Articles tagged with Complex Networks
A new nationwide Austrian study found that bone fractures are often part of a complex pattern of multiple conditions, underscoring the need for consistent osteoporosis screening at the time of a fracture. Osteoporosis is not systematically documented for many fracture types, highlighting a diagnostic gap, especially in men.
Researchers developed a compact aperture-adjustable antenna that maintains strong performance across the 57–71 GHz 5G band and improves signal strength by up to 62.2% at both lower and upper-band-edge frequencies. The system achieves data transmission speeds of up to 56 Gb/s, supporting future Beyond 5G and 6G applications.
A team from Emory University developed a simple method to test the accuracy of protein language models, which are used to analyze complex biological data. By comparing how these models 'embed' natural proteins versus synthetic ones, researchers can estimate their reliability and improve their performance.
A team of researchers at Binghamton University has developed a method to pinpoint discoveries that reshaped the course of science. The new metric uses neural embedding to analyze approximately 55 million scientific papers and patents, identifying major breakthroughs and simultaneous discoveries with greater accuracy.
Researchers have shown that topology can guide multiple, information-carrying light signals through chip-based photonic communication systems, making them more powerful and reliable. This breakthrough could enable the creation of networks of chips that communicate using light while taking advantage of topology's robustness.
Researchers identified small clusters of interacting components that act as amplifiers, triggering outsized reactions in complex systems. These clusters can control how strongly a system reacts after a disruption, and their presence can determine the stability of entire systems.
Researchers developed a new theoretical framework that links individual animal movements to population dynamics across space and time. The range-resident logistic model incorporates interactions between multiple animals, providing a more accurate prediction of population sizes and helping inform real-world conservation recommendations.
Groups of tiny particles suspended in liquid oscillate together, keeping time as though they sense each other's motion. The surrounding fluid enables the particles to 'feel' one another at a distance, influencing their motions without direct contact.
A new study found remarkable variation in how populations evolve in variable environments, with some cases benefiting from changes and others being hindered. The research has implications for understanding evolution and adapting to climate change, as well as informing AI and machine learning.
A team of researchers developed an innovative algorithm called 'Ponte' that integrates advanced functionalities to provide reliable wireless communications in industrial environments. The algorithm guarantees strict limits on delay and reliability, even over Wi-Fi, making it suitable for controlling robotic arms and autonomous vehicles.
A new study by Complexity Science Hub researcher Rafael Prieto-Curiel challenges the assumption that larger cities are more violent. The study shows that isolated cities, with limited highway connections, experience nearly seven times more violence against civilians per 100,000 residents than well-connected cities.
A new study from the Complexity Science Hub finds that belonging to more than one marginalized group can significantly harder forming social connections. The researchers developed a mathematical model and tested it using friendship data from around 40,000 U.S. high school students, revealing how overlapping disadvantages can interact.
Researchers at the University of Cincinnati developed a flapping wing drone that can hover like a moth around a light source using an extremum-seeking feedback system. The drone makes fine adjustments to maintain stability and distance, without relying on AI or complex calculations.
A new analytical method reveals overlooked species at risk of extinction, providing a valuable layer of insight for conservationists. The dual-role approach captures both predator and prey interactions, identifying keystone species and vulnerabilities.
Terrence Sejnowski has been elected to the Royal Society and the American Philosophical Society, a testament to his groundbreaking contributions to computational neuroscience. His pioneering work includes inventing the Boltzmann machine and NETtalk program, which revolutionized artificial neural networks and speech recognition.
Hari Kalva, a pioneer in video technology, has been inducted into the Florida Inventors Hall of Fame. His work has enabled the pixels of modern life, from Netflix streams to smartphones. He is also credited with developing the MP4 file format and pioneering machine learning for video encoding.
A new study from researchers at the Helmholtz Institute for Functional Marine Biodiversity offers fresh insights into why many microorganisms fail to grow in the lab. The study suggests that the survival of microbes depends on a hidden web of relationships between species, which can collapse with small structural changes.
The study proposes a new framework for understanding complex higher-order networks, which could lead to breakthroughs in physics, neuroscience, computer science, and more. The framework integrates discrete topology and non-linear dynamics, offering insights into how topology shapes dynamics and evolves dynamically.
Researchers at the University of Gothenburg have made a breakthrough in developing a new low-cost computer using spintronics, which enables information transmission at room temperature. The study demonstrates the ability to control and synchronize spin waves in complex networks, paving the way for the next generation of Ising machines.
