Evolutionary Models Research Articles

Experimental study on tribological behavior of a binderless cemented carbide at high contact stress

Knowledge of frictional evolution and associated damage mechanism during sliding wear conditions using binderless WC-based cemented carbide is lacking. In this study, the frictional evolution and corresponding transformation of microstructure, and wear mechanisms of Al2O3/WC-based cemented carbide due to the effect of different contact pressure, especially high pressure have been explored using a reciprocating ball-on-flat sliding wear tester, which was experimentally simulated following the ASTM G133–02 standard. The dynamic curves in friction coefficient with the sliding time were described. The microscopic 3D topography of contact surface was obtained by the MFP-3D atomic force microscope. The material removal and the wear rate were discussed. Worn surface morphologies at different moments, cross-sectional images of wear tracks at different loads, and wear debris were taken by field emission scanning electron microscope. The results suggested that the pressure plays a decisive role in frictional evolution and wear characteristics. Two models of frictional evolution were declared. A novel “surge” phenomena in friction coefficient was found and explained at high contact pressure. Wear transition from mild wear to severe wear was confirmed. More than one wear mechanism was observed, including micro-cutting (polishing), generation and propagation of cracks, cracking-induced spalling, plastic deformation, and the formation of tribolayer.

Closed equation model for cavity evolution in granular media

Closed equation model for cavity evolution in granular media

Evolutionary trajectory for nuclear functions of ciliary transport complex proteins.

SUMMARYCilia and the nucleus were two defining features of the last eukaryotic common ancestor. In early eukaryotic evolution, these structures evolved through the diversification of a common membrane-coating ancestor, the protocoatomer. While in cilia, the descendants of this protein complex evolved into parts of the intraflagellar transport complexes and BBSome, the nucleus gained its selectivity by recruiting protocoatomer-like proteins to the nuclear envelope to form the selective nuclear pore complexes. Recent studies show a growing number of proteins shared between the proteomes of the respective organelles, and it is currently unknown how ciliary transport proteins could acquire nuclear functions and vice versa. The nuclear functions of ciliary proteins are still observable today and remain relevant for the understanding of the disease mechanisms behind ciliopathies. In this work, we review the evolutionary history of cilia and nucleus and their respective defining proteins and integrate current knowledge into theories for early eukaryotic evolution. We postulate a scenario where both compartments co-evolved and that fits current models of eukaryotic evolution, explaining how ciliary proteins and nucleoporins acquired their dual functions.

The tripartite evolutionary game of enterprises' green production strategy with government supervision and people participation

Government supervision and people participation play vital roles in enterprises' green production strategy, but few studies have considered the strategy choices behind government supervision and people's participation. This study contended that whether an enterprise adopts the green production strategy is influenced not only by its responsible attitude facing social responsibility but also by the following two factors, the intensity of government supervision and whether people choose to participate in supervision or not when facing the enterprise adopting the green production strategy or not. We constructed a tripartite evolutionary game model to explore the behavioral evolution rules and evolutionary stability strategies of government supervision, people participation, and enterprises' green production. Then we employed numerical simulation to analyze how various factors influence the strategy selection of the government, people, and enterprises. The results show that if the utility values of government supervision and people participation are greater than 0, the enterprises will adopt the green production strategy. The system stability is affected by a synergistic relationship between participation cost, reputation benefit, and government subsidies, and an incremental relationship between enterprises' green production benefit, government subsidies, people's reported bonus, and enterprises' green production cost. This study provides a new theoretical perspective for research on government supervision, people participation, and enterprises' green production strategy, and the results provide important references for improving the enterprises' green production and urban environmental management.

Study on the Weibull distribution function-based stochastic damage evolution law for uniaxial compression in high-performance concrete with full aeolian sand

