Articles tagged with Complex Systems
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.
Researchers argue that 'The Line' should not be a showcase for future cities due to its unfeasible urban design, including extremely high population density and limited mobility. The city's planned 60-minute average commute times highlight the importance of efficient transportation systems in urban planning.
Researchers outline a new approach to understanding complex ecosystems using complexity science, which could increase our understanding of the natural world. The study highlights the importance of nonlinearities, stability, and resilience in ecological systems.
Researchers at the Complexity Science Hub found that periodic outbreaks of warfare can account for boom-bust patterns in population dynamics of early farming societies. The study suggests that social conflict played a crucial role in shaping the population dynamics of these societies, contrary to previous assumptions that climate chang...
Researchers developed a new method, photoacoustic spectral analysis (PASA), to analyze the tumor microenvironment without invasive procedures. The technique uses laser light and sound waves to identify different types of tumors with high accuracy.
A deep neural network developed by researchers at the University of California - Santa Cruz has been shown to accurately classify particle signals with 99.8% accuracy in real-time. The system can identify weak or noisy signals and pinpoint their source, making it suitable for point-of-care applications.
Researchers propose a 'state space' approach to reframe farming planning questions, enabling analytics and machine learning to explore optimal crop combinations and simulate different scenarios. This framework allows farmers to design diverse agricultural landscapes based on natural ecosystems, increasing crop yield and sustainability.
A new theorem helps system designers make informed decisions about consistency and availability trade-offs in networks. The CAL theorem provides a quantitative relationship between these factors, allowing for more efficient and reliable network designs.
Scientists developed a new clustering method to analyze similarities between chess openings, revealing ten distinct clusters that group similar strategies. The new classification complements the existing ECO Code and provides insights into player skill and opening complexity.
A complex system economic model shows that inequality boosts intolerance, but redistribution of wealth can prevent its spread. Economically disfavored individuals from minority groups may prioritize helping wealthy individuals over their own group when discriminated against.
Researchers developed an economic-epidemiological model to assess the impact of no closures. The study found that California's unemployment rate would have been lower, but deaths and hospitalizations from COVID-19 would have increased significantly, exacerbating current inequities.
A new study by Dartmouth College researchers finds that sanctions on wealth managers would be more effective than asset seizure in crippling Russia's oligarchs. The research uses network science to map the connections between wealthy individuals and their financial experts, revealing a vulnerable network that can be disrupted with targ...
Scientists develop eigenmodes of structured light that remain undistorted even in turbulent channels, enabling robust transmission through noisy media. This breakthrough paves the way for future work in quantum light communication and imaging through complex systems.
A researcher at the University of Copenhagen solved a 30-year-old problem in computer science by applying Petri nets to forecast COVID epidemic development. The breakthrough enables individual-oriented modeling, which can be used in epidemiology and other fields.
A University of Houston researcher has developed a method to describe complex systems using the least number of variables possible, reducing complexity from millions to just one. This advancement speeds up science with efficiency and ability to understand and predict natural system behavior.
Researchers studied the body ownership illusion using integrated information theory, discovering a relationship between local and global brain-body processes. This work may help explain altered states of consciousness, such as the blurring of self and non-self, leading to feelings of uneasiness.
A new study warns that climate change will negatively impact mountain landscapes and human activity, increasing risks of natural hazards like avalanches and river floods. Mountain communities are also affected, with traditional practices like transhumance and agriculture dying out due to changing weather patterns and water scarcity.
A new computational model based on fruit fly brain data may help explain how humans process memories and experiences. The model suggests that living organisms, including humans, use a similar '1-2-3-many' count sketch to track encounters with familiar sights and smells.
Researchers have developed new stable quantum batteries that can reliably store energy into electromagnetic fields. The micromaser system allows for efficient charging with protection against overcharging and preserves the stored energy's purity.
Researchers used artificial intelligence to demonstrate the correlation between cytoskeleton organisation and nuclear position in eukaryotic cells. The study successfully predicted the presence and location of nuclei in over 8,000 cells with high accuracy, transforming the way scientists approach complex biological systems.
