Model Simulations Research Articles

Calculations of extreme sea level rise scenarios are strongly dependent on ice sheet model resolution

The West Antarctic Ice Sheet (WAIS) is losing ice and its annual contribution to sea level is increasing. The future behaviour of WAIS will impact societies worldwide, yet deep uncertainty remains in the expected rate of ice loss. High-impact low-likelihood scenarios of sea-level rise are needed by risk-averse stakeholders but are particularly difficult to constrain. Here, we combine traditional model simulations of the Amundsen Sea sector of WAIS with Gaussian process emulation to show that ice-sheet models capable of resolving kilometre-scale basal topography will be needed to assess the probability of extreme scenarios of sea-level rise. This resolution exceeds many state-of-the-art continent-scale simulations. Our ice-sheet model simulations show that coarser resolutions tend to project a larger range of sea-level contributions than finer resolutions, inflating the tails of the distribution. We therefore caution against relying purely upon simulations 5 km or coarser when assessing the potential for societally important high-impact sea-level rise.

Optimizing oil-water separation using fractal surfaces.

Oil has become a prevalent global pollutant, stimulating the research to improve the techniques to separate oil from water. Materials with special wetting properties-primarily those that repel water while attracting oil-have been proposed as suitable candidates for this task. However, one limitation in developing efficient substrates is the limited available volume for oil absorption. In this study, we investigate the efficacy of disordered fractal materials in addressing this challenge, leveraging their unique wetting properties. Using a combination of a continuous model and Monte Carlo simulations, we characterize the hydrophobicity and oleophilicity of substrates created through ballistic deposition (BD). Our results demonstrate that these materials exhibit high contact angles for water, confirming their hydrophobic nature while allowing significant oil penetration, indicative of oleophilic behavior. The available free volume within the substrates varies from 60% to 90% of the total volume of the substrate depending on some parameters of the BD. By combining their water and oil wetting properties with a high availability of volume, the fractal substrates analyzed in this work achieve an efficiency in separating oil from water of nearly 98%, which is significantly higher compared to micro-pillared surfaces made from the same material but lacking a fractal design.

Causes of growing middle-to-upper tropospheric ozone over the northwest Pacific region

Abstract. Long-term ozone (O3) changes in the middle-to-upper troposphere are critical to climate radiative forcing and tropospheric O3 pollution. Yet, these changes remain poorly quantified through observations in East Asia. Concerns also persist regarding the data quality of the ozonesondes available at the World Ozone and Ultraviolet Radiation Data Centre (WOUDC) for this region. This study aims to address these gaps by analyzing O3 soundings at four sites along the northwestern Pacific coastal region over the past 3 decades and by assessing their consistency with an atmospheric chemistry–climate model simulation. Utilizing the European Centre for Medium-Range Weather Forecasts (ECMWF) Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) nudged simulations, it is demonstrated that trends between model and ozonesonde measurements are overall consistent, thereby gaining confidence in the model's ability to simulate O3 trends and confirming the utility of potentially imperfect observational data. A notable increase in O3 mixing ratio around 0.29–0.82 ppb a−1 extending from the middle troposphere to the upper troposphere is observed in both observations and model simulations between 1990 and 2020, primarily during spring and summer. The timing of these O3 tongues is delayed when moving from south to north along the measurement sites, transitioning from late spring to summer. Investigation into the drivers of these trends using tagged model tracers reveals that O3 of stratospheric origin (O3S) dominates the absolute O3 mixing ratios over the middle-to-upper troposphere in the subtropics, contributing to the observed O3 increases by up to 96 % (40 %) during winter (summer), whereas O3 of tropospheric origin (O3T) governs the absolute value throughout the tropical troposphere and contributes generally much more than 60 % to the positive O3 changes, especially during summer and autumn. During winter and spring, a decrease in O3S is partly counterbalanced by an increase in O3T in the tropical troposphere. This study highlights that the enhanced downward transport of stratospheric O3 into the troposphere in the subtropics and a surge of tropospheric O3 in the tropics are the two key factors driving the enhancement of O3 in the middle-to-upper troposphere along the northwest Pacific region.

