Articles tagged with Complex Systems
Researchers found that over half of projects in the popular OpenStack ecosystem are affected by shared instability from “flaky tests”, resulting in a cumulative loss of 1,156 days of developer time. The study identifies environmental and system-level factors as major causes of test instability.
Researchers challenge long-held assumptions about vegetation patterns in dryland ecosystems, finding that such patterns can actually indicate reduced ecosystem resilience. The new theoretical framework takes into account spatial constraints and environmental heterogeneities, revealing that ecosystem stability depends on specific enviro...
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.
Florida Atlantic University has received a $4.5 million grant from the US Air Force to establish a high-fidelity platform for autonomous decision-making and real-time sensor fusion research. The T-1A Jayhawk simulator will be used to study cognitive performance, situational awareness, stress and decision-making under pressure.
The Economy as an Evolving Complex System IV presents a new approach to understanding the economy, highlighting agent-based models and network tools that capture diversity and feedback loops. These tools are being used by policymakers and central banks to forecast GDP during crises and manage housing bubbles.
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.
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.
This study investigates how environmental variability and human migration influence the evolution of cooperation among humans. Simulation results reveal that cooperation is more likely to evolve when these factors are sufficiently high, hindering non-cooperative groups and encouraging cooperative groups.
Scientists at Seoul National University have developed a framework to manipulate emergent behavior in animal groups and robot swarms. The approach uses physics-informed AI to learn local interaction rules, enabling the control of collective patterns such as rings, clumps, and flocks.
Researchers at FAU have developed a smarter AI framework that can manage complex systems with unequal levels of authority and adapt to imperfect information. The framework, based on reinforcement learning and game theory, reduces unnecessary computation while maintaining system stability and optimal strategy outcomes.
The European consortium, funded by €4.5M, will recruit and train 15 PhD researchers to develop new models and methods for understanding complex biological systems. The network, coordinated by the University of Edinburgh, aims to create a framework grounded in physics that can be applied systematically.
Researchers Marie Teich and Wilmer Leal develop a formal framework to analyze metaphors, confirming they are enduring linguistic and cognitive structures. The study reveals two significant metaphorical processes: mappings from concrete to abstract topics and the emergence of new mappings between domains.
A new theory explains how ideas gain momentum and spread like wildfire. The researchers introduce a mathematical model that takes into account the evolution of ideas as they spread, leading to complex results with unexpected outcomes. This work has implications for understanding belief formation, misinformation, and social contagion.
A new study from the Complexity Science Hub reveals that innovation can only endure over time if it is balanced with exnovation - the loss or forgetting of older possibilities. The researchers found an interesting trade-off between innovation speed and system stability.
A new study uncovers coordinated efforts of paper mills, brokers, and infiltrated journals to fabricate research, pay for authorships, and citations. Millions of dollars are involved in these processes, with the problem so widespread that it's outpacing legitimate scientific publications.
A team of researchers developed a new quantum framework for analysing higher-order network data using topological signal processing. The Quantum Topological Signal Processing (QTSP) framework achieves linear scaling in signal dimension, opening the door to efficient quantum algorithms for problems previously considered out of reach.
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.
A new study found a universal organizing pattern governing species distribution across biogeographical regions. The research reveals that core areas provide optimal conditions for species survival and diversification, driving biodiversity radiance outward.
A new study in PNAS examines the rise and fall of Piast Poland, identifying key factors that contributed to its collapse. The research highlights the importance of balancing capital accumulation with social connectivity for sustainable political systems.
Researchers developed models to study EV's influence on human cooperation, revealing regional variability promotes cooperation in resource-poor areas. The findings provide new perspectives for archeological inquiry and insights into modern society's cooperative behavior.
Researchers developed a new liquid-crystal-based platform to handle hundreds of optical modes in compact two-dimensional setups, overcoming optical losses. This breakthrough enables the scalability of quantum simulations and all-optical AI systems.
Researchers developed a new method to include uncertainty in predictive algorithms, ensuring accurate and reliable solutions. The approach uses Markov models to explicitly include uncertainty in specific parameters, allowing for faster predictions and more complete analysis.
