Deposition Model Research Articles

Deep learning modeling of RNA ac4C deposition reveals the importance of plant alternative splicing.

The N4-acetylcytidine (ac4C) modification has recently been characterized as a noncanonical RNA marker in plants. While the precise installation of ac4C sites in individual plant transcripts continues to present challenges, the biological roles of ac4C in specific plant species are gradually being deciphered. Herein, we utilized a deep learning technique called iac4C (intelligent ac4C) to predict ac4C sites in mRNA. ac4C deposition was effectively forecasted by the iac4C model (AUROC = 0.948), revealing a reliable distribution pattern primarily situated in the transcribing area as opposed to regions that are not translated. The iac4C deep learning approach using a combination of BiGRU and self-attention mechanisms both validates previous studies showing a positive correlation between ac4C and RNA splicing in plant species and reveals new examples of other splicing events associated with ac4C. Our advanced deep learning algorithm for analyzing ac4C enables swift identification of important biological phenomena that would otherwise be challenging to uncover through traditional experimental approaches. These findings provide insight into the essential regulatory function of site-specific ac4C deposition in alternative splicing processes. The source code and datasets for iac4C are available at https://github.com/xlwei507/iac4C .

A computational modeling of airflow and radon progeny deposition in human respiratory system

A computational modeling of airflow and radon progeny deposition in human respiratory system

Characterisation of surface morphology of high voltage DC relay contacts under arc erosion

Abstract High voltage DC relays are a crucial component in new energy vehicles. Due to the high failure rate caused by contact sticking (fusion welding), existing technologies can only analyze contact morphology after failure. There is an urgent need to determine the quantitative characterization value of contact surface morphology and the correlation between morphology, failure mechanisms, and working conditions. In this study, an Olympus DSX1000 microscope is used to extract surface topography data, and a quantitative topography characterization method based on a machine vision system is proposed to quantitatively analyze contact surface changes after arc erosion. Grey correlation analysis was applied to explore the relationship between electrical parameters such as voltage, current, and capacitance, and the contact morphology features. The results show that current and capacitance have the greatest influence on contact surface features after arc erosion, while voltage has a relatively smaller influence. This conclusion is consistent with the experimentally observed arc erosion features. Finally, an arc ion sputtering deposition model was developed to analyze the material transfer mode and its influence on the contact failure mechanism. The results provide a scientific basis for the analysis and design improvement of high voltage DC relays.

A comparative analysis of an aerosol dry deposition microscale model for overhead powerlines insulators

Aerosol particles deposition on overhead power line insulators may significantly threaten electric systems, affecting dielectric properties and potentially causing surface discharges and service interruptions, leading to economic consequences. This study addresses this challenge by evaluating a dedicated microscale deposition model that integrated into an advanced air quality (AQ) modeling system. The microscale model integration into the AQ system aims to improve predictions of equivalent salt deposit density (ESDD), a key measure of insulator contamination. This enhancement is crucial for improving system resilience and reliability. The microscale model’s performance in reconstructing particulate matter (PM) deposition fluxes onto XP-70 porcelain-disk electrical insulator is assessed against measured ESDD data collected across various regions in Italy during several experimental campaigns. In order to better understand the specific phenomena impacting PM deposition, the microscale model is compared to the state-of-the-art Zhang deposition model used in CAMx. The analysis reveals that the microscale model tends to overestimate measured ESDD values and predicts higher deposition velocities than the Zhang model. These results suggest potential modelling differences between the two models, including variations in obstacle parameterizations, influence of particle aerodynamics, and dispersion modelling in the near-wall region.

