Speed Of Evolution Research Articles

Effect of dented residual stress on the surface-defect-induced pitting under rolling contact loading of M50 bearing steel

Surface-defect-induced pitting gradually becomes the limitation of the rolling contact fatigue life of the M50 bearing steel as the subsurface initiation spalling probability decreases recently. Dent formation lives residual stress (RS). However, it was ignored in past studies on surface-initiated pitting. Therefore, this study established a continuous simulation model from particle compression to cycle rolling contact loading to study the dent-induced RS effects on damage evolution. The constitutive model of damage evolution incorporated continuum damage mechanics and cohesive mechanics. The results show that the depth-width ratio of the dent and RS increases as the load and hardness increase. RS makes both subsurface-initiation-damage and surface-initiation-damage advance, and affects the direction and speed of the surface damage evolution. Moreover, the size of the pitting in the rolling direction increases as hardness increases.

PHDtools: A platform for pathogen detection and multi-dimensional genetic signatures decoding to realize pathogen genomics data analyses online

ObjectivesFacing the emerging diseases, rapid identification of the pathogen and multi-dimensional characterization of the genomic features at both isolate-level and population-level through high-throughput sequencing data can provide invaluable information to guide the development of antiviral agents and strategies. However, a user-friendly program is in urgent need for clinical laboratories without bioinformatics background to decode the complex big genomics data. MethodsIn this study, we developed an interactive online platform named PHDtools with a total of 15 functions to analyze metagenomics data to identify the potential pathogen and decode multi-dimensional genetic signatures including intra-/inter-host variations and lineage-level variations. The platform was applied to analyze the meta-genomic data of the samples collected from the 172 imported COVID-19 cases. ResultsAccording to the analytical results of mNGS, 27 patients were found to have the co-infections of SARS-CoV-2 with either influenza virus (n = 9) or human picobirnavirus (n = 19). Enough coverages of all the assembled SARS-CoV-2 genomes provided the sub-lineages of Omicron variant, and the number of mutations in the non-structural genes and M gene was increased, as well as the intra-host variations occurred in E and M gene were under positive selection (Ka/Ks > 1). These findings of increased or changed mutations in the SARS-CoV-2 genome characterized the current adaptive evolution patterns of Omicron sub-lineages, and revealed the evolution speed of these sub-lineages might increase. ConclusionsConsequently, the application of PHDtools has proved that this platform is accurate, user-friendly and convenient for clinical users who are deficient in bioinformatics, and the clinical monitor of SARS-CoV-2 genomes by PHDtools also highlighted the potential evolution features of current SARS-CoV-2 and indicated that the development of anti-SARS-CoV-2 agents and new-designed vaccines should incorporate the gene variations other than S gene.

Development of Machine Learning Models for Studying the Premixed Turbulent Combustion of Gas-To-Liquids (GTL) Fuel Blends

AbstractStudying the spatial and temporal evolution in turbulent flames represents one of the most challenging problems in the combustion community. Based on previous 3D numerical analyses, this study aims to develop data-driven machine learning (ML) models for predicting the flame radius evolution and turbulent flame speeds for diesel, gas-to-liquids (GTL), and their 50/50 blend (by volumetric composition) under different thermodynamic and turbulence operating conditions. Two ML models were developed in this study. Model 1 predicts the variations of the flame radius with time, equivalence ratio, and turbulence intensity, whereas model 2 predicts the variations of the turbulence flame speed with the operating parameters. The k-fold cross-validation technique is used for model training, and the developed neural network-based model is used to investigate the effects of operating parameters on the premixed turbulent flames. In addition, the possible minimum and maximum values of responses at the corresponding operating parameters are found using a genetic algorithm (GA) approach. Model 1 could capture the computational fluid dynamics (CFD) outputs with high precision at different flame radiuses and time instants with a maximum absolute error percentage of 5.46%. For model 2, the maximum absolute error percentage was 6.58%. Overall, this study demonstrates the applicability and promising performance of the proposed ML models, which will be used in subsequent research to analyze turbulent flames a posteriori.

A three-player game model for promoting enterprise green technology innovation from the perspective of media coverage.