Researchers uncover the origin of mixed-order transitions, where a macroscopic change is triggered by microscopic cascades. The study reveals long-term fluctuations can lead to sudden transformations in systems like water freezing or societal conflicts.
Researchers propose a new strategy to stabilize quantum networks by rebuilding connections after each use, which leads to an eventual stable network state. The key is finding the optimal number of links to add, determined to be the square root of the number of users.
A team from Osaka Metropolitan University has developed a crystal patterning method that controls the position and orientation of photochromic crystals, known as diarylethenes. This breakthrough allows for the creation of convex structures with precise control over crystal shape and size.
A newly discovered Tetrarchic boundary stone provides valuable historical insights into the sweeping tax reforms of Roman Emperor Diocletian. The inscription mentions two previously unknown village names, a new imperial surveyor, and reflects the socio-economic dynamics during the Tetrarchy period.
In a Weizmann Institute experiment, groups of ants demonstrated superior problem-solving skills compared to human groups and individuals. Humans struggled to improve performance when working together, relying on individual calculation rather than collective strategy.
A new study warns that human civilization is poised for a significant transformation as industrial civilization declines, giving rise to a postmaterialist, clean energy-based system. Rising authoritarianism poses a threat to this transition.
Professor LI Jinghai proposes Mesoscience, a concept exploring common principles among complex systems at mesoscales. This approach aims to identify and develop solutions for global challenges such as climate change, human health, and sustainable development goals.
The study emphasizes the need for a coherent approach to understanding A.I. threats, recognizing the intricate interplay between technology and society. Experts propose involving laypeople and experts in risk assessment processes, as well as promoting social resilience to ensure better decision-making.
A new study by University of Michigan researchers introduces a framework to compare and analyze competitive interactions across various fields, from sports to social hierarchies. The 'depth of competition' model reveals that human games and sports are surprisingly shallow, while animal competitions exhibit much deeper stratification.
A team of MIT engineers developed an algorithm to identify causal links in complex systems, taking data from various sources and analyzing interactions between variables. The method generates a causality map linking variables with likely cause-and-effect relationships, including synergistic and redundant links.
A new benchmark, V-score, has been developed to tackle quantum many-body problems. The V-score combines energy and fluctuation data into a single number, making it easier to rank different methods based on accuracy.
Researchers at Tohoku University have successfully applied quantum squeezing to enhance the accuracy of measurements in complex quantum systems. By reducing uncertainty in one aspect while increasing it in another, they can measure variables like position and momentum with greater precision.
A recent study found that hospitals with standardized data governance platforms were 47% less likely to be breached. The research proposes building enterprise-wide data analytics platforms to manage data sharing among diverse systems, simplifying the system and reducing breaches. Practitioners should embrace IT complexity as long as it...
A new metric assesses cities globally, uncovering significant inequalities in access to services. The research team developed a relocation algorithm to understand how to increase accessibility and reduce inequality in urban areas.
Researchers analyzed 650 million tweets to identify new words and tracked their adoption. Words used by central users persisted longer, while those with less central positions had a rapid rise and decline. The study reveals the predictive power of social network position in shaping language.
A new study reveals that women leaders with greater experience and connections play a crucial role in driving the success of community coalitions aimed at preventing childhood obesity. The research highlights the importance of these female leaders in facilitating the diffusion of prevention efforts.
Researchers introduce ghost channels and cycles to understand transient behaviors in complex systems like climate processes or neuronal networks. This new approach challenges traditional concepts based on stable or unstable equilibria, potentially helping predict tipping cascades and ecosystem degradation.
Researchers from MPI-DS investigated how non-reciprocal interactions can help overcome static equilibrium states in complex systems. They found that these interactions can counteract energy barriers, allowing trapped systems to escape and potentially leading to more efficient molecular systems.
The Complexity Science Hub is launching a new PhD program in Austria, focusing on complexity research to address current challenges. The interdisciplinary program will provide students with expertise in data, network, and complexity science.
