সংরক্ষণ করুন:
| প্রধান লেখক: | |
|---|---|
| বিন্যাস: | Recurso digital |
| ভাষা: | ইংরেজি |
| প্রকাশিত: |
Zenodo
2025
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| বিষয়গুলি: | |
| অনলাইন ব্যবহার করুন: | https://doi.org/10.5281/zenodo.17538075 |
| ট্যাগগুলো: |
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সূচিপত্রের সারণি:
- <p>This paper introduces a novel theoretical framework for understanding the evolution of senescence, recasting it as an information-dynamic process. We apply the Dynamic Entropy--Complexity Correspondence (DECC) to model an organism's life history. We establish a rigorous foundation by modeling the unfolding of the developmental program over the lifespan as a Continuous-Time Markov Process governed by a Master Equation. From this, we rigorously derive the Age-Dependent Complexity Dynamics Equation (CDE). By weighting the CDE terms by Fisher's reproductive value ($V_{a}$), we transform the problem of life-history evolution into one of optimal control. We demonstrate that the canonical theories of senescence---Disposable Soma (DS), Antagonistic Pleiotropy (AP), and Mutation Accumulation (MA)---emerge as distinct classes of solutions to a single variational problem. The DS theory is shown to be an optimal strategy trading late-life robustness ($\dot{\Delta}<0$) for early-life phenotypic expression ($\dot{H}(X)>0$). AP represents a constrained trajectory, while MA arises from vanishing selective pressure ($V_{a}\rightarrow 0$). This synthesis provides a unified, mathematically rigorous foundation for senescence, explaining it as an evolved, optimal, and information-theoretically constrained strategy.</p>