Statistical Physics of Evolving Systems

Evolution is customarily perceived as a biological process. However, when formulated in terms of physics, evolution is understood to entail everything. Based on the axiom of everything comprising quanta of actions (e.g., quanta of light), statistical physics describes any system evolving toward thermodynamic balance with its surroundings systems. Fluxes of quanta naturally select those processes leveling out differences in energy as soon as possible. This least-time maxim results in ubiquitous patterns (i.e., power laws, approximating sigmoidal cumulative curves of skewed distributions, oscillations, and even the regularity of chaos). While the equation of evolution can be written exactly, it cannot be solved exactly. Variables are inseparable since motions consume driving forces that affect motions (and so on). Thus, evolution is inherently a non-deterministic process. Yet, the future is not all arbitrary but teleological, the final cause being the least-time free energy consumption itself. Eventually, trajectories are computable when the system has evolved into a state of balance where free energy is used up altogether.

Integrating Stochastic and Deterministic Process in the Biogeography of N2-Fixing Cyanobacterium Candidatus Atelocyanobacterium Thalassa

UCYN-A is one of the most widespread and important marine diazotrophs. Its unusual distribution in both cold/warm and coastal/oceanic waters challenges current understanding about what drives the biogeography of diazotrophs. This study assessed the community assembly processes of the nitrogen-fixing cyanobacterium UCYN-A, developing a framework of assembly processes underpinning the microbial biogeography and diversity. High-throughput sequencing and a qPCR approach targeting the nifH gene were used to investigate three tropical seas: the Bay of Bengal, the Western Pacific Ocean, and the South China Sea. Based on the neutral community model and two types of null models calculating the β-nearest taxon index and the normalized stochasticity ratio, we found that stochastic assembly processes could explain 66–92% of the community assembly; thus, they exert overwhelming influence on UCYN-A biogeography and diversity. Among the deterministic processes, temperature and coastal/oceanic position appeared to be the principal environmental factors driving UCYN-A diversity. In addition, a close linkage between assembly processes and UCYN-A abundance/diversity/drivers can provide clues for the unusual global distribution of UCYN-A.

Randomness in the Cosmos

After an introduction of the concepts of randomness and determinacy, I present simple definitions of ‘random number or variable’ or ‘random event’, ‘pseudo-random numbers’, ‘stochastic process’, ‘chance’ and ‘probability’, ‘determinism’ (or ‘deterministic process’), and ‘chaos’. I then proceed to review the different cosmic processes and phenomena where randomness plays an important role. In all these types of processes, I show that there is an underlying “order”, in that there’s a probability distribution for the frequency of such events, the sizes of the objects under consideration, and so on. I conclude with some thoughts on randomness and order in the world and divine providence.

Spatiotemporal evolution and assembly processes of ammonia-oxidising prokaryotic communities in 1000 years coastal reclaimed soils

Coastal marshes are transitional areas between terrestrial and aquatic ecosystems and vulnerable to climate change and anthropogenic activities. In recent decades the reclamation of coastal marshes remarkably increased and their effects on microbial communities present in coastal marshes have been studied with great interest. However, most of these studies focused on microbial community composition and diversity. The processes underlying functional community assembly and spatiotemporal effect often ignored. Therefore, community structure and assembly mechanisms of ammonia-oxidising prokaryotes in long-term reclaimed coastal marshes have not been studied. Here using qPCR and IonS5TMXL sequencing platform, we investigated spatiotemporal dynamics, assembly processes and diversity patterns in ammonia-oxidising prokaryotes in over 1000 years reclaimed coastal salt marsh soils. The taxonomic & phylogenetic diversity and composition of the ammonia-oxidizers showed apparent spatiotemporal variations along reclamation of soil. The phylogenetic null modelling-based analysis showed across all sites, the archaeal ammonia-oxidising community assembled by deterministic process (84.71%). The ammonia-oxidising bacterial community was formed more by a stochastic process in coastal marshes and at stage 60 years (|βNTI|<2), despite its relatively dominant deterministic process (55.2%). The deterministic assembly process and nitrification activity in reclaimed soils was positively correlated. Archaeal amoA gene abundance were also positively correlated with the nitrification rate. Our study revealed that during the 1000 years of reclamation coastal marshes both ammonia-oxidising communities responded differently to diversity change and assembly processes and nitrification activity. These findings provide a better understanding of how long-term reclamation affect soil N cycling and assembly dynamics of ammonia-oxidising communities.