The objective of this study was to explore the game relationship among enterprise, the government, and the public under the new media environment, so as to provide decision-making reference for improving enterprise green technology innovation and promoting economy high-quality development with new media participation. This study constructs a three-subject evolutionary game model of enterprise, government, and public based on multi-agent relationship analysis and evolutionary game theory. In addition, the derivation of an evolutionary equilibrium strategy and numerical simulation analysis is carried out to comprehensively explore the evolution trajectory of green technology innovation system under the new media environment. (1) The system may have four stable evolutionary strategies: (1,0,0), (0,0,1), (1,0,1), and (1,1,1). (2) The initial strategy probability of various actors would affect the system evolution speed but not the evolution result, and the authenticity of new media reports is an important factor determining the system evolution of green technology innovation. (3) Numerical simulation results show that a fair and just new media environment can effectively constrain the traditional production behavior of enterprise, actively guide the public to participate in supervision, and play an alternative role to government regulation to a certain extent. This study explores the evolutionary balance strategy of green technology innovation system under the new media environment, which not only enriches relevant theories of media environment governance but also has important reference value for promoting enterprises' green technology innovation and establishing an environmental governance system jointly governed by government, enterprise, public, and media.

Optimal quantum speed for mixed states

The question of how fast a quantum state can evolve is considered. Using the definition of squared speed based on the Euclidean distance given in (Brody and Longstaff 2019 Phys. Rev. Res. 2 033127), we present a systematic framework to obtain the optimal speed of a d-dimensional system evolved unitarily under a time-independent Hamiltonian. Among the set of mixed quantum states having the same purity, the optimal state is obtained in terms of its purity parameter. We show that for an arbitrary d, the optimal state is represented by a X-state with an additional property of being symmetric with respect to the secondary diagonal. For sufficiently low purities for which the purity exceeds the purity of maximally mixed state I/d by at most 2/d2 , the only nonzero off-diagonal entry of the optimal state is ϱ1d , corresponding to the transition amplitude between two energy eigenstates with minimum and maximum eigenvalues, respectively. For larger purities, however, whether or not the other secondary diameter entries ϱi,d−i+1 take nonzero values depends on their relative energy gaps |Ed−i+1−Ei| . The effects of coherence and entanglement, with respect to the energy basis, are also examined and found that for optimal states both resources are monotonic functions of purity, so they can cause speed up quantum evolution leading to a smaller quantum speed limit. Our results show that although the coherence of the states is responsible for the speed of evolution, only the coherence caused by some off-diagonal entries located on the secondary diagonal play a role in the fastest states.

Modeling Group Opinion Evolution on Online Social Networks: A Gravitational Field Perspective

The research on group behavior is effective for establishing a good network environment since people in social networks tend to form groups spontaneously. Most studies on group behavior on online social networks assume that all individuals are reduced to one cluster, ignoring the existence of potential clusters and their importance in group opinion dynamics. This article introduces a novel group-gravitational field (GGF) model to investigate the opinion evolution based on group behavior by the following aspects: 1) the GGF model reduces a cluster in the social network into a charge and the whole network into a gravitational field; 2) the GGF model calculates the initial influence of a cluster according to the topology information and further constructs a gravity matrix of the network based on the Coulomb law; and 3) opinion-leader clusters exert the internal field force on common opinion clusters inside the gravitational field. The GGF model simulates the evolution of opinions among clusters in a network and studies the law of group behavior according to the influence between clusters based on Coulomb’s law. Experiments on real social networks verify that the GGF model enhances the speed of opinion evolution significantly. The simulation experiments indicate that the existence of clusters promotes the rapid convergence of opinions, a gathering of followers influences information dissemination in social networks, and the GGF model fits the reality better. This article provides a new approach to network supervision and control.

Coupling Effect and Chain Evolution of Urban Rail Transit Emergencies

Emergency events such as fire, flood and COVID-19 occurred in urban rail transit (URT) usually triggered chain effect and evolved into huge disaster. This kind of chain with complexity and uncertainty evolution brought great challenges to the safety management of the system. Thus, the coupling effects of emergencies and then its relationship with the chain evolution is necessary to analyze emphatically. A Graph Evaluation and Review Technique Simulation (GERTS) evolution network is firstly constructed to describe the coupling effect and chain evolution of emergencies. Then, considering the internal and external influencing factors of the emergency chain, a dynamic evolution model of the emergency chain based on Coupled Map Lattice (CML) is proposed. This paper takes fire chain of URT as an example to simulate the evolution process of emergency chain, and analyze the impact of different coupling effects and various influencing factors on the evolution of emergency chain. The results of numerical simulation show that the AND-coupling can significantly inhibit the evolution of emergency events, while the OR-coupling and CO-coupling can expand the impact scope of emergency events. In addition, the evolution speed of emergency events can be controlled by increasing the coupling action time and improving the URT repair ability. When an emergency event occurs, the analysis of coupling effect and the accompanied chain evolution will help managers to make scientific judgment on the development trend of the emergency events and make targeted emergency defense measures.