Researchers introduce 'fitness centrality,' a faster method to identify crucial elements in any network, with practical applications in supply chains, ecological conservation, and cybersecurity. The approach streamlines analysis, making it practical for vast networks.
Researchers analyzed firm-level data from the global supply network, revealing that wealthy nations are only exposed to supply chain disruptions from other high-income countries. Poor and developing nations are disproportionately affected by economic shocks due to their structural embeddedness in their local or national supply chains.
A recent study by University of Hawaii at Manoa researchers highlights the hidden threat of global underground infrastructure vulnerability to sea-level rise. Shallow and saltier groundwater exacerbates corrosion and failure of critical systems such as sewer lines, roadways, and building foundations in cities worldwide.
The University of Manchester has received a £4.2 million funding award to tackle the UK's most challenging resilience and security problems. The project, SALIENT, will drive interdisciplinary research on robust supply chains, global order, and technological security.
Sydney researchers have identified new structural relationships in complex networks like Twitter and political blogs. A 'source-basin' structure plays a crucial role in organizing the flow of information, with influential nodes serving as sources and densely connected active nodes forming basins.
The study analyzed over 1.2 million criminal incidents, revealing that specialists tend to operate within a confined geographic area and collaborate with local networks. The method can help law enforcement agencies anticipate criminal developments and tailor measures for prevention, policing, and rehabilitation.
Researchers found a total of 4,721 proteins altered with age in the murine ovary, including upregulated ECM proteins associated with fibrosis. Age-dependent changes also affect immune response pathways and unique immune cell populations.
Researchers have successfully solved a problem in graph theory that has attracted attention from within the field. The team's research involves packing coloring, which deals with labelling parts of a graph to comply with certain rules and avoid specific conflicts.
The study creates a network that maps domestic trades between holdings in Austria, revealing the most significant risks of disease spread. The analysis highlights the importance of monitoring and prevention strategies in regions with high animal density and frequent transfers.
A team of researchers from Kyoto University and international institutions has developed a mathematical solution to the temporal asymmetry of nonequilibrium disordered Ising networks. This breakthrough offers insights into the behavior of biological systems, machine learning, and AI tools.
NetSci 2023 brings together top researchers in physics, computer science, biology, and social sciences to exchange ideas on network structures. Keynote speakers discuss the application of superconducting elements and the dynamic processes governing large networks.
Researchers from Complexity Science Hub highlight similarities in models used by economists and physicists to analyze financial markets. The study aims to create an overview of these models, promoting interdisciplinary collaboration and avoiding research that gets lost in translation.
Bar-Ilan University researchers found that large and heterogeneous complex networks exhibit enhanced stability due to non-random patterns of interaction, contradicting Sir Robert May's original prediction. This discovery offers new guidelines for designing stable infrastructure networks and protecting fragile ecosystems.
Scientists have discovered a connection between Amazon rainforest temperature changes and Tibetan Plateau climate patterns, highlighting the global impact of Earth system tipping elements. The study found a pronounced propagation pathway from South America to Tibet via Southern Africa and the Middle East.
A recent study by Tokyo University of Science researchers provides theoretical foundations for effective parameter tuning in the Bernoulli shift map. They used modular arithmetic to determine optimal parameter values for preserving chaos, with implications for other chaotic maps like the tent and logistic maps.
The study infers the dimensionality of complex networks using hyperbolic geometry, which captures relational structures in real-world domains. It reveals extremely low dimensions for molecular networks and higher dimensions for social networks and the Internet, with implications for network characterization and predictive capability.
Researchers developed a method to identify valve dysfunction using complex network analysis that is accurate, simple to use, and low-cost. The diagnostic tool works by analyzing the sounds produced by the heart, creating a graph of connected points, and identifying correlations between nodes.
A research team used game theory to analyze cooperation in networks and found that networks with a high level of cooperation can emerge if individuals take a clear-cut position against free riders. The study also showed that if contributors leave an environment too quickly, it leads to a lower level of cooperation.
A team at the Complexity Science Hub Vienna mapped an entire nation's supply chain network using mobile phone data, predicting systemic risk and resilience. The model can be easily implemented by other countries and provides a detailed view of national economic behavior on a daily timescale.
A research team from the Complexity Science Hub Vienna has developed a stress test to identify weaknesses and strengths in healthcare systems. They used data from Austria to show how many resident physicians can drop out before patients don't find a new doctor within reasonable distance, highlighting regional differences in resilience.