Researchers from Queen Mary University of London developed a novel analysis to explore the impact of parasite virulence and infection probability on species coexistence in a complex system. The study found that stochasticity plays a significant role in determining whether species coexist or go extinct.
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.
Researchers found termites use humidity to guide their nest-building activity, not relying on pheromones. The study used artificial structures with varying heights and shapes, tracking termite behavior and correlating it with changes in the 3D structure.
Politecnico researchers developed a new type of neural network called Latent Dynamics Network (LDNet) that can accurately predict the evolution of complex systems in low-dimensional spaces. This approach offers significant innovations over traditional methods, enabling up to 5 times more accurate results with a reduction of over 90% in...
Researchers created mathematical models to examine aspects of human behavior affecting pandemic trends. They found that risk perception and adherence to preventive measures are crucial in understanding why similar policies resulted in different outcomes.
Research reveals that spatial patterns in dryland vegetation are critical for adapting to changing environmental conditions. The study provides empirical evidence supporting the role of self-organized clusters in maintaining ecosystem function and health.
Researchers developed a mathematical model showing how cicadas come to a consensus about local average temperature, leading to large-scale swarms. The model is related to those describing 'avalanches' in decision-making among stock market traders, highlighting the importance of communication in collective behavior.
A team of scientists and philosophers identifies a new law of nature that governs the evolution of complex systems, including plants, animals, stars, and minerals. The law states that complex systems evolve to states of greater patterning, diversity, and complexity, regardless of whether they are living or nonliving.
Researchers propose a new framework to explain the emergence of 'dynamical heterogeneities' in glass-forming liquids, which become increasingly correlated as they cool down. This study provides insights into the Stoke-Einstein breakdown and suggests a new handle for understanding other complex systems with intermittent dynamics.
Researchers from the University of Oldenburg developed a new stochastic method to mitigate sudden swings in wind turbine power output. The study found that control systems are mainly responsible for short-term fluctuations and can be optimized to ensure more consistent energy output.
A groundbreaking study by Florida Atlantic University reveals that agency emerges from the coupled relation between humans and their environment. Infants are found to discover their causal powers and transition from spontaneous to intentional behavior at a critical level of coordination, marking an abrupt increase in movement rate.
Researchers created a comprehensive index of human cells mapping sizes and abundance across the entire body. The study reveals surprising mathematical patterns underlying cell size and number, challenging fundamental understanding of cell growth and proliferation.
A new paper suggests that ecology can inspire more powerful, resilient, and socially responsible AI to solve complex problems. Artificial intelligence systems can incorporate greater amounts of data and diverse sources, discovering new interactions and drivers that may not have been considered before.
Researchers at the University of Sydney and Max Planck Institute have developed new methods to describe synchronicity in complex systems. Their findings suggest that convergent walks on a network structure can lead to poor quality synchronisation.
Researchers at EPFL have developed the Backtracking Dynamical Cavity Method (BDCM) to study disordered systems, which are found in materials science, climate, and social networks. By tracing steps backward from stable points, the BDCM provides valuable insights into complex system dynamics.
The study uses an improved artificial bee colony algorithm to minimize potential issues with ETRVs, such as excessive energy consumption and operational safety concerns. The algorithm successfully finds the most competitive solution on all instances, achieving significant improvement over other comparative algorithms.
Human cells have been found to synchronize their movements in unison, similar to grandfather clocks, allowing them to work more efficiently and combat diseases. This new understanding can pave the way for developing biochemical tools to prevent serious diseases like cancer and diabetes.
GOBI overcomes model-free and model-based inference method limitations by introducing an easily testable condition for a general monotonic ODE model to reproduce time-series data. It successfully infers positive and negative regulations in various networks, distinguishing between direct and indirect causation.
A research team applied a variable reduction strategy to an emergency material scheduling problem, simplifying the model and reducing complexity. The approach improved optimization efficiency and yielded higher-quality solutions, offering insights into effective solution methods for large-scale problems.