The issues of environmental degradation due to natural sand overextraction are becoming increasingly severe. In desert regions, utilizing aeolian sand as a substitute for natural sand in construction projects facilitates the resource economization and the effective management of desertification. The concrete industry is expected to significantly contribute to this objective, as high-performance concrete with full aeolian sand (FA-HPC) has demonstrated excellent mechanical properties. However, current researches have yet to establish a rational damage evolution law for uniaxial compression in FA-HPC from the perspective of damage characteristics. In this study, uniaxial compression tests were conducted on FA-HPC with different mixture proportions. Simultaneously, the stress-strain behavior was examined, and acoustic emission (AE) signals were collected and localized. Based on the Weibull distribution function-based stochastic damage evolution law for uniaxial compression, regression analyses of the stress-strain and AE cumulative ringing count for FA-HPC were performed. Damage evolution model for effective stress and damage variable were established and validated with experimental data to confirm their applicability. The scale and shape parameters of the model were predicted using the mixture proportions as independent variables. The results show that the rationality of the damage evolution law assumption was validated through AE source localization. The goodness of fit values for damage variable and effective stress equation range from 0.87 to 0.98, with the ascending segment and the vicinity of the peak point closely matching the experimental data, indicating that the Weibull distribution function-based stochastic damage model for uniaxial compression is applicable for FA-HPC. The predicted values of the damage evolution model parameters based on the mixture proportions align well with the measured values, achieving a goodness of fit of 0.99, thereby guiding the study of FA-HPC's compressive characteristics prior to the formation of primary cracks. Notably, there remains a need to propose corrective equations to enhance the correlation between regression curves and experimental data in the late failure stages of FA-HPC in future research, achieving precise predictions by considering the interactions of multiple factors.

Novel integration of PSO-enhanced damage mechanics and finite element method for predicting medium–low-cycle fatigue life in perforated structures

In this research, we introduce an innovative approach that combines the Continuum Damage Mechanics-Finite Element Method (CDM-FEM) with the Particle Swarm Optimization (PSO)-based technique, to predict the Medium-Low-Cycle Fatigue (MLCF) life of perforated structures. First, fatigue tests are carried out on three center-perforated structures, aiming to assess their fatigue life under various strengthening conditions. These tests reveal significant variations in fatigue life, accompanied by an examination of crack initiation through the analysis of fatigue fracture surfaces. Second, an innovative fatigue life prediction methodology is applied to perforated structures, which not only forecasts the initiation of fatigue cracks but also traces the progression of damage within these structures. It leverages an elastoplastic constitutive model integrated with damage and a damage evolution model under cyclic loads. The accuracy of this approach is validated by comparison with test results, falling within the three times error band. Finally, we explore the impact of various strengthening techniques, including cross-sectional reinforcement and cold expansion, on the fatigue life and damage evolution of these structures. This is achieved through an in-depth comparative analysis of both experimental data and computational predictions, which provides valuable insights into the behavior of perforated structures under fatigue conditions in practical applications.

Gaia BH1 and BH2 — Evolutionary Models with Overshooting of the Black Hole Progenitors within the Present-Day Binary Separation

Abstract Three black holes (BHs) in wide binaries — Gaia BH1, BH2 and BH3 — were recently discovered. The likely progenitors of the BHs were massive stars that experienced a supergiant phase, reaching radii of ∼1000R⊙, before collapsing to form the BH. Such radii are difficult to accommodate with the present-day orbits of BH1 and BH2 — with semi-major axes of 1.4 and 3.7 au, respectively. In this letter, we show that the maximal radii of the supergiants are not necessarily so large, and realistic stellar evolution models, with some assumed overshooting above the convective core into the radiative stellar envelope, produce substantially smaller maximal radii. The limited expansion of supergiants is consistent with the empirical Humphreys-Davidson limit — the absence of red supergiants above an upper luminosity limit, notably lower than the highest luminosity of main-sequence stars. We propose that the evolution that led to the formation of Gaia BH1 and BH2 simply did not involve an expansion to the cool supergiant phase.

Subaru/CHARIS High-resolution Mode Spectroscopy of the Brown Dwarf Companion HD 33632 Ab

Brown dwarfs (BDs) are model degenerate in age and mass. High-contrast imaging and spectroscopy of BD companions to host stars where the mass and age can be independently constrained by dynamics and stellar age indicators, respectively, provide valuable tests of BD evolution models. In this paper, we present a new epoch of Subaru/CHARIS H- and K-band observations of one such previously discovered system, HD 33632 Ab. We reanalyze the mass and orbit using our new epoch of extracted relative astrometry and fit extracted spectra to the newest generation of equilibrium, disequilibrium, and cloudy spectral and evolution models for BDs. No spectral model perfectly agrees with evolutionary tracks and the derived mass and age, instead favoring a somewhat younger BD than the host star’s inferred age. This tension can potentially be resolved using atmosphere and evolution models that consider both clouds and disequilibrium chemistry simultaneously or by additional future spectra at higher resolution or in other band passes. Photometric measurements alone remain consistent with the luminosity predicted by evolutionary tracks. Our work highlights the importance of considering complexities like clouds, disequilibrium chemistry, and composition when comparing spectral models to evolutionary tracks.