Closing the Circulation Budget

AbstractCirculation budgets can identify physical processes underpinning tropical cyclones, mesoscale convective vortices, and other weather systems where there are interactions across scales. It is unclear, however, how well these budgets close in practice. The present study uses the rapid intensification of Tropical Cyclone Nepartak (2016) as a case study to quantify the practical limitations of calculating circulation budgets using standard reanalyzes and numerical weather model data. First, we evaluate the circulation budget with ERA5. The budget residual can be reduced considerably by including contributions to circulation changes from subgrid‐scale momentum transports, and reduced further with 24‐hr smoothing, which dampens the discontinuous effects of data assimilation. Second, using a high‐resolution Met Office Unified Model simulation, we examine how the choice of the path used (the domain boundary) affects the budget closure. Third, the truncation errors associated with numerical differentiation in time and space are investigated. The circulation budget improves as the model data are analyzed with more frequent time output intervals, and as the output grid spacing decreases. For the tropical convective examples evaluated here, the column mean budget residuals increase by up to 50% as the output intervals increase from 5 min to 3 hr. Errors also increase if the data are regridded to a coarser horizontal grid spacing and when convection straddles the domain boundary. A key result is that the circulation budget need not close for physical inferences made about the circulation and its evolution to be meaningful, thus validating the use of the technique in prior studies.

Temperature seasonality regulates organic carbon burial in lake

Organic carbon burial (OCB) in lakes, a critical component of the global carbon cycle, surpasses that in oceans, yet its response to global warming and associated feedbacks remains poorly understood. Using a well-dated biomarker sequence from the southern Tibetan Plateau and a comprehensive analysis of Holocene total organic carbon variations in lakes across the region, here we demonstrate that lake OCB significantly declined throughout the Holocene, closely linked to changes in temperature seasonality. Process-based land surface model simulations clarified the key impact of temperature seasonality on OCB in lakes: increased seasonality in the early Holocene saw warmer summers enhancing ecosystem productivity and organic matter deposition, while cooler winters improved organic matter preservation. The Tibetan Plateau’s heightened sensitivity to climate and ecosystem dynamics amplifies these effects. With declining temperature seasonality, we predict a significant slowdown or reduction in OCB across these lake sediments, leading to carbon emissions and amplified global warming.

Evaluating Nitrogen Gas Injection Performance for Enhanced Oil Recovery in Fractured Basement Complex Reservoirs: Experiments and Modeling Approaches

This study explored the effectiveness of gas injection for enhanced oil recovery (EOR) in fractured basement complex reservoirs, combining laboratory experiments with numerical simulation analyses. The experiments simulated typical field conditions, focusing on understanding the interaction between the injected gas and the reservoir’s fracture–matrix system. The laboratory results showed that under the current reservoir pressure and temperature conditions, nitrogen gas flooding in the fractured matrix achieved a superior oil recovery efficiency compared to that of the other gases tested (CO2, APG, and oxygen-reduced air), exhibiting the most favorable movable oil saturation range and the lowest residual oil saturation. To evaluate the performance of nitrogen gas injection in a fractured basement complex reservoir, a 3D reservoir model with complex natural fractures was built in a numerical reservoir simulator. Special methods were required for the geological modeling and reservoir simulation, with the specific principles outlined. Numerical simulations of gas injection into fractured basement complex reservoirs revealed that cyclic gas injection was identified as the most effective strategy, balancing incremental oil recovery with minimized gas channeling risks. This study demonstrated that the optimal injection location and rate are crucial factors affecting the recovery performance. These findings provided actionable insights for implementing gas injection EOR strategies in fractured basement complex reservoirs, highlighting the importance of optimizing the injection parameters to maximize the recovery.

