Exploring and mapping the distribution of temperate savanna in the sandy lands of eastern China
Peer-Reviewed Publication
Updates every hour. Last Updated: 20-May-2025 00:10 ET (20-May-2025 04:10 GMT/UTC)
A paper published in SCIENCE CHINA Earth Sciences revealed that, the geographical distribution of the temperate savanna on the sandy lands of eastern China at the first time by integrating very high-resolution unmanned aerial vehicle and satellite imagery.
CLEVELAND—Researchers at Case Western Reserve University, University Hospitals and Houston Methodist will harness the power of artificial intelligence (AI) to more accurately predict risk of heart failure and other cardiovascular events, including estimating when an adverse event might occur, by developing an AI model that “learns” from patient scans.
How can we ensure that life-saving drugs or genetic therapies reach their intended target cells without causing harmful side effects? Researchers at Helmholtz Munich, Ludwig-Maximilians-Universität (LMU) and Technical University Munich (TUM) have taken an important step to answer this question. They have developed a method that, for the first time, enables the precise detection of nanocarriers – tiny transport vehicles – throughout the entire mouse body at a single-cell level. This innovation, called “Single-Cell Profiling of Nanocarriers” or short “SCP-Nano”, combines advanced imaging with artificial intelligence to provide unparalleled insights into the functionality of nanotechnology-based therapies. The results, published in Nature Biotechnology, pave the way for safer and more effective treatments, including mRNA vaccines and gene therapies.
In a paper published in National Science Review, Prof. Xu proposes a new term "viral aggregation" to more accurately describe the accumulation of lysis products in the soil environment. In addition, he advocates that incorporating soil viruses into existing MCP and MinCP models, namely virus-MCP and virus-MinCP, can substantially improve our understanding of global carbon cycle.
A new study from Oxford University has uncovered why the deep neural networks (DNNs) that power modern artificial intelligence are so effective at learning from data. The new findings demonstrate that DNNs have an inbuilt ‘Occam's razor,’ meaning that when presented with multiple solutions that fit training data, they tend to favour those that are simpler. What is special about this version of Occam’s razor is that the bias exactly cancels the exponential growth of the number of possible solutions with complexity. The study has been published today (14 Jan) in Nature Communications.
In a paper published in Polymer Science & Technology, an international team of scientists
explores an effective protocol for toughening vitrimers based on dioxaborolane metathesis through introducing a reversible secondary interaction and revealed the underlying molecular mechanism of this protocol. They copolymerized hexyl methacrylate with hydrogen-bonding n-isopropyl methacrylamide and vitrimeric cross-linkers to prepare dual-cross-linked networks. They found the breakup of the hydrogen bonds during the elongation significantly dissipated the energy, leading to the softening of the materials, thereby facilitating the stretch to high strain. Then the Dobrynin model modified by Konkolewicz and co-workers upon including a strain rate-dependent element was used to capture the softening process. The deviation at a high content of hydrogen bonds was attributed to the coupled motion of the hydrogen bonds where the distance between hydrogen bonds becomes smaller than the Kuhn length. Modification of the model according to this change is considered an interesting future work. This study is led by Shilong Wu and Quan Chen (State Key Laboratory of Polymer Physics and Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun 130022, China).