The clearest picture yet of LUCA suggests it was a relatively complex organism living 4.2 billion years ago, a time long considered too harsh for life to flourish.
This review article examines the current understanding of the origin and early evolution of eukaryotic cells, highlighting key events and players involved in this process, particularly focusing on the symbiotic relationship between an archaeal host and a bacterial endosymbiont.
This study uses ecological niche modeling to reconstruct the palaeodistribution of Neanderthals and anatomically modern humans during Marine Isotope Stage 5, identifying the Zagros Mountains as a potential contact and interbreeding zone.
This article lists five of the best open-source email clients for Linux, with a focus on Geary as the author's preferred choice. The article provides details on each client, including its strengths, weaknesses, and suitability for different user needs.
The paper proposes the "law of increasing functional information," a new law of nature that could help explain the evolution of complex systems across multiple scales in the universe, from atoms and molecules to stars and brains.
These systems are characterized by three attributes: they form from numerous components, processes generate numerous configurations, and configurations are preferentially selected based on function.
The law suggests that functional information of a system will increase over time when subjected to selection for function(s). The authors argue this law could help predict the behavior of these systems and provide a unified framework for understanding their evolution.
They suggest it could be a missing piece in our understanding of the universe.
These systems are characterized by three attributes: they form from numerous components, processes generate numerous configurations, and configurations are preferentially selected based on function.
The law suggests that functional information of a system will increase over time when subjected to selection for function(s). The authors argue this law could help predict the behavior of these systems and provide a unified framework for understanding their evolution.
They suggest it could be a missing piece in our understanding of the universe.
This article discusses the origin and migration of Homo sapiens, the first modern humans. It covers their evolution, the development of language, and their migration out of Africa between 70,000 and 100,000 years ago. It also touches upon the environmental impacts of human migration.
Explore the relationships between 2,235,473 species and discover images on a zoomable page.
- Life's evolution on Earth began with single-celled organisms and evolved into complex life forms through environmental factors and extinction events, culminating in the emergence of mammals and ultimately our own species.
- The article highlights the significance of our species, Homo sapiens, within the grand scheme of things, occurring within the last 300,000 years.
- Despite the limited time our species exists compared to the vastness of cosmic time, it encourages us to consider the potential for future life forms
- The article highlights the significance of our species, Homo sapiens, within the grand scheme of things, occurring within the last 300,000 years.
- Despite the limited time our species exists compared to the vastness of cosmic time, it encourages us to consider the potential for future life forms
P1. Loss function. In any evolving system, there exists a loss function of time-dependent variables that is minimized during evolution.
P2. Hierarchy of scales. Evolving systems encompass multiple dynamical variables that change on different temporal scales (with different characteristic frequencies).
P3. Frequency gaps. Dynamical variables are split among distinct levels of organization separated by sufficiently wide frequency gaps.
P4. Renormalizability. Across the entire range of organization of evolving systems, a statistical description of faster-changing (higher-frequency) variables is feasible through the slower-changing (lower-frequency) variables.
P5. Extension. Evolving systems have the capacity to recruit additional variables that can be utilized to sustain the system and the ability to exclude variables that could destabilize the system.
P6. Replication. In evolving systems, replication and elimination of the corresponding information-processing units (IPUs) can take place on every level of organization.
P7. Information flow. In evolving systems, slower-changing levels absorb information from faster-changing levels during learning and pass information down to the faster levels for prediction of the state of the environment and the system itself.
P2. Hierarchy of scales. Evolving systems encompass multiple dynamical variables that change on different temporal scales (with different characteristic frequencies).
P3. Frequency gaps. Dynamical variables are split among distinct levels of organization separated by sufficiently wide frequency gaps.
P4. Renormalizability. Across the entire range of organization of evolving systems, a statistical description of faster-changing (higher-frequency) variables is feasible through the slower-changing (lower-frequency) variables.
P5. Extension. Evolving systems have the capacity to recruit additional variables that can be utilized to sustain the system and the ability to exclude variables that could destabilize the system.
P6. Replication. In evolving systems, replication and elimination of the corresponding information-processing units (IPUs) can take place on every level of organization.
P7. Information flow. In evolving systems, slower-changing levels absorb information from faster-changing levels during learning and pass information down to the faster levels for prediction of the state of the environment and the system itself.