Relationship Between Urbanization–Induced Land Use Changes and Flood Risk: Case Study in Chiang Mai, Thailand

Urban flooding has long been a critical issue, particularly in rapidly urbanizing regions of developing countries, where land use changes—especially the conversion of rice paddies into urban areas—have significantly increased flood risks. This study investigated the impact of urbanization on flood risk taking Chiang Mai, Thailand, as a case study. Based on historical flood data, the study identified and analyzed frequent flood–prone areas in Chiang Mai during the period from 1990 to 2018. By integrating the Rainfall–Runoff–Inundation (RRI) model simulation results and the remote sensing data, the research quantified dynamics in flood risk, exposure, and vulnerability across these frequent flood–prone areas. The findings demonstrated that the conversion of high–exposure paddy fields into urban areas markedly elevated area flood risks, primarily due to the reduction in water retention capacity and the inheritance of the high–exposure characteristics of paddy fields. This study highlighted the importance of integrating sustainable urban planning and land management strategies in rapidly urbanizing regions. Furthermore, this study examined the feasibility of adopting flood characteristics quantification in frequent flood–prone areas as a systematic approach to analyze the dynamic interplay between flood risks and urbanization in developing countries.

Impact of Grid Resolution on Wave‐Mean Flow Interactions With High Resolution Mars Global Climate Model Simulations

AbstractWe have executed a series of simulations with the NASA Ames Mars Global Climate Model by systematically increasing horizontal and vertical resolution with the goal of resolving small‐scale waves that significantly affect the mean thermal and momentum structure of the atmosphere. Our reference high‐resolution simulation is 1/4° horizontal resolution and ∼1.5 km vertical resolution, and we compare results to a low‐resolution simulation that is ∼4° in the horizontal and ∼4 km in the vertical. We show that the main biases in the zonal mean temperature and momentum fields between the low‐ and high‐resolution simulations can be alleviated by including parameterized orographic and non‐orographic gravity waves at low resolution.

Assessment of Mangrove Cover Change Based on Combining Remote Sensing Technique and Hydrodynamic Model Simulation

Mangrove ecosystems along Vietnam's coastline face significant degradation due to human activities, despite their crucial role in coastal protection against natural hazards. This study aims to assess the spatial and temporal changes in mangrove coverage along Vietnam's southern coast by integrating remote sensing techniques with hydrodynamic model simulations. The research methodology combines the Collect Earth tool analysis of Spot-4 and Planet satellite imagery (2000-2020) with Mike 21-HD two-dimensional (2D) hydrodynamic modeling to evaluate mangrove coverage changes by simulating shoreline erosion. Results analysis reveals that a significant increase of 109.83 ha in mangrove area within Vinh Chau Town of Soc Trang Province during the period 2010-2020, predominantly in the eastern region. Hydrodynamic simulations demonstrate that the coastal zone is primarily influenced by the interaction of nearshore currents, East Sea tides, and seasonal monsoon wave patterns. The model results effectively capture the complex interactions between these hydrodynamic factors and mangrove distribution. These findings not only validate the effectiveness of combining remote sensing and hydrodynamic modeling for mangrove assessment but also provide crucial insights for sustainable coastal ecosystem management. The study's integrated approach offers a robust framework for monitoring mangrove dynamics and developing evidence-based conservation strategies, highlighting the importance of maintaining these vital ecosystems for coastal protection.

Seasonal lake‐to‐air temperature transfer functions derived from an analysis of 1395 modern lakes: A tool for reconstructing air temperature from proxy‐derived lake water temperature