Molecular evolution of intestinal-type early gastric cancer according to Correa cascade.

Early screening is crucial for the prevention of intestinal-type gastric cancer. The objective of the current study was to ascertain molecular evolution of intestinal-type gastric cancer according to the Correa cascade for the precise gastric cancer screening. We collected sequential lesions of the Correa cascade in the formalin-fixed and paraffin-embedded endoscopic submucosal dissection-resected specimens from 14 Chinese patients by microdissection, and subsequently determined the profiles of somatic aberrations during gastric carcinogenesis using the whole exome sequencing, identifying multiple variants at different Correa stages. The results showed that TP53, PCLO, and PRKDC were the most frequently mutated genes in the early gastric cancer (EGC). A high frequency of TP53 alterations was found in low-grade intraepithelial neoplasia (LGIN), which further increased in high-grade intraepithelial neoplasia (HGIN) and EGC. Intestinal metaplasia (IM) had no significant correlation with EGC in terms of mutational spectra, whereas both LGIN and HGIN showed higher genomic similarities to EGC, compared with IM. Based on Jaccard similarity coefficients, three evolutionary models were further constructed, and most patients showed linear progression from LGIN to HGIN, ultimately resulting in EGC. The ECM-receptor interaction pathway was revealed to be involved in the linear evolution. Additionally, the retrospective validation study of 39 patients diagnosed with LGIN indicated that PRKDC mutations, in addition to TP53 mutations, may drive LGIN progression to HGIN or EGC. In conclusion, the current study unveils the genomic evolution across the Correa cascade of intestinal-type gastric cancer, elucidates the underlying molecular mechanisms of gastric carcinogenesis, and provides some evidence for potential personalized gastric cancer surveillance.

An evolutionary game analysis of the prefabricated building supply side under dynamic government reward and punishment mechanisms

From the standpoint of the supply side of prefabricated buildings, an evolutionary game model between the government and developers is constructed under the static and dynamic reward and punishment mechanisms in order to promote the development of prefabricated buildings and realize the transformation and upgrading of the construction industry. The simulation study of the example is conducted, and the impact of policy cost, subsidy upper limit, and tax upper limit on the system’s evolutionary stability strategy is examined. The findings demonstrate that when the government chooses static subsidy and static tax policies, there is no evolutionary stable strategy in the game system. The flaws of the static reward and punishment system can be adequately compensated for by the dynamic subsidy and dynamic tax policy, leading to an evolutionary stable state. The likelihood of developers producing prefabricated structures is negatively connected with policy cost and subsidy upper limits and favorably correlated with tax upper limits, according to the dynamic reward and punishment mechanism. The findings of the study have significant implications for government policy that will encourage the widespread use of prefabricated structures in China.

An analysis of optimal equilibrium in the carbon trading market - From a tripartite evolutionary game perspective

As the climate crisis intensifies, achieving the global consensus of carbon peaking and carbon neutrality has become imperative. Carbon trading is an important financial measure to address the environmental crisis, and the realization of the dual‑carbon goals requires the cooperation and joint efforts of all parties involved in the carbon emissions trading market. This study constructs a dynamic evolutionary game model involving enterprises, government, and financial institutions while considering consumers' influence. By solving for equilibrium points and conducting numerical simulations, we explore optimal strategy choices for each stakeholder. Our findings reveal that the success of enterprise low-carbon transition is contingent upon market dynamics and requires active cooperation from government, financial institutions, and the public. Furthermore, factors such as financial market efficiency and internal governance capacity significantly impact enterprises' transformation decisions by influencing low-carbon transition costs. Public feedback indirectly affects enterprise decisions through its influence on financial institutions' provision of green services. Additionally, gradual reduction of carbon quotas by government entities facilitates progress toward low-carbon transformation objectives.