Time evolution of the inner structure of antimony phosphate nanosheet suspension developing structural colouration.

Structural colouration observed in antimony phosphate nanosheet suspensions has been known for two decades, but the stability of their inner structures has not been a topic in colloidal nanosheet systems. In this study, we investigate the time evolution of structures in suspension using UV-visible spectrometry and small-angle X-ray scattering. Here, we report that antimony phosphate nanosheet systems re-organise their inner structures, especially at lower concentrations (isotropic or biphasic region), and that the basal spacing decreases with time after sample preparation, although the evolution speed depends on the sample concentration. The stability of the inner structure of the suspension is essential for their application as structural colour materials in sensors and colourants.

A deep multiple-instance text binary classification for topic relevant content extraction on social media

Social media platforms have rich text data, which can be used in data mining and analysis. However, given the fact, the evolution speed of natural languages is rapid in social media, and data on social media is very noisy. This is a great challenge to the accuracy of data analysis. To overcome this problem, we propose a topic-relevant content extraction (TRCE) based on deep multiple instance classification, leveraging existing information and hierarchical relationships among texts under a thread on social media as weak supervision to extract topic-strong-relevant data and filter out noise accurately without manually labeling data. The proposed method introduces latent variables, Bernoulli distribution, and variational inference into multiple-instance learning (MIL) to generate pseudo labels. Then we employ a dual-stream neural network with a 3-stage training process to achieve training MIL end-to-end. Experimental results show TRCE has a significant improvement compared with other MIL methods. Meanwhile, it only has a little decrease compared with supervised text classification on accuracy and F1 score. Given the fact TRCE does not need manually labeled data at all, while supervised classification relies heavily on labeled data, TRCE is a competitive method to extracting topic-relevant data and filtering out noise on social media.

Does sociality affect evolutionary speed?

Does sociality affect evolutionary speed?

Evolution of dispersal and the maintenance of fragmented metapopulations

Because it affects dispersal risk and modifies competition levels, habitat fragmentation directly constrains dispersal evolution. When dispersal is traded off against competitive ability, increased fragmentation is often expected to select higher dispersal. Such evolutionary effects could favor the maintenance of the metapopulation by fostering spatial rescue effects. Using an evolutionary model, we first investigate how dispersal evolves in a metapopulation when fragmentation and aggregation of this fragmentation are fixed. Our results suggest that high fragmentation indeed selects for dispersal increase, but this effect is largely reduced in aggregated landscapes, to the point of being nonexistent at the highest aggregation levels. Contrasted dispersal strategies coexist at high fragmentation levels and with no or low aggregation. We then simulate time‐varying fragmentation scenarios to investigate the conditions under which evolutionary rescue of the metapopulation happens. Faster evolution of dispersal favors the persistence of the metapopulation, but this effect is very reduced in aggregated landscapes. Overall, our results highlight how the speed of evolution of dispersal and the structuration of the fragmentation will largely constrain metapopulation survival in changing environments.

Fabrication of S-scheme Zn1-xCdxS/NiO heterojunction for efficient photocatalytic hydrogen evolution

Establishing S-heterojunction was considered to be effective strategy to accelerate the speed of photocatalytic hydrogen evolution. In this study, we synthesized the S-scheme Zn1-xCdxS/NiO heterojunction by growing Zn1-xCdxS (ZCS) nanoparticles on NiO nanosheets for efficient photocatalytic hydrogen evolution. The photogenerated holes in ZCS could rapidly quenching with the photogenerated electrons of NiO though a S-scheme process, leaving the photogenerated electrons in the conduction band (CB) of ZCS for reduction of H+. The hydrogen evolution reactivity of the optimal ZCS/NiO was 259.2 mmol g−1 h−1, with the apparent quantum efficiency (AQE) of 15.8 % at 420 nm, which was 4.3 and 1728.0 times that of ZCS nanoparticle and NiO nanosheet, respectively. More importantly, the hydrogen evolution rate of ZCS/NiO was still 462.5 μmol g−1 h−1 without adding the sacrificial agent. This work provided a view for constructing S-scheme heterojunction to enhance photocatalytic hydrogen evolution performance.