AbstractLacustrine palaeotemperature reconstructions are important for characterising past temperature and hydroclimate change, validating multi‐proxy reconstructions and evaluating global climate models. In particular, lake water temperature is often derived from geochemical proxies—including clumped isotopes (Δ47), oxygen isotopes (δ18O), alkenone lipids (Uk’37) and GDGT compounds (TEX86). However, global climate models, constrained by resolution, computational demand and cost, are designed to simulate large‐scale processes, often at the expense of resolving lakes and simulating lake temperature. Consequently, this limitation complicates the comparison of climate model‐simulated variables such as air temperature, with lake water temperature or with other proxy variables (e.g. pollen‐derived air temperature), and requires the use of a transfer function to relate lake temperature to air temperature. Previous work developed transfer functions to translate proxy‐derived seasonal lake water temperature to mean annual air temperature using ground‐based measurements from 88 lakes. This study reports new lake‐to‐air temperature transfer functions (for annual, spring through summer, spring, summer and warmest month) that incorporate lake surface water temperature, and new variables including latitude and elevation, by analysing climate reanalysis data and long‐term satellite observations of surface temperatures for 1395 modern lakes via regression‐based inverse modelling. With the use of multiple regression models and a dataset roughly 10 times larger, the error in predictions of mean annual air temperature is reduced by up to 48% compared to previous work. To demonstrate the potential of the new transfer functions for integrating and comparing proxy data with model output, Pliocene and Pleistocene mean annual air temperature was reconstructed from Δ47‐derived lake temperatures and compared with model simulations for the Last Glacial Maximum and mid‐Piacenzian warm period. The new transfer functions, with reduced error, should enable more accurate palaeotemperature reconstructions from proxy‐derived lake water temperature and allow for more comprehensive assessments of climate model skill.

Sub-Daily Performance of a Convection-Permitting Model in Simulating Decade-Long Precipitation over Northwestern Türkiye

One of the main differences between regional climate model and convection-permitting model simulations is not just how well topographic characteristics are represented, but also how deep convection is treated. The convection process frequently occurs within hours, thus a sub-daily scale becomes appropriate to evaluate these changes. To do this, a series of simulations has been carried out at different spatial resolutions (0.11 and 0.025) using the COSMO-CLM (CCLM) climate model forced by the ECMWF Reanalysis v5 (ERA5) between 2011 and 2020 over a domain covering northwestern Türkiye. Hourly precipitation and heavy precipitation simulated by both models were compared with the observations by Turkish State Meteorological Service (TSMS) stations and Integrated Multi-satellitE Retrievals for GPM (IMERG). Subsequently, we aimed to identify the reasons behind these differences by computing several atmospheric stability parameters and conducting event-scale analysis using atmospheric sounding data. CCLM12 displays notable discrepancies in the timing of the diurnal cycle, exhibiting a premature shift of several hours when compared to the TSMS. CCLM2.5 offers an accurate representation of the peak times, considering all hours and especially those occurring during the wet hours of the warm season. Despite this, there is a tendency for peak intensities to be overestimated. In both seasons, intensity and extreme precipitation are highly underestimated by CCLM12 compared to IMERG. In terms of statistical metrics, the CCLM2.5 model performs better than the CCLM12 model under extreme precipitation conditions. The comparison between CCLM12 and CCLM2.5 at 12:00 UTC reveals differences in atmospheric conditions, with CCLM12 being wetter and colder in the lower troposphere but warmer at higher altitudes, overestimating low-level clouds and producing lower TTI and KI values. These conditions can promote faster air saturation in CCLM12, resulting in lower LCL and CCL, which foster the development of low-level clouds and frequent low-intensity precipitation. In contrast, the simulation of higher TTI and KI values and a steeper lapse rate in CCLM2.5 enables air parcels to enhance instability, reach the LFC more rapidly, increase EL, and finally promote deeper convection, as evidenced by higher CAPE values and intense low-frequency precipitation.

Extracting rates and activation free energies of martensitic transitions using nanomechanical force statistics: theory, models, and analysis

Nanomechanical responses (force-time profiles) of crystal lattices under deformation exhibit random critical jumps, reflecting the underlying structural transition processes. Despite extensive data collection, interpreting dynamic critical responses and their underlying mechanisms remains a significant challenge. This study explores a microscopic theoretical approach to analyse critical force fluctuations in martensitic transitions. Extensive sampling of the critical forces was performed using nonequilibrium molecular dynamics simulations of an atomic model of single-crystalline titanium nickel. We demonstrate that a framework of nonequilibrium statistical mechanics offers a principled explanation of the relationship between strain rate and the critical force distribution as well as its mean. The martensitic transition is represented on a free energy landscape, taking into account the thermally activated evolution of atomic arrangements over a barrier during its time-dependent deformation. The framework enables consistent inference of the relevant fundamental properties (e.g., intrinsic rate, activation free energy) that define the rate process of structural transition. The study demonstrates how the statistical characterisation of nanomechanical response-stimulus patterns can offer microscopic insights into the deformation behaviours of crystalline materials.

