Financial institutions are linked together in a global web of interactions whose structure can be analyzed quantitatively by means of network theory. Today, 15 years after the 2007-2008 financial crisis, the role of networks for monitoring financial stability is widely recognized. Both policymakers and researchers agree that systemic risk has to be studied and managed by adopting a network perspective.
In a first-of-its-kind study, researchers used smart watches and a dedicated app to monitor 169 subjects before and during Israel's second COVID-19 lockdown (October 2020).
Mandating vaccination could have a substantial negative impact on voluntary compliance, according to research published today in PNAS.
After winning the FIFA World Cup, France could also win the European Football Championship - this is the conclusion of researchers from the Universities of Innsbruck (Austria) and Ghent (Belgium), the Technical Universities of Dortmund and Munich (Germany) and Molde University College (Norway). England and Spain also have a good chance of winning the title, according to the forecast.
In network science, the famous "friendship paradox" describes why your friends are (on average) more popular, richer, and more attractive than you are. But a slightly more nuanced picture emerges when we apply mathematics to real-world data.
A new study by ecologist André de Roos shows that differences between juveniles and adults of the same species are crucial for the stability of complex ecological communities. The research, published in Proceedings of the National Academy of Sciences, represents a major advance in ecological modeling at a time when biodiversity is declining and species around the world are rapidly going extinct.
In a new study published in Proceedings of the National Academy of Sciences (PNAS), a research team of the Institute of Complex Systems of the UB (UBICS) analysed the time evolution of real complex networks and developed a model in which the emergence of new nodes can be related to pre-existing nodes, similarly to the evolution of species in biology.
Machine learning, when used in climate science builds an actual understanding of the climate system. This means we can trust machine learning and further its applications in climate science, say the authors.
Researchers from Tokyo Metropolitan University have enhanced "super-resolution" machine learning techniques to study phase transitions. They identified key features of how large arrays of interacting "particles" behave at different temperatures by simulating tiny arrays before using a convolutional neural network to generate a good estimate of what a larger array would look like using "correlation" configurations. The massive saving in computational cost may realize unique ways of understanding how materials behave.
New estimates suggest that mass gatherings during an election in the Malaysian state of Sabah directly caused 70 percent of COVID-19 cases detected in Sabah after the election, and indirectly caused 64.4 percent of cases elsewhere in Malaysia. Jue Tao Lim of the National University of Singapore, Kenwin Maung of the University of Rochester, New York, and colleagues present these findings in the open-access journal PLOS Computational Biology.