Researchers from Aarhus University are developing a new approach to turbulence modelling using physics-constrained machine learning to accurately simulate complex turbulent systems. The goal is to reduce computational costs while maintaining accuracy, enabling more efficient designs and predictions in various fields.
The Madrid Flight On Chip (MFOC) project has successfully implemented advanced technological products and introduced disruptive changes in the design and verification of complex space systems. The project, which ran for over three years, focused on Multi-Processor System on Chip (MPSoC) components and aimed to reduce testing costs.
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 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 developed a new way to apply antireflective coatings to 3D printed micro-optical systems, reducing light losses and improving imaging quality. The low-temperature coating technique can be used for applications such as miniature fiber endoscopes and virtual reality devices.
A new method predicts the starting materials and reaction paths of multi-step chemical reactions using only information about the target product molecule. The algorithm reduces the number of paths to explore, mitigating the combinatorial explosion that occurs in single-step reactions.
The new computational tool, AF2Complex, predicts the structure of protein complexes and their interactions, offering insights into biomolecular mechanisms. The model is based on AlphaFold 2 and performs well in predicting protein structures and complex formations.
Researchers create complex mixtures of biomolecules that spontaneously form self-organized patterns in response to environmental changes. This breakthrough bridges the complexity gap between chemistry and biology.
Researchers at NYU Tandon School of Engineering propose a paradigm to solve the problem of inferring collective size from individual behaviors. By observing self-propelled Vicsek particles, they show that the time rate of growth of mean square heading is sufficient to predict the number of particles under particular parameters.
Scientists at IIT realized coupled light vortices forming an ordered structure, a light crystal. They developed metasurfaces to control laser beams and created 100 light vortices with tunable topology, enabling new properties for optical communications and simulations of complex systems.
The Amazon rainforest is experiencing a decline in resilience, which could trigger dieback and have severe consequences for the environment. The study found that resilience has dropped consistently since the early 2000s, with parts of the forest losing resilience faster due to deforestation and climate change.
Researchers propose that cognitive activity operating on a planetary scale is necessary to tackle global issues. A mature technosphere involves integrating technological systems with Earth through feedback loops, making it self-maintaining and exhibiting emergent behavior.
Researchers from the Complexity Science Hub Vienna propose that homophily, or interacting with like-minded individuals, automatically leads to social balance and stability. They demonstrate this using data from the Massive Multiplayer Online Game Pardus, where players tend to form friendships with those who share similar characteristics.
A multidisciplinary team at UNIGE has developed a simple mathematical equation to explain the complex distribution of scales in ocellated lizards. This discovery contributes to a better understanding of skin color pattern evolution and provides an optimal pattern for animal survival.
A new framework, iDIRECT, can effectively infer direct relationships in association networks, improving our understanding of complex systems. This approach has been successfully applied to gene regulatory networks in E. coli and microbial communities in response to climate warming.
Researchers at George Washington University found that mainstream parenting communities were exposed to misinformation from alternative health and anti-vaccination communities on Facebook. The study reveals how social media machinery can pull these communities closer to extremes, highlighting the need for a new strategy to combat onlin...
This special issue examines the nature of tipping in complex systems, revealing recent trends and challenges. The studies highlight the pressing need to control tipping phenomena and harness their potential for efficient logic operations.
Researchers at Stanford University have developed a new method for rapidly prototyping complex geometries mirroring symmetries present in problems of interest. This technique uses a mixture of water and propylene glycol, along with a slippery surface, to create droplet lattices that can be manipulated and observed over time.
Aspen recovery in Yellowstone National Park has been found to be less robust than previously believed due to biased sampling methods. Random sampling of all young aspen within a stand revealed a slower rate of recovery compared to the five tallest young aspen, which were used in previous studies.
A new monitoring protocol preserves coherence in quantum Otto engines, leading to improved power output and reliability. The 'repeated contacts scheme' avoids measurement-induced quantum effects, making the engine more capable and dependable.