Multi-scenario analyses for antitrust immunity policies on shipping alliances: A dynamic tripartite evolutionary game perspective

Shipping alliances are regarded as a special group in antitrust immunity policies worldwide because of their abilities to coordinate shipping resources. In particular, the international shipping involves different countries and stakeholders, making it difficult to form a unified antitrust immunity and maritime policy. This study builds a tripartite dynamic evolutionary game model composed of stakeholders including the shipping alliances, ports, and governments. It analyses the complex impacts of government policy, cooperation between the port and shipping alliance, accountability mechanism, and sudden changes in the external environment on the different stakeholders’ decisions. The stability points, evolution process, and evolution speed of the tripartite game, along with the movement of the convergence point in the unstable state, are investigated. Furthermore, the mutual influence of the three parties, especially that of government policy on the evolution process regarding the pricing strategy and antitrust immunity, is discussed. The results show that the reduction in the freight rate difference makes it easier for the alliance to choose a low-freight strategy under the antitrust immunity policy. The government could cooperate with the port and indirectly restrict the alliance through the port extra charge, while an increase in the alliance supply would weaken the port’s bargaining power. This research also investigates the timing of government regulation by considering the sudden fluctuations of the market and the international political risk when the three parties exert a push–pull pressure on one another’s decisions and provides comprehensive decision support for the three parties from the perspective of dynamic evolution.

Benefits of Non-Destructive Evaluation and Probabilistic Damage Tolerance Cosimulation for Fracture Risk Reduction

In the context of the damage tolerance approach used to drive aircraft maintenance operations, it is essential to demonstrate the reliability of NDE inspections in detecting structural damage especially for additively manufactured components since this process produces components that may introduce material anomalies at any location within a component. The Probability Of Detection curve (POD) that links the probability to detect a detrimental flaw to its size is generally used as a key indicator for that purpose by giving the maximum flaw size that a NDE process can miss with a given level of probability and confidence. This information can then be used along with other inputs such as component geometries, mechanical properties, constraints, service and residual stresses and damage evolution speed to assess fracture risk and then adapt maintenance scenarios to optimize safety and component service life. NDE reliability and risk assessment are based on statistical indicators that need a large amount of data to provide reliable metrics. It is difficult to obtain such indicators using a purely empirical approach that is based on physical trials and measurements as it may involve many mock-ups and costly processes. Simulation tools can achieve this goal via their ability to include and precisely monitor many parameters as well as high computing capacities that are now available. The work presented in this paper involved cosimulations performed between the DARWIN® probabilistic damage tolerance software and the CIVA NDE simulation software. DARWIN computes fracture risk levels throughout a component, while CIVA can efficiently provide Probability Of Detection curves at different locations in a component and for various NDE methods. The presented application deals with a titanium gas turbine engine impeller disk and involves an Ultrasonic NDE inspection technique. It appears to be a very interesting approach to connect together NDE and Fracture mechanics simulations, two disciplines that generally work on their own. Indeed, DARWIN helps the user to determine detrimental flaw types, locations and sizes which are key inputs to develop an effective NDE inspection method. CIVA can provide location-specific POD curves that enable DARWIN to quantity the effect of dedicated NDE on potential risk reduction. This highlights the importance of NDE simulation for safety and helps to identify potential changes in the physical NDE process and the maintenance cycle that provide the best compromise between detection performance and cost.

Lichen Biodiversity and Near-Infrared Metabolomic Fingerprint as Diagnostic and Prognostic Complementary Tools for Biomonitoring: A Case Study in the Eastern Iberian Peninsula.

In the 1990s, a sampling network for the biomonitoring of forests using epiphytic lichen diversity was established in the eastern Iberian Peninsula. This area registered air pollution impacts by winds from the Andorra thermal power plant, as well as from photo-oxidants and nitrogen depositions from local and long-distance transport. In 1997, an assessment of the state of lichen communities was carried out by calculating the Index of Atmospheric Purity. In addition, visible symptoms of morphological injury were recorded in nine macrolichens pre-selected by the speed of symptom evolution and their wide distribution in the territory. The thermal power plant has been closed and inactive since 2020. During 2022, almost 25 years later, seven stations of this previously established biomonitoring were revaluated. To compare the results obtained in 1997 and 2022, the same methodology was used, and data from air quality stations were included. We tested if, by integrating innovative methodologies (NIRS) into biomonitoring tools, it is possible to render an integrated response. The results displayed a general decrease in biodiversity in several of the sampling plots and a generalised increase in damage symptoms in the target lichen species studied in 1997, which seem to be the consequence of a multifactorial response.

