Science has been exceedingly successful. But can we account for the success and objects of science without Platonism? Dr. Scott Berman, author of “Platonism and the Objects of Science” (2020), doesn’t think so. (Enjoy the bonus soccer, too!)
‘Talking’ to cells without influencing genes or molecules: it can be done by influencing bioelectric fields. By manipulating the bioelectric fields in orga…
Botanists discovered a new lipstick vine species, Aeschynanthus pentatrichomatus, in the Philippine rainforest. Found during a 2022 expedition, the plant is critically endangered and underscores the need for conservation in biodiversity hotspots.
Scientists have announced the discovery of a previously unknown species of lipstick vine, uncovered in the depths of the Philippine rainforest. The groundbreaking findings were published in the Nordic Journal of Botany.
A team of botanists from Oxford University and the University of the Philippines Los Baños made the discovery during a 2022 expedition to the remote Barangay Balbalasang rainforest on Luzon Island. Accessing this nearly impenetrable wilderness required several days of travel and the use of machetes to clear a path. During their exploration, the team was hosted by the Banao Tribe, an indigenous community who protect their local forest.
From a telescope network that spans much of the globe to a psychology study that spans 67 countries, here are the biggest science experiments on the planet.
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.
Previously, she served as Chief of Staff to Dr. Laura Matz, Chief Science and Technology Officer at Merck KGaA, Darmstadt, Germany. As part of the Science and Technology Office Leadership Team, she was responsible for fostering cross-sectoral collaboration, innovation, and digitalization across Merck’s three business sectors. She also spearheaded the company’s efforts in Bioconvergence, a multidisciplinary approach that synergizes biology, engineering, data, and digitalization. This initiative promises groundbreaking advancements in healthcare and the life sciences, heralding a new era of scientific collaboration for a healthier, more sustainable future.
Prior to that, Dr. Siragusa contributed to corporate innovation in several leadership roles:
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.