MATHEMATICAL MODELS FOR DIAGNOSTICS OF A BOLTED CONDUCTIVE JOINT UNDER CONDITIONS OF CHANGING MODE PARAMETERS

The reliability of the transmission and distribution of electricity in ports, ships and energy enterprises depends on the condition of the bolted conductive joints. Operational practice shows that 2 % of cases of emergency shutdowns of technological lines and fires on electrical equipment occur due to the weakening of bolted conductive joints. The main reasons for the bolted joint weakening are dynamic changes in operating current loads and changes in climatic parameters. It is possible to increase the reliability of bolted conductive joints using modern diagnostic methods that allow identifying the appearance of bolted joint weakening. The existing methods for diagnosing the state of bolted joints, which are based on monitoring the temperature of the bolted joint, are analysed. It has been established that the use of such methods to identify the initial moment of the joint weakening is impractical, since they react to the emergency state of the bolted joint, that is, to the critical temperature value. To identify the initial moment of the bolted joint weakening, it is proposed to simultaneously monitor the values of the load current and the parameters of the ambient air, which makes it possible to increase the reliability of detecting pre-emergency situations. To diagnose the initial moment of the bolted joint weakening, it is proposed to use the estimated Boolean functions. Arguments of Boolean variables are obtained for a stationary and continuous process of changing current and ambient temperatures, a stationary and deterministic process as well as a random and deterministic process. The minimized Boolean functions are given for the normal operation of the bolted joint, when the initial moment of weakening appears and when the emergency mode occurs.

Day-to-Day Dynamic Multivehicle Assignment: Deterministic Process Models

In the near future, transportation systems modelers and planners will likely be challenged by more complex scenarios. This is due to the different types of vehicles that include different (i) powertrains (conventional, hybrid, electric, etc.), (ii) ownerships (privately-owned vs. shared vehicles), and (iii) levels of automation (from human-driven to fully autonomous). All these different vehicle types compete for the same arcs and jointly participate to congestion. Thus, existing methods for travel demand assignment to a transportation network, the main tools for transportation systems analysis to support transportation project assessment and evaluation, need to be extended to cope with mixed traffic. In this paper, deterministic process models for day-to-day dynamic multivehicle assignment are presented, including fixed-point models for equilibrium assignment as a special case. Vehicle types may be distinguished with respect to several parameters, such as flow equivalence coefficient, occupancy factor, cost equivalence coefficient, and behavioral parameters. Results of an application to a toy network are also discussed showing that advanced vehicles (AVs) may or may not have a positive effect of equilibrium stability.

Extraneous E-Cadherin Engages the Deterministic Process of Somatic Reprogramming through Modulating STAT3 and Erk1/2 Activity

Although several modes of reprogramming have been reported in different cell types during iPSC induction, the molecular mechanism regarding the selection of different modes of action is still mostly unknown. The present study examined the molecular events that participate in the selection of such processes at the onset of somatic reprogramming. The activity of STAT3 versus that of Erk1/2 reversibly determines the reprogramming mode entered; a lower activity ratio favors the deterministic process and vice versa. Additionally, extraneous E-cadherin facilitates the early events of somatic reprogramming, potentially by stabilizing the LIF/gp130 and EGFR/ErbB2 complexes to promote entry into the deterministic process. Our current findings demonstrated that manipulating the pSTAT3/pErk1/2 activity ratio in the surrounding milieu can drive different modes of action toward either the deterministic or the stochastic process in the context of OSKM-mediated somatic reprogramming.

Assessing Accuracy of an Analytical Method in silico: Application to “Accurate Constant via Transient Incomplete Separation” (ACTIS)

<p>Analytical methods may not have reference standards required for testing their accuracy. We postulate that accuracy of an analytical method can be assessed in the absence of reference standards <i>in silico</i> if the method is built upon deterministic processes. A deterministic process can be precisely computer-simulated thus allowing virtual experiments with virtual reference standards. Here, we apply this <i>in silico</i> approach to study “Accurate Constant <i>via</i> Transient Incomplete Separation” (ACTIS), a method for finding the equilibrium dissociation constant (<i>K</i>_d) of protein–small molecule complexes. ACTIS is based on a deterministic process: molecular diffusion of the interacting protein–small molecule pair in a laminar pipe flow. We used COMSOL software to construct a virtual ACTIS setup with a fluidic system mimicking that of a physical ACTIS instrument. Virtual ACTIS experiments performed with virtual samples — mixtures of a protein and a small molecule with defined rate constants and, thus, <i>K</i>_d of their interaction — allowed us to assess ACTIS accuracy by comparing the determined <i>K</i>_d value to the input <i>K</i>_d value. Further, the influence of multiple system parameters on ACTIS accuracy was investigated. Within multi-fold ranges of parameters, the values of <i>K</i>_d did not deviate from the input <i>K</i>_d values by more than a factor of 1.25 strongly suggesting that ACTIS is intrinsically accurate and that its accuracy is robust. Accordingly, further development of ACTIS can focus on achieving high reproducibility and precision. We foresee that <i>in silico</i> accuracy assessment, demonstrated here with ACTIS, will be applicable to other analytical methods built upon deterministic processes.</p>