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1,000-year-old dingo bones show that it was injured, cared for, and ritually buried

Popular Science

The dog survived traumatic injuries, thanks to his Barkindji caretakers. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Breakthroughs, discoveries, and DIY tips sent six days a week. The remains of an ancient dingo is shining new light on deep relationships between Australia's First Nations and the wild dogs . Barkindji ancestors deliberately cared for and buried the dingo along the Baaka (Darling River) about 800 miles west of Sydney.


Bronze Age feasts uncovered in ancient English trash heaps

Popular Science

We've always loved a food fest. Breakthroughs, discoveries, and DIY tips sent every weekday. While they may not have been pretty sights, the large prehistoric trash dumps known as middens are critical to understanding human history . Details about a people's diet, architecture, clothing, and society can all be gleaned by digging through these mounds. In what is now the largest study of its kind, Cardiff University archaeologists documented years of excavations at six sites across southern England.


Find Rhinos without Finding Rhinos: Active Learning with Multimodal Imagery of South African Rhino Habitats

arXiv.org Artificial Intelligence

Much of Earth's charismatic megafauna is endangered by human activities, particularly the rhino, which is at risk of extinction due to the poaching crisis in Africa. Monitoring rhinos' movement is crucial to their protection but has unfortunately proven difficult because rhinos are elusive. Therefore, instead of tracking rhinos, we propose the novel approach of mapping communal defecation sites, called middens, which give information about rhinos' spatial behavior valuable to anti-poaching, management, and reintroduction efforts. This paper provides the first-ever mapping of rhino midden locations by building classifiers to detect them using remotely sensed thermal, RGB, and LiDAR imagery in passive and active learning settings. As existing active learning methods perform poorly due to the extreme class imbalance in our dataset, we design MultimodAL, an active learning system employing a ranking technique and multimodality to achieve competitive performance with passive learning models with 94% fewer labels. Our methods could therefore save over 76 hours in labeling time when used on a similarly-sized dataset. Unexpectedly, our midden map reveals that rhino middens are not randomly distributed throughout the landscape; rather, they are clustered. Consequently, rangers should be targeted at areas with high midden densities to strengthen anti-poaching efforts, in line with UN Target 15.7.