Showing 20 articles starting at article 1
Categories: Ecology: Extinction, Mathematics: Modeling
Published Self-improving AI method increases 3D-printing efficiency
(via sciencedaily.com) Original source An artificial intelligence algorithm can allow researchers to more efficiently use 3D printing to manufacture intricate structures. The development could allow for more seamless use of 3D printing for complex designs in everything from artificial organs to flexible electronics and wearable biosensors. As part of the study, the algorithm learned to identify, and then print, the best versions of kidney and prostate organ models, printing out 60 continually improving versions.
Published Mobile species are 'glue' which connect different habitats together
(via sciencedaily.com) Original source A groundbreaking study conducted across 30 field sites in the southwest UK has revealed the importance of incorporating varied habitats into the landscape at large.
Published Environmental laws failing to slow deforestation
(via sciencedaily.com) Original source Australia's environmental laws are failing to stop high rates of tree clearing to make way for agriculture, development and mining.
Published 'Masters of shape-shifting': How darkling beetles conquered the world
(via sciencedaily.com) Original source Large-scale genomic analysis of darkling beetles, a hyper-diverse insect group of more than 30,000 species worldwide, rolls back the curtain on a 150-million-year evolutionary tale of one of Earth's most ecologically important yet inconspicuous creatures, according to new research.
Published Peering into the mind of artificial intelligence to make better antibiotics
(via sciencedaily.com) Original source Artificial intelligence (AI) has exploded in popularity as of late. But just like a human, it's hard to read an AI model's mind. Explainable AI (XAI) could help us do just that by providing justification for a model's decisions. And now, researchers are using XAI to scrutinize predictive AI models more closely, which could help make better antibiotics.
Published Will climate change lead to the extinction of a newly discovered tarantula species?
(via sciencedaily.com) Original source Biologists have discovered a new species of tarantula from the Madrean Sky Island biodiversity hotspot in southeastern Arizona. This remarkable new species is endemic to the Chiricahua Mountains and is predominately distributed in mid- to high-elevation forests, which are increasingly threatened due to climate change.
Published AI model aids early detection of autism
(via sciencedaily.com) Original source A new machine learning model can predict autism in young children from relatively limited information. The model can facilitate early detection of autism, which is important to provide the right support.
Published Rethinking the dodo
(via sciencedaily.com) Original source Researchers are setting out to challenge our misconceptions about the Dodo, one of the most well-known but poorly understood species of bird. Researchers have undertaken the most comprehensive review of the taxonomy of the Dodo and its closest relative, the Rodriguez Island Solitaire.
Published The banana apocalypse is near, but biologists might have found a key to their survival
(via sciencedaily.com) Original source The bananas in your supermarket and that you eat for breakfast are facing functional extinction due to the disease Fusarium wilt of banana (FWB) caused by a fungal pathogen called Fusarium oxysporum f.sp. cubense (Foc) tropical race 4 (TR4). However, thanks to recent research from an international team of scientists we now know that Foc TR4 did not evolve from the strain that wiped out commercial banana crops in the 1950s and that the virulence of this new strain seems to be caused by some accessory genes that are associated the production of nitric oxide. The research opens the door to treatments and strategies that can slow, if not control, the as-of-yet unchecked spread of Foc TR4.
Published Why do researchers often prefer safe over risky projects? Explaining risk aversion in science
(via sciencedaily.com) Original source A mathematical framework that builds on the economic theory of hidden-action models provides insight into how the unobservable nature of effort and risk shapes investigators' research strategies and the incentive structures within which they work, according to a new study.
Published As human activities expand in Antarctica, scientists identify crucial conservation sites
(via sciencedaily.com) Original source Establishing Key Biodiversity Areas in the Southern Ocean will be vital for safeguarding the ecosystem from the impact of human activities, researchers say.
Published In subdivided communities cooperative norms evolve more easily
(via sciencedaily.com) Original source Researchers simulated social norms with a supercomputer. Their findings contribute to a deeper understanding of the evolution of social norms and their role in fostering cooperative behavior.
Published Leading AI models struggle to identify genetic conditions from patient-written descriptions
(via sciencedaily.com) Original source Researchers discover that while artificial intelligence (AI) tools can make accurate diagnoses from textbook-like descriptions of genetic diseases, the tools are significantly less accurate when analyzing summaries written by patients about their own health. These findings demonstrate the need to improve these AI tools before they can be applied in health care settings to help make diagnoses and answer patient questions.
Published Giant fossil seeds from Borneo record ancient plant migration
(via sciencedaily.com) Original source Ancient fossil beans about the size of modern limes, and among the largest seeds in the fossil record, may provide new insight into the evolution of today's diverse Southeast Asian and Australian rainforests, according to researchers who identified the plants.
Published Think fast -- or not: Mathematics behind decision making
(via sciencedaily.com) Original source New research explains the mathematics behind how initial predispositions and additional information affect decision making.
Published AI poses no existential threat to humanity, new study finds
(via sciencedaily.com) Original source Large Language Models (LLMs) are entirely controllable through human prompts and lack 'emergent abilities'; that is, the means to form their own insights or conclusions. Increasing model size does not lead LLMs to gain emergent reasoning abilities, meaning they will not develop hazardous abilities and therefore do not pose an existential threat. A new study sheds light on the (until now unexplained) capabilities and shortcomings of LLMs, including the need for carefully engineered prompts to exhibit good performance.
Published Millions of years for plants to recover from global warming
(via sciencedaily.com) Original source Catastrophic volcanic eruptions that warmed the planet millions of years ago shed new light on how plants evolve and regulate climate. Researchers reveal the long-term effects of disturbed natural ecosystems on climate in geological history and its implications for today.
Published Researchers develop AI model that predicts the accuracy of protein--DNA binding
(via sciencedaily.com) Original source A new artificial intelligence model can predict how different proteins may bind to DNA.
Published Nature at risk in the hunt for the perfect selfie
(via sciencedaily.com) Original source The need for a dramatic selfie or the perfect landscape photo is proving detrimental to nature, a new research collaboration has found.
Published Researchers outline promises, challenges of understanding AI for biological discovery
(via sciencedaily.com) Original source Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use machine learning in computational biology, understanding model behavior remains crucial for uncovering the underlying biological mechanisms in health and disease. Researchers now propose guidelines that outline pitfalls and opportunities for using interpretable machine learning methods to tackle computational biology problems.