We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply. Achieving net zero global emissions of carbon dioxide (CO2), with declining emissions of other greenhouse gases, is widely expected to halt global warming. CO2 emissions will continue to drive warming until fully balanced by active anthropogenic CO2 removals. For practical reasons, however, many greenhouse gas accounting systems allow some a''passivea'' CO2 uptake, such as enhanced vegetation growth due to CO2 fertilisation, to be included as removals in the definition of net anthropogenic emissions. By including passive CO2 uptake, nominal net zero emissions would not halt global warming, undermining the Paris Agreement. Here we discuss measures addressing this problem, to ensure residual fossil fuel use does not cause further global warming: land management categories should be disaggregated in emissions reporting and targets to better separate the role of passive CO2 uptake; where possible, claimed removals should be additional to passive uptake; and targets should acknowledge the need for Geological Net Zero, meaning one tonne of CO2 permanently restored to the solid Earth for every tonne still generated from fossil sources. We also argue that scientific understanding of net zero provides a basis for allocating responsibility for the protection of passive carbon sinks during and after the transition to Geological Net Zero....
A month after his election in 2016, Donald Trump chose Andrew Puzder, a longtime fast-food-company CEO, to be his secretary of labor. Most of Trump's Cabinet picks moved smoothly through the confirmation process, but Puzder's nomination languished amid allegations of wage theft, sexual harassment, and spousal abuse, as well as his acknowledgment that he had hired an undocumented immigrant as a nanny and not paid her taxes. By February 2017, he gave up and withdrew his nomination. Being a president's most troubled or scandal-ridden nominee is dangerous'like being the weakest or sickest member of the herd when predators start to circle. Republican senators probably calculated that if they rejected Puzder, Trump would send a pick with less baggage and higher qualifications, which is exactly what he did: Alex Acosta, the eventual selection, had a long government resume and easily won confirmation. Something very different is happening with Trump's Cabinet picks this time. Less than two weeks have passed since the election, but the president-elect has already put forward a batch of nominees so aberrant by historical standards that any one of them would have been a gigantic story in the past. (Hello, Attorney General'designate Matt Gaetz.) Each one barely holds the media's attention for an hour or two before the next nomination eclipses them. (Whoops, I didn't see you there, Robert F. Kennedy Jr., nominee to lead the Department of Health and Human Services.)...
Over the past two decades, new technologies have helped scientists generate a vast amount of biological data. Large-scale experiments in genomics, transcriptomics, proteomics, and cytometry can produce enormous quantities of data from a given cellular or multicellular system. However, making sense of this information is not always easy. This is especially true when trying to analyze complex systems such as the cascade of interactions that occur when the immune system encounters a foreign pathogen. MIT biological engineers have now developed a new computational method for extracting useful information from these datasets. Using their new technique, they showed that they could unravel a series of interactions that determine how the immune system responds to tuberculosis vaccination and subsequent infection. This strategy could be useful to vaccine developers and to researchers who study any kind of complex biological system, says Douglas Lauffenburger, the Ford Professor of Engineering in the departments of Biological Engineering, Biology, and Chemical Engineering....
Dario Amodei, the CEO of Anthropic, recently published an essay called 'Machines of Loving Grace.' It sketches out his vision for how AI could radically transform neuroscience, economics, diplomacy, and the meaning of work. Amodei also imagines the ways AI could accelerate biological research and yield miraculous cures in the 21st century; everything from the prevention and treatment of nearly all infectious and inherited diseases to the elimination of most cancers. 'Biology is probably the area where scientific progress has the greatest potential to directly and unambiguously improve the quality of human life,' Amodei writes. 'My basic prediction is that AI-enabled biology and medicine will allow us to compress the progress that human biologists would have achieved over the next 50-100 years into 5-10 years.' This is an inspiring vision, but as Amodei acknowledges, achieving it will first require that we think deeply about existing bottlenecks and then roadmap ways to solve them. Indeed, most of what we publish at Asimov Press are roadmaps of this kind, including essays that examine persistent obstacles to scientific progress (such as 'Where's the Synthetic Blood'') or speculative fiction that imagines possible futures once these obstacles have been overcome (see 'Tinker' or 'Models of Life')....