The JWST Resolved Stellar Populations Early Release Science Program. VI. Identifying Evolved Stars in Nearby Galaxies

We present an investigation of evolved stars in the nearby star-forming galaxy Wolf–Lundmark–Melotte (WLM), using Near-Infrared Camera (NIRCam) imaging from the JWST Resolved Stellar Populations Early Release Science program. We find that various combinations of the F090W, F150W, F250M, and F430M filters can effectively isolate red supergiants and thermally pulsing asymptotic giant branch (TP-AGB) stars from one another, while also providing a reasonable separation of the primary TP-AGB subtypes: carbon-rich C-type stars and oxygen-rich M-type stars. The classification scheme we present here agrees very well with the well-established Hubble Space Telescope (HST) medium-band filter technique. The ratio of C to M-type stars is 0.8 ± 0.1 for both the new JWST and the HST classifications, which is within 1σ of empirical predictions from optical narrowband CN and TiO filters. The evolved star colors show good agreement with the predictions from the PARSEC + COLIBRI stellar evolutionary models, and the models indicate a strong metallicity dependence that makes stellar identification even more effective at higher metallicity. However, the models also indicate that evolved star identification with NIRCam may be more difficult at lower metallicities. We test every combination of NIRCam filters using the models and present additional filters that are also useful for evolved star studies. We also find that ≈90% of the dusty evolved stars are carbon rich, suggesting that carbonaceous dust dominates the present-day dust production in WLM, similar to the findings in the Magellanic Clouds. These results demonstrate the usefulness of NIRCam in identifying and classifying dust-producing stars without the need for mid-infrared data.

The Scale of Stellar Yields: Implications of the Measured Mean Iron Yield of Core Collapse Supernovae

The scale of α-element yields is difficult to predict from theory because of uncertainties in massive star evolution, supernova physics, and black hole formation, and it is difficult to constrain empirically because the impact of higher yields can be compensated by greater metal loss in galactic winds. We use a recent measurement of the mean iron yield of core collapse supernovae (CCSN) by Rodriguez et al., y¯Fecc=0.058±0.007M⊙ , to infer the scale of α-element yields by assuming that the plateau of [α/Fe] abundance ratios observed in low-metallicity stars represents the yield ratio of CCSN. For a plateau at [α/Fe]cc = 0.45, we find that the population-averaged yields of O and Mg are about equal to the solar abundance of these elements, logyOcc/ZO,⊙=logyMgcc/ZMg,⊙=−0.01±0.1 , where yXcc is the mass of element X produced by massive stars per unit mass of star formation. The inferred O and Fe yields agree with predictions of the Sukhbold et al. CCSN models assuming their Z9.6+N20 neutrino-driven engine, a scenario in which many progenitors with M < 40M ⊙ implode to black holes rather than exploding. The yields are lower than assumed in many models of the galaxy mass–metallicity relation, reducing the level of outflows needed to match observed abundances. Our one-zone chemical evolution models with η=Ṁout/Ṁ*≈0.6 evolve to solar metallicity at late times. By further requiring that models reach [α/Fe] ≈ 0 at late times, we infer a Hubble-time integrated Type Ia supernova rate of 1.1×10−3M⊙−1 , compatible with estimates from supernova surveys.

The radius distribution of M dwarf-hosted planets and its evolution

Abstract M dwarf stars are the most promising hosts for detection and characterization of small and potentially habitable planets, and provide leverage relative to solar-type stars to test models of planet formation and evolution. Using Gaia astrometry, adaptive optics imaging, and calibrated gyrochronologic relations to estimate stellar properties and filter binaries we refined the radii of 117 Kepler Objects of Interest (confirmed or candidate planets) transiting 74 single late K- and early M-type stars, and assigned stellar rotation-based ages to 113 of these. We constructed the radius distribution of 115 small (&amp;lt;4R⊕) planets and assessed its evolution. As for solar-type stars, the inferred distribution contains distinct populations of ‘super-Earths’ (at ∼1.3R⊕) and ‘sub-Neptunes’ (at ∼2.2 R⊕) separated by a gap or ‘valley’ at ≈1.7R⊕that has a period dependence that is significantly weaker (power law index of -0.03$^{+0.01}_{-0.03}$) than for solar-type stars. Sub-Neptunes are largely absent at short periods (&amp;lt;2 days) and high irradiance, a feature analogous to the ‘Neptune desert’ observed around solar-type stars. The relative number of sub-Neptunes to super-Earths declines between the younger and older halves of the sample (median age 3.86 Gyr), although the formal significance is low (p = 0.08) because of the small sample size. The decline in sub-Neptunes appears to be more pronounced on wider orbits and low stellar irradiance. This is not due to detection bias and suggests a role for H2O as steam in inflating the radii of sub-Neptunes and/or regulating the escape of H/He from them.