Chemical Logic of Peptide Branching by Iterative Nonlinear Nonribosomal Peptide Synthetases.

Branch-point syntheses in nonribosomal peptide assembly are rare but useful strategies to generate tripodal peptides with advantageous hexadentate iron-chelating capabilities, as seen in siderophores. However, the chemical logic underlying the peptide branching by nonribosomal peptide synthetase (NRPS) often remains complex and elusive. Here, we review the common strategies for the biosynthesis of branched nonribosomal peptides (NRPs) and present our biochemical investigation on the NRPS-catalyzed assembly of fimsbactin A, a branched mixed-ligand siderophore produced by the human pathogenic strain Acinetobacter baumannii. We untangled the unusual branching mechanism of fimsbactin A biosynthesis through a combination of bioinformatics, site-directed mutagenesis, in vitro reconstitution, molecular modeling, and molecular dynamics simulation. Our findings clarify the roles of the fimsbactin NRPS enzymes, uncovering catalytically redundant domains and identifying the multifunctional nature of the FbsF cyclization (Cy) domain. We demonstrate the dynamic interplay between l-serine and 2,3-dihydroxybenzoic acid derived dipeptides, partitioning between amide and ester forms via a 1,2-N-to-O-acyl shift orchestrated by the noncanonical, multichannel FbsF Cy domain. The branching event occurs in a secondary condensation event facilitated by this Cy domain with two dipeptidyl intermediates, which generates a branched tetrapeptide thioester. Finally, the terminal condensation domain of FbsG recruits a soluble nucleophile to release the final product. This study advances our understanding of the intricate biosynthetic pathways and chemical logic employed by NRPSs, shedding light on the mechanisms underlying the synthesis of complex branched peptides.

Dynamic Evolution and Effective Tuning of Lithium Dendrites Revealed by Phase Field Model and 2D Numerical Simulation.

Lithium dendrites are widely acknowledged as the main culprit of the degradation of performance in various Li-based batteries. Studying the mechanism of lithium dendrite formation is challenging because of the high reactivity of lithium metal. In this work, a phase field model and in situ observation experiments were used to study the growth kinetics and morphologies of lithium dendrites in terms of anisotropy, temperature, and potential difference. Subsequently, a 2D numerical simulation has been developed to illustrate the impact of microscopic parameters, such as electrolyte potential, current distribution, and anode overpotential, on the growth of lithium dendrites after nucleation. Meanwhile, the influence of electrode interface, charging rate, and charging mode on lithium dendrites was also studied using the 2D model and in situ experiments. This work provides comprehensive insights into the kinetics of dendrite formation and morphologies, offering an important theoretical reference for the safety and long-life applications of batteries.

Vertical Gradient of Nitryl Chloride and Implications for Atmospheric Photochemistry in Pearl River Delta, China, during Wintertime.

Nitryl chloride (ClNO2) is a key precursor of chlorine radicals, influencing atmospheric oxidation and secondary pollutants formation. Few studies have examined the ClNO2 chemistry from the perspective of the planetary boundary layer. Here, we conducted a vertically resolved investigation of ClNO2 at six heights (ranging from 5 to 335 m) on a 356 m tower in the Pearl River Delta, China, during winter 2021. Nocturnal ClNO2 is notably lower at the surface than the upper layers, with the nocturnal median concentration at 220 m (51 parts per trillion by volume, pptv) being approximately three times higher than that recorded in the surface layer (16 pptv). Observation-constrained box model simulations show that the NO gradients primarily account for the vertical disparities. Compared to the hydroxyl radical (OH) production via the nitrous acid and ozone photolysis, ClNO2 photolysis contributes to radical formation by 3.8% (1.8%) at 220 m (5 m) in the morning (07:00-08:00), indicates the enhanced significance of ClNO2 chemistry aloft compared with the ground, and may cause the underestimation of ClNO2 photolysis impacts if solely relying on surface measurements. We highlight that more field studies are needed to elucidate ClNO2 chemistry across the boundary layer.

