building automation applications. Current research has shown that there are two machine learning-based algorithms that are particularly prominent for general object detection: You Only Look Once (YOLOv5) and Detection Transformer (DETR).
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January 2025
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
With the advent of the 5G era, high-precision localization based on mobile communication networks has become a research hotspot, playing an important role in indoor emergency rescue in shopping malls, smart factory management and tracking, as well as precision marketing. However, in complex environments, non-line-of-sight (NLOS) propagation reduces the measurement accuracy of 5G signals, causing large deviations in position solving. In order to obtain high-precision position information, it is necessary to recognize the propagation state of the signal before distance measurement or angle measurement.
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