Leveraging intergovernmental data sharing for digital transformation in ecological and environmental protection

The data-sharing problem in the digital transformation of ecological environmental protection is a result of complex interactions and continuous strategic interactions among governments. While existing research has focused on the application and impact of digital technologies in ecological environmental protection, there remains a paucity of micro-level investigations into data sharing among different local governments regarding ecological environment protection. Notably, the issue of data barriers between local governments is particularly prominent. This paper analyzes the data-sharing problem in the digital transformation of ecological environmental protection through an evolutionary game model involving central and local governments, providing new perspectives and methods for understanding and improving data sharing and governance of ecological environmental protection, thereby promoting the digital transformation of the ecological environmental governance system and governance capacity. It finds that six stable equilibrium strategies can form based on local government participation levels, with the superior government's active promotion and regulation being crucial for achieving stable, multi-party participation. Key factors include the superior government's administrative costs and incentives, and local governments' benefits, costs, and risk considerations. The study highlights the importance of benefit-sharing rules and provides optimization strategies for enhancing intergovernmental data sharing.

The impacts of climate change, early agriculture and internal fluvial dynamics on paleo-flooding episodes in Central China

Floods clustered in episodes are the most prevalent natural disaster worldwide, causing substantial economic and human losses. Although these events are often linked to time-periods of extreme rainstorms and unique atmospheric circulation patterns, the river basin characteristics affected by anthropogenic land use changes could exert a strong influence. However, the way and extent of how land use changes across different time scales affect flooding periods are still unclear, especially considering the historical land use changes. This study uses the Landlab landscape evolution model, coupled with an evapotranspiration model, to investigate the forcing factors for the paleo-flooding trends in the Wei River catchment over the last 5000 years. The results indicate that the flooding period from 4400 to 4000 BP was caused by an increase of 28 % in antecedent moisture content as well as a decrease of 28 % in its spatial variability, which are primarily due to climate change, and that the contribution of land-use change is less than 5 %. The increases of about 14 % and 8 % in main channel sedimentation rate play a leading role in flood generation during the time periods from 3400 to 2800 BP and 2000–1400 BP, respectively. These two periods of increased flooding are primarily caused by the erosional effects of increasing anthropogenic land use, whose contributions range from 33 % to 64 %. Furthermore, based on our modelling results, we suggest that the downstream propagation of the main flooding locations, from the Wei River to the lower reaches of the Yellow River, can be explained by the downstream migrating sediment wave. In conclusion, our simulation results give new insights into the causes of Holocene flooding periods in the middle Yellow River from the perspective of dynamic changes in catchment characteristics, which is helpful to improve regional flood risk management under future climate change and anthropogenic activities.

Is the low-energy tail of shock-accelerated protons responsible for over-ionized plasma in supernova remnants?

Abstract Over-ionized, recombining plasma is an emerging class of X-ray bright supernova remnants (SNRs). This unique thermal state, where the ionization temperature ($T_{\rm z}$) is significantly higher than the electron temperature ($T_{\rm e}$), is not expected from the standard evolution model that assumes a point explosion in a uniform interstellar medium, thus requiring a new scenario for the dynamical and thermal evolution. A recently proposed idea attributes the over-ionization state to additional ionization contribution from the low-energy tail of shock-accelerated protons. However, this new scenario has been left untested, especially from the atomic physics point of view. We report calculation results of the proton impact ionization rates of heavy-element ions in ejecta of SNRs. We conservatively estimate the requirement for accelerated protons, and find that their relative number density to thermal electrons needs to be higher than $5\ (k T_{\rm e}/1\:\mbox{keV})\%$ in order to explain the observed over-ionization degree at $T_{\rm z}/T_{\rm e} \ge 2$ for K-shell emission. We conclude that the proton ionization scenario is not feasible because such a high abundance of accelerated protons is prohibited by the injection fraction from thermal to non-thermal energies, which is expected to be $\sim\! 1\%$ at most.