A physiologically based pharmacokinetic (PBPK) model describing the kinetics of a commercial mixture α-, β-, and γ-hexabromocyclododecane exposure in mice.

Hexabromocyclododecane (HBCD) is a brominated flame retardant, that is added, but not chemically bonded, to consumer products. HBCD is sold as a commercial-grade HBCD mixture containing three major stereoisomers: alpha (α), beta (β), and gamma (γ), with relative amounts of 12% for α-HBCD, 6% for β-HBCD, and 82% for γ-HBCD. HBCDs are widely measured in the environment and in biological matrices. The toxicological effects of its exposure in humans are not clearly understood. A recent reassessment pointed out potential thyroid disruption as a primary effect. This current work aims to update a physiologically based pharmacokinetic (PBPK) model for γ-HBCD in C57BL/6 mice and incorporate equations and codes for α-HBCD and β-HBCD isomers and simulate them as a mixture. Physiological parameters were taken from the literature, calculated based on the log Kow or optimized with the dataset. The elimination of HBCDs in urine and feces was optimized to reflect the percent dose excreted, as published in the literature. Compared with data from the literature for α-HBCD, β-HBCD, and γ-HBCD in multiple tissues, the model simulations accurately described the pharmacokinetics of HBCDs in the mouse. The utility of the model was demonstrated by predicting blood concentrations from three studies in adult mice evaluating dopaminergic changes in the brain. Although this PBPK model for the mixture explicitly describes α-HBCD, β-HBCD, and γ-HBCD as individual exposures, but also as a mixture, more experimental data with commercial HBCD mixtures is still needed to improve the model.

Investigation of ion temperature in low-density undercritical foams

Abstract The ion temperature in laser-heated foam materials can be considerably higher than the electron temperature due to the internal collisions of the plasma flows originating from the heterogeneous foam microstructure. Recently, we have developed a novel hybrid multiscale model for laser-foam interaction that successfully reproduces the experimentally measured heat front propagation in laser-heated subcritical foams of various densities. However, when applied to undercritical foams with average density closer to critical, the hybrid model simulations predict an ion–electron temperature ratio much larger than in any previously reported measurements and suggest that the influence of foam microstructure is more impactful for larger average densities. For such foams, the laser-driven heat front velocity was measured many times, but the ion temperature received much less attention. To investigate the ion temperature, the laser interaction with 10 mg cm − 3 undercritical chlorine-doped TMPTA foams has been studied at the PALS facility, using an extended diagnostic complex emphasizing the x-ray time-resolved studies of the plasma wave propagation inside the foam and the distribution of macroscopic plasma parameters via high-resolution x-ray spectroscopy. The ion and electron temperatures have been measured from Doppler broadening and the relative intensity ratio of chlorine x-ray spectral lines. The averaged ion and electron temperature ratio ranges from 2 to 4 depending on the laser pulse energy. The simulations agree reasonably well with the experimental results.