Calcium Carbonate Deposition Model Supporting Multiple Operating Conditions Based on the Phase-Field Method for Free-Surface Flows

The drainage systems of tunnels situated in limestone regions frequently encounter crystallization blockages. Numerous studies have addressed this issue, and their findings identified factors such as the flow velocity and temperature as influencing the crystallization process. However, these studies could not predict the occurrence of crystallization. Regarding theoretical approaches, most studies have focused on full-pipe operations or have solely considered flow-field dynamics without including simulations of the chemical reactions and mass transfers. This study introduces a mass-transfer model for drainage pipes based on a two-phase flow (water and air) with a free surface and non-full pipe flow that simulates the crystallization deposition process in drainage pipes. This model can predict the deposition conditions at varying flow velocities and intuitively visualize the crystallization process under the influence of various factors. The impact of flow velocity on the overall crystallization deposition process can be directly analyzed through simulations developed using this model. The results show that under conditions of incomplete pipe flow with no pressure at the outlet, the weight of the deposition first increases and then decreases within a certain velocity. This model can depict the variations within a 30 d period.

Discrete element model of nanoparticle deposition during electrospraying

Electrospraying is a technique for the production and deposition of nanoparticles. However, deposited layer morphology is strongly dependent on the operating conditions and hard to predict. Here, we present a spatially 3D model based on the Discrete Element Method (DEM) with the analytical evaluation of interparticle forces and drag force and the numerical evaluation of electric force. The developed connection between mesh-free DEM and mesh-based Finite Volume Method (FVM) used for the evaluation of electric potential field enables to lower the computational time while maintaining accuracy of the predictions We focus on modelling the influence of interparticle forces on particle deposition and deposited layer morphology, which are phenomena usually neglected in the literature so far. Preferential landing of particles is indicated to be a consequence of both electric force and Van der Waals forces. Contact particle interactions allow particle stacking (creating thus fractal-like structure) or allow falling down of particles and their rearrangement (leading to compact layers).

Numerical modeling of particle deposition in a realistic respiratory airway using CFD-DPM and genetic algorithm.

In this study, a realistic model of the respiratory tract obtained from CT medical images was used to solve the flow field and particle motion using the Eulerian-Lagrangian approach to obtain the maximum particle deposition in the bronchial tree for the main purpose of optimizing the performance of drug delivery devices. The effects of different parameters, including particle diameter, particle shape factor, and air velocity, on the airflow field and particle deposition pattern in different zones of the lung were investigated. In addition, a genetic algorithm was employed to obtain the maximum particle deposition in the bronchial tree and the effect of the aforementioned parameters on particle deposition. Reverse flow, vortex formation, and laryngeal jet all affect the airflow structure and particle deposition pattern. The mouth-throat region had the highest deposition fraction at various flow rates. A change in the deposition pattern with an increased deposition fraction in the throat was observed owing to the increased diameter and shape factor of the particles, resulting from the higher inertia and drag force, respectively. The particle deposition analysis showed that three parameters, shape factor, diameter, and velocity, are directly related to particle deposition, and the diameter is the most effective parameter for particle deposition, with an effect of 60% compared to the shape factor and velocity. Finally, the prediction of the genetic algorithm reported a maximum particle deposition in the bronchial tree of 17%, whereas, based on the numerical results, the maximum particle deposition was reported to be 16%. Therefore, there is a 1% difference between the prediction of the genetic algorithm and the numerical results, which indicates the high accuracy of the prediction of the genetic algorithm.

Puerarin alleviates apoptosis and inflammation in kidney stone cells via the PI3K/AKT pathway: Network pharmacology and experimental verification.

Puerarin(PUE), an isoflavonoid extracted from Pueraria root, has anti-apoptotic effects. The objective of this research is to examine the impact of PUE on renal apoptosis and inflammation resulting from renal calculi and to elucidate its mechanism. The approach of network pharmacology and molecular docking was employed to discover potential targets and pathways of PUE. An animal model of calcium oxalate crystal deposition by intraperitoneal injection of glyoxylate and a model of COM-induced human renal tubular epithelial cells (HK2) were used to investigate the pharmacological mechanisms of PUE against apoptosis and inflammation. We used haematoxylin-eosin (H&E) and Periodic Acid-Schiff staining (PAS) to assess the effect of PUE on crystal deposition and damage. The mechanism of PUE was elucidated and validated using Western blotting, histology and immunohistochemical staining. Network pharmacology findings indicated that the PI3K/AKT pathway plays a crucial role in PUE. We experimentally demonstrate that PUE alleviated COM-induced changes in apoptotic proteins, increased inflammatory indicators and changes in oxidative stress-related indicators in HK2 cells by activating the PI3K/AKT pathway, reduced serum creatinine and urea nitrogen levels in mice caused by CaOx, alleviated crystal deposition and damage, and alleviated apoptosis, oxidative stress and inflammation. Puerarin attenuates renal apoptosis and inflammation caused by kidney stones through the PI3K/AKT pathway.