A study by UC3M researchers found that higher collective risks lead to stronger social norms and increased punishment for non-compliance. However, as perceived risk decreases, compliance with these norms also drops. The study, published in Nature Communications, provides evidence on how collective risks impact social behavior.
Research at Kyoto University using drones and a multi-agent system found that feral horses synchronize their behavior not only within unit groups but also across different parts of the herd. The study's results suggest that individual horses can recognize the behavior of distant individuals, averaging a nearest distance of 39.3m.
Physicists developed an electrical technique to study the Leidenfrost effect, revealing the temperature at which vapor layers form and collapse. The results show that stable vapor layers can be sustained at 240 degrees Celsius, with a minimum heat of 140 degrees Celsius required for their existence.
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 from NYUAD and University of Wisconsin-Madison develop interactive 3D diagrams to teach functional neuroanatomy. The study shows that VR exceeded PC viewing for experience-based learning outcomes, making it an enjoyable and easier learning tool.
Researchers found significant periodic flow velocity fluctuations in fuel injector ignite combustion oscillations, leading to high mechanical stress on the combustion chamber. The findings provide a reasonable answer for why these oscillations occur and have significant implications for preventing fatal damage in critical engines.
A recent study published in Nature Geoscience explores past abrupt climate changes and their tipping points. The research, led by Arizona State University scientist Michael Barton, analyzes historic data from sediment cores, dust records, and ice cores to quantify small changes that can lead up to massive changes.
Common pitfalls in internet energy analysis include oversimplification, conflation of internet usage with energy demand, projecting too far into the future, and overgeneralization. These errors can lead to inaccurate predictions of massive energy growth in IT, which often doesn't materialize
Scientists analyzed Twitter data during the 2019 Spanish general elections and Charlie Hebdo attack, finding a modular structure with internal hierarchies responding to user interests. This breakthrough in network analysis sheds light on the conditions required for coexistence of macro-scale patterns.
Researchers developed a new method to model complex earthquake rupture processes affecting systems of multiple faults. The approach was applied to the magnitude 7.9 Gulf of Alaska earthquake, revealing irregular behavior linked to pre-existing ocean floor features, including fracture zones and plate-bending faults.
A multidisciplinary team of scientists has developed a new way to detect phase transitions in raw data by analyzing its intrinsic dimension, a statistical property that reveals collective properties of partition functions. This method is agnostic and does not require prior knowledge of the system's parameters.
The research team developed a fast and affordable quantum random number generator, beating all previous records with a speed of 8.05 gigabits per second. This device has promising potential for commercial applications in cryptography and complex systems modeling.
Physical frailty is defined as a state of depleted reserves resulting in increased vulnerability to stressors. A complex systems approach suggests that interventions like physical activity can remedy frailty by addressing dysregulation across multiple interconnected physiological and biological systems.
The VEDLIoT project is developing a new generation of IoT platforms that use machine learning to improve the performance and energy efficiency of devices. The platform aims to enable autonomous vehicles, smart homes, and industrial applications to learn and adapt to their environments.
Researchers at Tokyo Institute of Technology developed a novel approach for modular controller design, enabling decentralized system upgrades without compromising stability. The new design allows individual subsystem developers to design and implement controllers independently, improving overall system performance.
A joint research group has developed a way to simulate the quantum physical properties of complex solid state systems using real systems of atoms. The team's approach uses mathematical and numerical methods to investigate which quantum systems are suitable for simulations, paving the way for progress in robust quantum computing.
Researchers developed a novel control architecture that defends complex, interconnected systems against cyberattacks by implementing a Leader-Follower approach. This algorithm can detect and isolate infected sub-systems, reducing the impact of targeted DoS attacks and increasing system robustness.
A new relationship between humanity and the ocean is required to secure the continuity of the diverse life support roles provided by the sea. The paper proposes three key transition pathways to make complex ocean systems more resilient and ensure a more sustainable future.