Caves as interim-refugia: Chemical signatures of human habitation under extreme environments of Ladakh, NW India

2021 ◽  
Vol 36 ◽  
pp. 102799
Author(s):  
Amritpal Singh Chaddha ◽  
Runcie P. Mathews ◽  
Kamlesh Kumar ◽  
Sheikh Nawaz Ali ◽  
Binita Phartiyal ◽  
...  
2020 ◽  
pp. 1-20
Author(s):  
JENNY C. DUNN ◽  
ANTONY J. MORRIS ◽  
PHILIP V. GRICE ◽  
WILL J. PEACH

Summary Conservation measures providing food-rich habitats through agri-environment schemes (AES) have the potential to affect the demography and local abundance of species limited by food availability. The European Turtle Dove Streptopelia turtur is one of Europe’s fastest declining birds, with breeding season dietary changes coincident with a reduction in reproductive output suggesting food limitation during breeding. In this study we provided seed-rich habitats at six intervention sites over a 4-year period and tested for impacts of the intervention on breeding success, ranging behaviour and the local abundance of territorial turtle doves. Nesting success and chick biometrics were unrelated to the local availability of seed-rich habitat or to the proximity of intervention plots. Nestling weight was higher close to human habitation consistent with an influence of anthropogenic supplementary food provision. Small home ranges were associated with a high proportion of non-farmed habitats, while large home ranges were more likely to contain seed-rich habitat suggesting that breeding doves were willing to travel further to utilize such habitat where available. Extensively managed grassland and intervention plot fields were selected by foraging turtle doves. A slower temporal decline in the abundance of breeding males on intervention sites probably reflects enhanced habitat suitability during territory settlement. Refining techniques to deliver sources of sown, natural, and supplementary seed that are plentiful, accessible, and parasite-free is likely to be crucial for the conservation of turtle doves.


Author(s):  
Petar Radanliev ◽  
David De Roure ◽  
Kevin Page ◽  
Max Van Kleek ◽  
Omar Santos ◽  
...  

AbstractMultiple governmental agencies and private organisations have made commitments for the colonisation of Mars. Such colonisation requires complex systems and infrastructure that could be very costly to repair or replace in cases of cyber-attacks. This paper surveys deep learning algorithms, IoT cyber security and risk models, and established mathematical formulas to identify the best approach for developing a dynamic and self-adapting system for predictive cyber risk analytics supported with Artificial Intelligence and Machine Learning and real-time intelligence in edge computing. The paper presents a new mathematical approach for integrating concepts for cognition engine design, edge computing and Artificial Intelligence and Machine Learning to automate anomaly detection. This engine instigates a step change by applying Artificial Intelligence and Machine Learning embedded at the edge of IoT networks, to deliver safe and functional real-time intelligence for predictive cyber risk analytics. This will enhance capacities for risk analytics and assists in the creation of a comprehensive and systematic understanding of the opportunities and threats that arise when edge computing nodes are deployed, and when Artificial Intelligence and Machine Learning technologies are migrated to the periphery of the internet and into local IoT networks.


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