Bioconvergence — Bridging Science And Nature To Shape Tomorrow — Dr. Nina Siragusa Ph.D. — Merck KGaA, Darmstadt, Germany
#NinaSiragusa #MerckGroup #Darmstadt.
Dr. Nina Siragusa, Ph.D., MBA, is the Strategy, Business, and Data & Digital Lead within the global R&D organization of Merck Healthcare KGaA, Darmstadt, Germany. In this role, she leads strategic projects, manages business operations, and drives digital transformation.
Slow-wave sleep plays a crucial role in strengthening memory by enhancing synaptic connections in the brain, with new findings suggesting potential methods for boosting memory through targeted stimulation.
For nearly two decades, scientists have known that slow, synchronized electrical waves in the brain during deep sleep play a key role in forming memories. However, the underlying reason remained unclear — until now. In a new study published in Nature Communications, researchers from Charité – Universitätsmedizin Berlin propose an explanation. They found that these slow waves make the neocortex, the brain’s long-term memory center, especially receptive to new information. This discovery could pave the way for more effective memory-enhancing treatments in the future.
It’s getting harder to harder to ignore the potential disruptive power of AI in research. Scientists are already using AI tools but could the future lead to complete replacement of humans? How will our scientific institutions transform? These are difficult questions but ones we have to talk about in today’s episode.
Written, presented \& edited by Prof. David Kipping.
THANK-YOU to T. Widdowson, D. Smith, L. Sanborn, C. Bottaccini, D. Daughaday, S. Brownlee, E. West, T. Zajonc, A. De Vaal, M. Elliott, B. Daniluk, S. Vystoropskyi, S. Lee, Z. Danielson, C. Fitzgerald, C. Souter, M. Gillette, T. Jeffcoat, J. Rockett, D. Murphree, M. Sanford, T. Donkin, A. Schoen, K. Dabrowski, R. Ramezankhani, J. Armstrong, S. Marks, B. Smith, J. Kruger, S. Applegate, E. Zahnle, N. Gebben, J. Bergman, C. Macdonald, M. Hedlund, P. Kaup, W. Evans, N. Corwin, K. Howard, L. Deacon, G. Metts, R. Provost, G. Fullwood, N. De Haan, R. Williams, E. Garland, R. Lovely, A. Cornejo, D. Compos, F. Demopoulos, G. Bylinsky, J. Werner, S. Thayer, T. Edris, F. Blood, M. O’Brien, D. Lee, J. Sargent, M. Czirr, F. Krotzer, I. Williams, J. Sattler, B. Reese, O. Shabtay, X. Yao, S. Saverys, A. Nimmerjahn, C. Seay, D. Johnson, L. Cunningham, M. Morrow, M. Campbell, B. Devermont, Y. Muheim, A. Stark, C. Caminero, P. Borisoff, A. Donovan, H. Schiff, J. Cos, J. Oliver, B. Kite, C. Hansen, J. Shamp, R. Chaffee, A. Ortiz, B. McMillan, B. Cartmell, J. Bryant, J. Obioma, M. Zeiler, S. Murray, S. Patterson, C. Kennedy, G. Le Saint, W. Ruf, A. Kochkov, B. Langley, D. Ohman, P. Stevenson, T. Ford \& T. Tarrants.
Quantum walks are a powerful theoretical model using quantum effects such as superposition, interference and entanglement to achieve computing power beyond classical methods.
A research team at the National Innovation Institute of Defense Technology from the Academy of Military Sciences (China) recently published a review article that thoroughly summarizes the theories and characteristics, physical implementations, applications and challenges of quantum walks and quantum walk computing. The review was published Nov. 13 in Intelligent Computing in an article titled “Quantum Walk Computing: Theory, Implementation, and Application.”
As quantum mechanical equivalents of classical random walks, quantum walks use quantum phenomena to design advanced algorithms for applications such as database search, network analysis and navigation, and quantum simulations. Different types of quantum walks include discrete-time quantum walks, continuous-time quantum walks, discontinuous quantum walks, and nonunitary quantum walks. Each model presents unique features and computational advantages.
Artificial intelligence (AI) is becoming increasingly useful for the prediction of emergency events such as heart attacks, natural disasters, and pipeline failures. This requires state-of-the-art technologies that can rapidly process data. In this regard, reservoir computing, specially designed for time-series data processing with low power consumption, is a promising option.
It can be implemented in various frameworks, among which physical reservoir computing (PRC) is the most popular. PRC with optoelectronic artificial synapses that mimic human synaptic elements are expected to have unparalleled recognition and real-time processing capabilities akin to the human visual system.
However, PRC based on existing self-powered optoelectronic synaptic devices cannot handle time-series data across multiple timescales, present in signals for monitoring infrastructure, natural environment, and health conditions.
Through its commitment to international nuclear nonproliferation — a mission focused on limiting the spread of nuclear weapons and sensitive technology while working to promote peaceful use of nuclear science and technology — the United States maintains a constant vigilance aimed at reducing the threat of nuclear and radiological terrorism worldwide.
With extensive research into both basic and applied uranium science, as well as internationally deployed operational solutions, the Department of Energy’s Oak Ridge National Laboratory is uniquely positioned to contribute its comprehensive capabilities toward advancing the U.S. nonproliferation mission.
In 1943, seemingly overnight, ORNL emerged from a rural Tennessee valley as the site of the world’s first continuously operating nuclear reactor, in support of U.S. efforts to end World War II. ORNL’s mission soon shifted into peacetime applications, harnessing nuclear science for medical treatments, power generation and breakthroughs in materials, biological and computational sciences.
Dive into a universe of scientific research and innovation spanning diverse topics from astronomy to zoology. Stay ahead with our timely updates, learn from expert insights, and ignite your curiosity. Explore the wonders of science with us today.
Researchers have developed a technique called “atomic spray painting” using molecular beam epitaxy to strain-tune potassium niobate, enhancing its ferroelectric properties.
This method allows precise manipulation of material properties, with potential applications in green technologies, quantum computing, and space exploration.
A cutting-edge X-ray method reveals the 3D orientation of nanoscale material structures, offering fresh insights into their functionality.
Researchers at the Swiss Light Source (SLS) have developed a groundbreaking technique called X-ray linear dichroic orientation tomography (XL-DOT). This method reveals the three-dimensional arrangement of a material’s structural building blocks at the nanoscale. Its first application focused on a polycrystalline catalyst, enabling scientists to visualize crystal grains, grain boundaries, and defects—critical features that influence catalyst performance. Beyond catalysis, XL-DOT offers unprecedented insights into the structure of various functional materials used in information technology, energy storage, and biomedical applications.