Researchers developed a metric to quantify the impact of social determinants on disease transmission, finding that even low-risk populations can be vulnerable to outbreaks due to social factors. The study highlights the need for equitable resource distribution in infectious disease control, benefiting everyone in the process.
A new model of conformity excels in real-world data, disregarding outliers to produce more accurate results. The researchers tested the model against various scenarios and found it superior to the French-Harary-DeGroot model in many cases.
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.
A study published in Nature Sustainability finds that climate policies targeting lifestyle changes can erode existing 'green' values, leading to unintended negative effects. Researchers surveyed over 3,000 Germans and found a 52% greater negative response to climate mandates than COVID-19 mandates.
Researchers have determined that computational devices must dissipate at least as much heat as the useful information transmitted, challenging earlier views of communication costs. This finding has implications for building energy-efficient systems and could inspire future computer architecture.
A new study reveals that Normalized Mutual Information (NMI), a widely used metric for algorithm performance, can produce biased results. The researchers developed an asymmetric, reduced version of the mutual information metric to eliminate biases and improve comparison across fields.
A recent study proposes a model that links individual risk tolerance to environmental factors, influencing learning strategies and community resilience. The model predicts that wealthy individuals are more likely to take risks, while vulnerable communities rely on traditions to manage risk, leading to persistent cautious attitudes.
The use of AI in the criminal justice system raises concerns about fairness and transparency. Researchers advise for clear understanding of data used and procedure by judges to use guidance from AI systems. Explainable AI systems may help, but transparency doesn't have to mean understanding computer code.
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.
Researchers have developed an algorithm to infer the structure of hypergraphs using only observed dynamics, allowing for the analysis of complex systems without prior knowledge. The approach was tested on EEG data from over 100 human subjects and accurately captured higher-order interactions in the brain.
A recent study found that many professions follow a nested structure in job skills, where advanced skills depend on prior mastery of broader skills. This has significant implications for wage inequality and career mobility. Basic educational skills are essential for developing higher-order reasoning and can lead to higher wage premiums.
A new paper challenges the long-held principle of parsimony in modeling, suggesting that complex models can be more flexible and accurate. Researchers argue that relying too much on parsimony can lead to misapplied assumptions and biased results, highlighting the need for a tool to guide model building.
A new mathematical model offers a more realistic representation of how conformist and anti-conformist biases shape cultural traits through a population. The study finds that populations rarely converge to a single trait, and even small variations in individual behavior result in persistent diversity.
A hybrid method links bottom-up behaviors and top-down causation in a single theory to capture interactions between small-scale behaviors and system-level properties in disturbed systems. The approach has been tested in examples such as post-fire forest ecosystems and pandemics, predicting ecological patterns and system dynamics.
Researchers have developed a new field called stochastic thermodynamics, which provides tools to investigate and quantify the energetics of computational systems far from thermal equilibrium. This can help minimize heat losses and optimize energy efficiency in computing.
The publication of the Malleus maleficarum in 1487 played a crucial role in spreading persecution across Europe, with each new edition leading to an increase in witch trials. Social influence, particularly from neighboring cities, also contributed to the spread of witch-hunting practices.
Researchers have found that higher-order interactions can lead to deeper basins of attraction, making solutions more stable, while also shrinking the basins themselves.
The Networks of Beliefs theory presents a comprehensive model of individual- and social-level belief dynamics, integrating personal, social, and external dissonances. By understanding these interplay dynamics, researchers can better grasp how beliefs change when we pay attention to different parts of our belief system.
Several common analogies used to model belief dynamics are examined for their conceptual mileage and baggage. The authors argue that while these analogies can provide useful concepts and methodologies, they have limitations and can lead to inaccurate inferences. To construct accurate models, researchers should consider multiple sources...
Researchers show that individuals can influence others to make decisions in the best interest of society through social norms and positive feedback loops. This approach can be more effective than centralized models in achieving collective action.
A new study suggests that specific physical conditions during the Snowball Earth era, including ocean viscosity and resource deprivation, may have driven eukaryotes to form multicellular colonies. This finding provides a potential explanation for the long delay in the evolution of multicellularity.
A new model suggests that strong policies can backfire in polarized societies if people perceive low risk, leading to a rebound in fossil fuel use. In highly polarized situations, social interactions reinforce dominant norms, making it harder for subsequent transitions to occur.
Researchers introduce mathematical equations revealing minimum and maximum predicted energy cost of computational processes with randomness, offering insights into computing energy-cost bounds. The framework offers a way to calculate lower bounds on the energy cost of unpredictable finish situations.
Researchers propose reuniting variance, exactitude, and coarse-grained cultures to advance biosphere science and inform solutions to 21st-century challenges. Integration of these cultures can reveal assumptions, challenge theories with data, and guide new data collection.
Physicists develop new method to efficiently determine all possible first-passage times and their probabilities, capturing randomness of both walker and environment. This approach builds on existing ideas and could improve predictive analyses in fields such as biology, migration systems, and financial markets.
A new simulation model examines the conditions under which institutions emerge and persist, highlighting the critical role of competition and learning from out-groups. The study builds on Elinor Ostrom's design principles for successful management, shifting focus to understanding how collective property rights arise and spread.