Analytical temperature model for spindle speed selection in additive friction stir deposition

This paper describes a physics-based, analytical model for additive friction stir deposition (AFSD) spindle speed selection to achieve a desired deposition temperature. In the model, power input to the feedstock, which enables plastic flow and deposition, is related to the material temperature rise and subsequent flow stress reduction using Fourier’s conduction rate equation. Power input is modeled as frictional heating at the deposit-surface interface and adiabatic heating due to plastic deformation. The flow stress is predicted using the strain, strain rate, and temperature-dependent Johnson-Cook constitutive model for the selected feedstock alloy. Model predictions are compared to AFSD numerical simulation results available in the literature and experiments for aluminum alloys.

Element Formation in Radiation-hydrodynamics Simulations of Kilonovae

Understanding the details of r-process nucleosynthesis in binary neutron star merger (BNSM) ejecta is key to interpreting kilonova observations and identifying the role of BNSMs in the origin of heavy elements. We present a self-consistent, two-dimensional, ray-by-ray radiation-hydrodynamic evolution of BNSM ejecta with an online nuclear network (NN) up to a timescale of days. For the first time, an initial numerical relativity ejecta profile composed of the dynamical component and spiral-wave and disk winds is evolved including detailed r-process reactions and nuclear heating effects. A simple model for the jet energy deposition is also included. Our simulation highlights that the common approach of relating in postprocessing the final nucleosynthesis yields to the initial thermodynamic profile of the ejecta can lead to inaccurate predictions. Moreover, we find that neglecting the details of the radiation-hydrodynamic evolution of the ejecta in nuclear calculations can introduce deviations of up to 1 order of magnitude in the final abundances of several elements, including very light and second r-process peak elements. The presence of a jet affects element production only in the innermost part of the polar ejecta, and it does not alter the global nucleosynthesis results. Overall, our analysis shows that employing an online NN improves the reliability of nucleosynthesis and kilonova light-curve predictions.

In Situ-Constructed Multifunctional Composite Anode with Ultralong-Life Toward Advanced Lithium-Metal Batteries.

Metallic lithium is the most competitive anode material for next-generation high-energy batteries. Nevertheless, the extensive volume expansion and uncontrolled Li dendrite growth of lithium metal not only cause potential safety hazards but also lead to low Coulombic efficiency and inferior cycling lifespan for Li metal batteries. Herein, a multifunctional dendrite-free composite anode (Li/SnS2) is proposed through an in situ melt-infusion strategy. In this configuration, the 3D cross-linked porous Li2S/Li22Sn5 framework facilitates the rapid penetration of electrolytes and accommodates the volume expansion during the repeated Li-plating process. Meanwhile, the lithiophilic Li2S phases with a low Li+ transport barrier ensure preferential Li deposition, effectively avoiding uneven electron distribution. Moreover, the Li22Sn5 electron conductors with appropriate Li+ bonding ability guarantee rapid charge transport and mass transfer. Most importantly, the steady multifunctional skeleton with sufficient inner interfaces (Li2S/Li22Sn5) in the whole electrode, not only realizes the redistribution of the localized free electron, contributing to the decomposition of Li clusters, but also induces a planar deposition model, thus restraining the generation of Li dendrites. Consequently, an unprecedented cyclability of over 6500h under an ultrahigh areal capacity of 10mAhcm-2 and a current rate of 20mAcm-2 is achieved for the prepared Li2S/Li22Sn5 composite anode. Moreover, the assembled Li/SnS2||LiFePO4 (LFP) pouch full-cells also demonstrate remarkable rate capability and a convincing cycling lifespan of more than 2000 cycles at 2 C.