Researchers developed a novel computational method to control large complex networks using local information, addressing the challenge of controlling complex systems. The method considers computational time and information communication costs to produce optimal choices.
Researchers at the University of Illinois Urbana-Champaign have developed a low-cost ultrasound imaging method to study the relationship between Alzheimer's disease and the brain's vascular system. The technique, which provides high-resolution images of animal microvasculature, may aid in early detection of the disease.
Researchers at CSH create the first complete representation of Hungary's economy, mapping production networks and supply relationships. They find that only a few firms pose a substantial risk to the overall economy, with nearly 75% of systemic risk concentrated on just 100 high-risk companies.
Researchers used complex networks to study synchronized structures of extreme rainfall events, revealing regions with similar climatological behaviors. The analysis showed that extreme rainfalls are not independent but have a degree of similarity globally.
A mathematical model reveals that spontaneous symmetry breaking in chemical reactions leads to homochirality, optimizing energy harvesting from the environment. This phenomenon could explain how life developed on primordial Earth and has implications for the synthesis of chiral drug molecules.
A study by Tokyo University of Science researchers has demonstrated that a computationally-light model can simulate complex brain cell responses, including periodic and quasi-periodic responses. The Izhikevich neuron model was found to be capable of reproducing both types of responses at lower computational cost.
A study by Tokyo University of Science researchers used WCNs with increasing n values to find features of language that cannot be analyzed using existing WCNs. They found important features in networks with more than three co-occurrences, independent of text data.
Bar-Ilan University researchers develop a two-step recovery process to revive failed networks by restructuring damaged links and reigniting the entire system through controlled node activation. This approach has shown promise in steering a failed microbiome back to functionality, particularly with probiotic interventions.
Researchers developed a new method for generating network layouts that allow for visualizing different information in two- and three-dimensional virtual space. This facilitates the exploration of complex protein interactions and provides more versatile, comprehensible representations of networks.
Researchers at UC3M have developed a mathematical model that analyzes the appearance of oscillations in flow networks, which may help explain how blood circulates in the brain. The model takes into account the size of the network and predicts the frequency of pressure oscillations.
A study by researchers at the University of São Paulo developed a model that can predict the likelihood of politicians being convicted of corruption based on their voting histories. The model achieved 90% accuracy in identifying corrupt deputies.
The special issue examines the collective dynamics of complex networks with applications in neuroscience, climate modelling, and Earth science. The papers cover a broad range of topics including dynamics of excitable systems, cluster dynamics, and interplay of noise and feedback.
Researchers from Paderborn University create a simple integrated quantum network using thin layers of lithium niobate to demonstrate large-scale functionalities. The project aims to develop scalable quantum components with industrial application potential.
Researchers have developed a new model for micro-swimmer-based transport, which shows that a swarm of micro-swimmers can transport particles more efficiently than traditional methods. The study's findings suggest that this phenomenon could be useful in biological applications, such as delivering drugs to specific locations in the body.
A new study analyzed Italian firms' Twitter conversations during the pandemic, revealing a focus on environmental sustainability and digital transformation. The research highlights the importance of corporate social responsibility and stakeholder engagement on these themes.
Researchers apply mathematics to real-world data, finding popular people tend to be friends with each other, while less popular people connect with others of similar status. The study reveals around 95% of variation in social networks can be explained by these two factors.
Researchers from Göttingen and Auckland universities simulated microscopic clusters from the Big Bang, discovering complex networks of structures that mimic today's galaxy distribution. These primordial clumps would have masses of only a few grams and be incredibly small.
Researchers demonstrated mathematically that low-dimensional embeddings fail to capture important properties of social networks and other complex networks. This flaw leads to significant structural aspects being lost in the embedding process, resulting in inaccurate predictions and recommendations.
A study published in PLOS ONE reveals that prehistoric Italian communities traded copper across complex networks, with most coming from Tuscany. Non-Tuscan copper was also a significant import to the region, contributing to a growing picture of independent metal exchange networks.
A new computational tool developed by USC researchers solves the 'community detection' problem, identifying patterns and relationships among entities with greater accuracy than existing tools. The Ollivier-Ricci curvature-based method can be leveraged by various groups, including biologists, doctors, and political strategists.
Researchers analyzed 10,000 perfumes and found that less-common notes and accords are more likely to be successful in online reviews. Generic notes like floral notes and well-represented ingredients like musk or vanilla also play a significant role in perfume success.