Integrating ecological philosophy into ideological and political education in universities: Bridging with biomechanics for sustainable development and human health considerations

The ideological and political education (IPE) ecosystem in universities is not only an essential component of the broader educational ecosystem but also a microcosm of it. In an era that emphasizes ecology and sustainability, integrating the concepts of the biomechanics field into the ecological environment of IPE in universities holds significant practical implications. Biomechanics, a discipline dedicated to studying the mechanical behavior of organisms, has a profound impact on aspects such as the ecological environment and human health. From the perspective of ecological philosophy, the ecological environment of IPE in universities should fully consider the sustainable development of biomechanical technologies and their influence on human health. This paper presents a dynamic early warning system for IPE in universities based on an improved Support Vector Machine (SVM) algorithm. This system aims to optimize the IPE model and enhance educational effectiveness while incorporating concepts related to biomechanics. We have constructed an evaluation index system for the quality of IPE in universities across five dimensions: basic quality, teaching attitude, teaching method, teaching ability, and teaching effect. These indicators are evaluated through expert scoring to generate a comprehensive assessment of the teaching quality of IPE. Taking into account the close connection between human mechanical responses and the ecological environment in the field of biomechanics, during the evaluation process, we incorporate the impact of the ecological environment on the human biomechanical state (such as bone development and muscle function) into consideration. This approach guides students to establish a correct ecological view and understanding of biomechanical technologies. Model simulations and performance verifications show that the fuzzy neural network undergoes 779 training iterations, with a training target set at 0.05 and a learning rate of 0.09. This model demonstrates a strong ability to provide comprehensive dynamic early warnings for IPE in universities. It has obvious advantages in adaptability, model fitting accuracy, and processing efficiency in the face of information overload, contributing to the continuous development of IPE in universities from the integrated perspective of ecological philosophy and biomechanics.

Effects of Base Course Restraint on Early Age Transverse Cracking in CRCP

Asphalt Interlayer (AIL) is planning to be inserted between a concrete slab and base course in continuously reinforced concrete pavement (CRCP) in a super express highway in Japan. In this study, the effects of AIL are investigated based on observations and measurements on a test CRCP and simulations with three dimensional finite element method (3DFEM). The test pavement has two sections with and without AIL and strains and temperatures in the slab were measured. Investigation of the test pavement revealed that air temperature at the time of concrete casting affected the strains in the slab and crack pattern. Also, three closely spaced cracks were observed in the AIL section. To examine how AIL affects cracking situations, numerical simulations were conducted using a 3DFE model that was developed in this study. The model employs an incremental algorithm to consider changes of free contraction strain (FCS) and material properties of concrete at the early age. Mechanical interaction between steel and concrete was modeled with three nonlinear springs. The model was validated by simulating early age cracking of the slab and comparing the predicted strains and the strains measured in the test pavement. Effects of AIL on spacing and width of transverse crack were investigated with the model. The simulations of the 3DFE model revealed that the crack spacing does not change by using AIL, while AIL narrows the crack width. It was found that a small peak in tensile stress on the top of the slab near the crack appears in the AIL section, which might cause “secondary” crack near “primary” crack. The peak disappears after the secondary crack occurs near the primary crack, resulting in a cluster cracking observed in the test pavement.

Identification of potent TMPRSS4 inhibitors through structural modeling and molecular dynamics simulations

TMPRSS4, a transmembrane serine protease type II, is associated with various pathological illnesses. It has been found to activate SARS-CoV-2, enhance viral infection of human small-intestinal enterocytes and is overexpressed in different types of cancers. Therefore, this study aims to disover potential TMPRSS4 inhibitors that have better binding affinity than the approved inhibitors: 2-hydroxydiarylamide and tyroserleutide. Since no 3D-structure is known for TMPRSS4, structural models for the TMPRSS4 serine protease domain were developed. The modeled structures were validated and subjected to molecular dynamics simulations. FDA-approved, clinical/preclinical drugs and natural products were docked to the pocket of TMPRSS4. Moreover, through a systematic analysis, MD simulations and MM-GBSA binding free energy calculations revealed that the best candidates Ergotamine, S55746, NPC478048, Lifirafenib, and NPC77101 are highly stable drug candidates in complex with TMPRSS4, displaying low RMSD and RMSF values with strong binding stability. Among these compounds, Ergotamine showed the most favorable binding energy (-33.73 kcal/mol). Overall, our in silico results revealed that these compounds could act as potent TMPRSS4 inhibitors and need to be validated by future experimental studies.