Characterization of pediatric extrathoracic aerosol deposition with air-jet dry powder inhalers

The use of air-jet dry powder inhalers (DPIs) offers a number of advantages for the administration of pharmaceutical aerosols, including the ability to achieve highly efficient and potentially targeted aerosol delivery to the lungs of children using the oral or trans-nasal routes of administration. To better plan targeted lung delivery of pharmaceutical aerosols with these inhalers, more information is needed on the extrathoracic (ET) depositional loss in pediatric subjects when using relatively small (e.g., 0.5–2 μm) particles and including oral or nasal device interfaces. The objective of this study was to implement validated computational fluid dynamics (CFD) models to characterize ET depositional loss during mouth-throat (MT) and nose-throat (NT) aerosol administration to pediatric subjects (2–10 years old) using an air-jet DPI platform across a range of initial small-particle aerosol sizes (0.41–13.65 μm) and inhalation flow rates (8–20 L/min).A new CFD model focused on small-particle aerosol depositional loss in existing pediatric airway models was developed and validated with existing in vitro data. The validated CFD model was then used to characterize depositional loss in the MT and NT regions of children using particle sizes, flow rates and interfaces consistent with air-jet DPIs.Successful validation of the CFD model for small-particle aerosol deposition was achieved through enhanced resolution of the near-wall transport conditions. Existing non-dimensional parameters were used to produce high quality single-curve deposition efficiency correlations with r2 values in the range of 0.95–0.97. A new method for predicting realistic polydisperse aerosol deposition using the developed correlations and an equivalent monodisperse particle diameter was also introduced. In conclusion, the newly developed correlations will be useful in planning the lung delivery of next-generation inhaled medications, where achieving both low ET loss and targeted airway deposition, perhaps with excipient enhanced growth technology, are critical factors.

The molecular regulated mechanism of METTL3 and FTO in lipid metabolism of Hu sheep

BackgroundBalanced lipid metabolism can improve the growth performance and meat quality of livestock. The m6A methylation-related genes METTL3 and FTO play important roles in animal lipid metabolism; however, the mechanism through which they regulate lipid metabolism in sheep is unclear. ResultsWe established lipid deposition models of hepatocytes and preadipocytes in Hu sheep. In the hepatocyte lipid deposition model, the genes expression levels of FABP4, Accα, ATGL and METTL3, METTL14, and FTO—were significantly up-regulated after lipid deposition (P < 0.05). Transcriptomic and metabolomic analyses showed that lipid deposition had a significant effect on MAPK, steroid biosynthesis, and glycerophospholipid metabolism pathway in hepatocytes. The m6A methylation level decreased but the difference was not significant after METTL3 interference, and the expression levels of FABP4 and ATGL increased significantly (P < 0.05); the m6A methylation level significantly increased following METTL3 overexpression, and LPL and ATGL expression levels significantly decreased (P < 0.05), indicating that overexpression of METTL3 inhibited the expression of lipid deposition-related genes in a m6A-dependent manner. The m6A methylation level was significantly increased, ATGL expression was significantly decreased (P < 0.05), and LPL, FABP4, and Accα expression was not significantly changed following FTO interference (P > 0.05); the m6A methylation level was significantly decreased after FTO overexpression, and LPL, FABP4, and ATGL expression was significantly increased (P < 0.05), indicating that FTO overexpression increased the expression of lipid deposition-related genes in a m6A-dependent manner. Transcriptomic and metabolomic analyses showed that m6A methylation modification mainly regulated lipid metabolism through triglyceride metabolism, adipocytokine signaling, MAPK signaling, and fat digestion and absorption in hepatocytes. In the lipid deposition model of preadipocytes, the regulation of gene expression is the same as that in hepatocytes. ConclusionsMETTL3 significantly inhibited the expression of lipid deposition-related genes, whereas FTO overexpression promoted lipid deposition. Our study provides a theoretical basis and reference for accurately regulating animal lipid deposition by mastering METTL3 and FTO genes to promote high-quality animal husbandry.