Researchers found that larger, more diverse, and less segregated cities experience decreased implicit racial biases due to increased social interactions. This is attributed to a lack of cosmopolitan public spaces where people can interact with others from different groups, creating barriers to equity.
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.
A new study finds that cities with higher per-capita GDP generate more waste, while economies of scale reduce greenhouse gas emissions. The research uses scaling theory to analyze waste products from over 1,000 cities worldwide.
Uncertainty in thermodynamic parameters can influence experiment outcomes, suggesting a new approach to modifying stochastic thermodynamics equations. This oversight has implications for various systems, including cells and optical tweezers, where precision is limited by the uncertainty in system parameters.
Pre-modern states faced a steeply increasing risk of collapse within two centuries after formation, driven by environmental degradation, economic inequality, and other internal mechanisms. The research highlights the need to understand these internal processes that contribute to state demise.
A recent study published in Science has found that 75% of possible mutations in E. coli protein lead to high antibiotic resistance, contradicting the longstanding fitness landscapes theory. This discovery has significant real-world implications for understanding antibiotic resistance and evolutionary processes.
Researchers have identified a major weakness in reservoir computing, a powerful machine learning tool used to model complex dynamic systems. The tool requires a lengthy warm-up time and relies on key information about the system being predicted being built in, making it challenging to accurately predict chaotic behaviors.
Researchers Gabriel Gellner and Kevin McCann develop an inverse approach to modeling food webs, assuming ecosystems exist and working backward to characterize web dynamics. This method, using biological constraints, succeeds in simulating large, diverse ecosystems and understanding their stability.
Research team used genome models to test viability, persistence, and evolvability of prokaryote endosymbioses, finding that more than half were viable but often less fit and adaptable than their ancestors. The study suggests metabolic network compatibility is unlikely the limiting factor in prokaryotic endosymbiosis.
A workshop at the Santa Fe Institute explores the complex interplay of contagions, including infectious diseases, social phenomena, and online behavior. Researchers aim to develop new tools to study interactions between different types of contagion.
Researchers study how choice of network framework affects synchronization, finding that hypergraphs promote easier synchronization than simplicial complexes. The choice of representation can influence the outcome, suggesting structural heterogeneity is key to understanding collective dynamics.
A new study reveals that the COVID-19 pandemic exacerbated racial inequalities in the US criminal legal system, with non-white individuals disproportionately receiving longer sentences. The study found that the population shift due to the pandemic increased the fraction of incarcerated Black and Latino people.
A recent study uses sparsification to identify critical links in a network, reducing computation time for simulating disease spread. The technique preserves overall dynamics while removing non-essential edges, enabling faster simulations of large-scale pandemics.
A new study led by Stefani Crabtree reveals that sustainable practices are often hindered by the flow of information between humans and their environments. The research provides a framework to assess how societies interact with their environments for good or ill, guiding environmental decision-making.
A new study by Helena Miton and Simon DeDeo presents a model for the transmission of tacit knowledge, which is passed down with limited specification. The model captures how learners overcome constraints to succeed in complex practices, predicting stability over time with minimal information.
Archaeoecology examines the past 60,000 years of human-ecosystem interactions, revealing how humans impacted nature and ecosystems shaped human culture. By integrating data from archaeology, ecology, and palaeoecology, this emerging field can provide crucial insights to solve today's environmental challenges.
A new predictive network model estimates how much dissonance people experience when holding conflicting beliefs about a topic. This approach can help determine who will change their minds about contentious scientific issues when presented with evidence-based information.
A new general theory describes how temperature affects living things at all scales, predicting patterns in metabolism, growth rate, and mortality rate. The model combines elements lacking in earlier attempts, providing a universal framework for understanding temperature's impact on biology.
Researchers developed a framework to investigate the bidirectional relationship between masking and disease. They found that without proper enforcement of masking, mass vaccination may not be enough to reduce epidemic size.
A new model offers a physics-inspired way to evaluate rankings, providing accurate predictions in various systems. The continuous numbering system allows for better handling of discrete data, enabling the calculation of ranking probabilities and uncertainty.
A new study by Santa Fe Institute researchers Katrin Schmelz and Samuel Bowles found that people's opposition to vaccines quadrupled when mandated, but many switched to pro-vaccination as they became more convinced of the vaccines' effectiveness. To increase vaccination rates, policymakers need to focus on building trust and changing h...
A new study reveals that individuals use covert online signals to convey their political identity, especially in mixed groups. This allows them to communicate without risking negative reactions from those who disagree. The research found that people prefer overt signals in homogeneous groups.
A team of researchers identified universal patterns in the chemistry of life that do not appear to depend on specific molecules. They discovered scaling laws between the number of enzymes in different functional classes and an organism's genome size, which don't depend on particular enzymes.
A new study reveals that roots are the true engine of terrestrial nutrient cycling, driving biodiversity in South Africa's Fynbos and Afrotemperate Forest biomes. The research found that Fynbos plants use thinnest roots to limit nutrient availability for trees, allowing them to outcompete forest species.