Genomic estimates of mutation and substitution rates contradict the evolutionary speed hypothesis of the latitudinal diversity gradient.

The latitudinal diversity gradient (LDG) refers to a decrease in biodiversity from the equator to the poles. The evolutionary speed hypothesis, backed by the metabolic theory of ecology, asserts that nucleotide mutation and substitution rates per site per year are higher and thereby speciation rates are higher at higher temperatures, generating the LDG. However, prior empirical investigations of the relationship between the temperature and mutation or substitution rate were based on a few genes and the results were mixed. We here revisit this relationship using genomic data. No significant correlation between the temperature and mutation rate is found in 13 prokaryotes or in 107 eukaryotes. An analysis of 234 diverse trios of bacterial taxa indicates that the synonymous substitution rate is not significantly associated with the growth temperature. The same data, however, reveal a significant negative association between the nonsynonymous substitution rate and temperature, which is explainable by a larger fraction of detrimental nonsynonymous mutations at higher temperatures due to a stronger demand for protein stability. We conclude that the evolutionary speed hypothesis of the LDG is unsupported by genomic data and advise that future mechanistic studies of the LDG should focus on other hypotheses.

Quantum evolution speed and its limit in the driven double‐well system

AbstractWe investigate quantum evolution speed in the driven double‐well system using the entangled trajectory molecular dynamics method. We emphasize not only the evolution speed of the quantum state but also its limit according to different definitions. The Wasserstein 1‐distance is used to quantify the distance between distinguishable quantum states in the phase space, the quantum speed limit based on the geometry has been shown to be the strictest one. The single trajectory's contribution to the quantum speed limit is discussed, which is related to both the time evolution of the trajectory and its position in the total Wigner function. The resonance and chaos strongly enhance the evolution speed and its limit in the driven double‐well system. The resonance effect makes a large proportion of representative points pass through the well as a whole, nevertheless, the chaos makes the Wigner function disperse in the phase space.

The Genetic Code Assembles via Division and Fusion, Basic Cellular Events.

Standard Genetic Code (SGC) evolution is quantitatively modeled in up to 2000 independent coding 'environments'. Environments host multiple codes that may fuse or divide, with division yielding identical descendants. Code division may be selected-sophisticated gene products could be required for an orderly separation that preserves the coding. Several unforeseen results emerge: more rapid evolution requires unselective code division rather than its selective form. Combining selective and unselective code division, with/without code fusion, with/without independent environmental coding tables, and with/without wobble defines 25 = 32 possible pathways for SGC evolution. These 32 possible histories are compared, specifically, for evolutionary speed and code accuracy. Pathways differ greatly, for example, by ≈300-fold in time to evolve SGC-like codes. Eight of thirty-two pathways employing code division evolve quickly. Four of these eight that combine fusion and division also unite speed and accuracy. The two most precise, swiftest paths; thus the most likely routes to the SGC are similar, differing only in fusion with independent environmental codes. Code division instead of fusion with unrelated codes implies that exterior codes can be dispensable. Instead, a single ancestral code that divides and fuses can initiate fully encoded peptide biosynthesis. Division and fusion create a 'crescendo of competent coding', facilitating the search for the SGC and also assisting the advent of otherwise uniformly disfavored wobble coding. Code fusion can unite multiple codon assignment mechanisms. However, via code division and fusion, an SGC can emerge from a single primary origin via familiar cellular events.

Exploring the Evolution Speed of a Two-qubit System Under Weak Measurement and Measurement Reversal in Correlated Noise Channels

Exploring the Evolution Speed of a Two-qubit System Under Weak Measurement and Measurement Reversal in Correlated Noise Channels

On nonlinear description of neutrino flavour evolution in solar matter

We formulate a formalism of the neutrino state evolution as an open system in the Sun, obtained by solving a quasilinear extension of the von Neumann equation. We obtain similar predictions for the averaged neutrino survival probability measured on Earth as in the Mikheev–Smirnov–Wolfenstein (MSW) approach, differing by details inside the Sun where the quasilinear evolution predicts suppression of oscillations. We discuss the issue of energy transfer between the neutrino and the Sun and the speed of the neutrino state evolution.