Blockchain Technology Adoption by Critical Stakeholders in Prefabricated Construction Supply Chain Based on Evolutionary Game and System Dynamics

Blockchain technology (BT) is a promising solution to address information asymmetry and trust issues in the prefabricated construction supply chain (PCSC). However, its practical application in PCSC remains limited under the influence of stakeholders’ adoption strategies. While previous studies have analyzed drivers and barriers to BT adoption, they often take a static view, neglecting the long-term dynamic decision-making interactions between stakeholders. This study addresses this gap by examining the interests of owners, general contractors, and subcontractors, and by developing a tripartite evolutionary game model to analyze the interaction mechanism of the strategy of adopting BT in PCSC. Additionally, a system dynamics simulation validates the evolution of stabilization strategies and examines the impact of key parameters. The results indicate that successful BT adoption requires technology maturity to surpass a threshold between 0.5 and 0.7, along with a fair revenue and cost-sharing coefficient between general contractors and subcontractors, ranging from 0.3 to 0.5 at the lower limit and 0.7 to 0.9 at the upper limit. Notably, general contractors play a pivotal role in driving BT adoption, acting as potential leaders. Furthermore, appropriate incentives, default compensation, and government subsidies can promote optimal adoption strategies, although overly high incentives may reduce owners’ willingness to mandate BT adoption. This study provides practical insights and policy recommendations for critical stakeholders to facilitate the widespread adoption of BT in PCSC.

Toward a Comprehensive Grid of Cepheid Models with MESA. I. Uncertainties of the Evolutionary Tracks of Intermediate-mass Stars

Helium-burning stars, in particular Cepheids, are especially difficult to model, as the choice of free parameters can greatly impact the shape of the blue loops—the part of the evolutionary track at which the instability strip is crossed. Contemporary one-dimensional stellar evolution codes, like Modules for Experiments in Stellar Astrophysics (MESA), come with a large number of free parameters that allow us to model the physical processes in stellar interiors under many assumptions. The uncertainties that arise from this freedom are rarely discussed in the literature despite their impact on the evolution of the model. We calculate a grid of evolutionary models with MESA, varying several controls, like solar mixture of heavy elements, mixing-length theory prescription, nuclear reaction rates, the scheme to determine convective boundaries, atmosphere model, and temporal and spatial resolution, and quantify their impact on age and location of the evolutionary track on the H-R diagram from the main sequence until the end of core helium burning. Our investigation was conducted for a full range of masses and metallicities expected for classical Cepheids. The uncertainties are significant, especially during core helium burning, reaching or exceeding the observational uncertainties of logTeff and logL for detached eclipsing binary systems. For ≥9 M ⊙ models, thin convective shells develop and evolve erratically, not allowing the models to converge. A careful inspection of Kippenhahn diagrams and convergence study is advised for a given mass and metallicity, to assess how severe this problem is and to what extent it may affect the evolution.

Optimized patient-specific immune checkpoint inhibitor therapies for cancer treatment based on tumor immune microenvironment modeling.

Enhancing patient response to immune checkpoint inhibitors (ICIs) is crucial in cancer immunotherapy. We aim to create a data-driven mathematical model of the tumor immune microenvironment (TIME) and utilize deep reinforcement learning (DRL) to optimize patient-specific ICI therapy combined with chemotherapy (ICC). Using patients' genomic and transcriptomic data, we develop an ordinary differential equations (ODEs)-based TIME dynamic evolutionary model to characterize interactions among chemotherapy, ICIs, immune cells, and tumor cells. A DRL agent is trained to determine the personalized optimal ICC therapy. Numerical experiments with real-world data demonstrate that the proposed TIME model can predict ICI therapy response. The DRL-derived personalized ICC therapy outperforms predefined fixed schedules. For tumors with extremely low CD8 + T cell infiltration ('extremely cold tumors'), the DRL agent recommends high-dosage chemotherapy alone. For tumors with higher CD8 + T cell infiltration ('cold' and 'hot tumors'), an appropriate chemotherapy dosage induces CD8 + T cell proliferation, enhancing ICI therapy outcomes. Specifically, for 'hot tumors', chemotherapy and ICI are administered simultaneously, while for 'cold tumors', a mid-dosage of chemotherapy makes the TIME 'hotter' before ICI administration. However, in several 'cold tumors' with rapid resistant tumor cell growth, ICC eventually fails. This study highlights the potential of utilizing real-world clinical data and DRL algorithm to develop personalized optimal ICC by understanding the complex biological dynamics of a patient's TIME. Our ODE-based TIME dynamic evolutionary model offers a theoretical framework for determining the best use of ICI, and the proposed DRL agent may guide personalized ICC schedules.