Phase-field modeling of lithium dendrite deposition process: When an internal short circuit occurs

Lithium dendrite growth is the main trigger for internal short circuits (ISC) of lithium-ion batteries. This paper investigates the lithium dendrite growth during the whole short circuit evolution process. In this paper, the lithium dendrite growth is divided into the initial deposition of the initial operation and the secondary deposition due to the internal short circuit. Firstly, a two-dimensional model based on the phase-field theory is developed and the growth in static electrolyte is investigated. Secondly, we summarize the whole evolution process and analyze the internal structural changes as well as the external features due to the internal short circuit. Based on this analysis, a model of secondary deposition in a flowing electrolyte is proposed. The model takes into account the effect of the flowing electrolyte on the dendrites. Finally, we investigate the growth of dendrites during secondary deposition. Due to an internal short circuit that damages the separator, a flowing electrolyte appears around the damaged region. This flowing electrolyte leads to uneven growth of dendrites, with “splitting” and “branch inhibition”. This phenomenon will accelerate the continued deposition of dendrites and induce a secondary internal short circuit. This work provides a quantitative simulation model for dendrite growth when an ISC occurs. Moreover, it also provides a reference for designing the structure of liquid batteries with high cycle times and safety.

High-temperature deposition model for molten particle prediction based on droplet-surface interaction criteria

Particle deposition in gas turbine engines damages blade surfaces and diminishes engine performance. Deposition results from heat and momentum exchanges between fluid and particles, coupled with the interactions between particles and surfaces. The increasing turbine inlet temperatures cause particles to become molten, complicating their interaction with surfaces. Existing models fail to convincingly explain the deposition behaviors of molten particles. In the present study, considering particle fluidity and the nonlinear accumulation of deposits, the deposition criteria for viscous droplets and the maximum steady deposit layer model were incorporated to establish an unsteady high-temperature deposition model. The new model, validated against experiment results in the literatures, predicts molten particle deposition behavior with an average error of 3.89 % in capture efficiency at high-temperature conditions. It accurately predicts crown-like deposit morphology and nonlinear accumulation, matching experimental observations. Applied to nozzle guide vanes with film cooling, results show that deposits primarily occur on the leading edge and pressure side near the trailing edge. The particle capture efficiency initially rises before diminishing as particle size increases, whereas an inverse trend is noted with the escalation of the mass flow ratio. At a mass flow ratio of 0.15, the capture efficiency hits the minimum of about 13.2 %.

Numerical model of asphaltene deposition in vertical wellbores: Considerations of particle shape and drag force

Asphaltene deposition and plugging are common phenomena during crude oil production, significantly reducing production efficiency. Understanding the deposition behavior of asphaltene particles in vertical wellbores, particularly in relation to drag force interactions and settlement velocity, is imperative to mitigate these issues. Existing empirical models often fail due to their inherent inaccuracies and neglect of asphaltene particles' irregular shapes. This work established a quantitative method to describe irregular geometries of asphaltene particles. Shape coefficient, ∅, and shape coefficient influence factor, θ, are used to assess the impact of particle shape on the drag force coefficient and settling velocity. Experimental results from sedimentation experiments reveal particles with smaller shape coefficients encounter greater flow resistance and higher drag force coefficients. Moreover, the impact of shape coefficient on the drag coefficient gradually decreases as the Reynolds number increases. Based on these experimental findings, distinct models for the drag force coefficient and settling velocity of asphaltene particles are established, achieving a reduction in average error ranging between 2 % ∼ 25 % compared to existing models.

JIRAM Observations of Volcanic Flux on Io: Distribution and Comparison to Tidal Heat Flow Models

AbstractJuno has allowed clear, high‐resolution imaging of Io's polar volcanoes using the Jovian Infrared Auroral Mapper (JIRAM) instrument. We have used data from JIRAM's M‐band (4.78 μm) imager from 11 Juno orbits to construct a global map of volcanic flux. This map provides short‐term insight into the spatial distribution of volcanoes and the ways in which high‐ and low‐latitude volcanoes differ. Using spherical harmonic analysis, we quantitatively compare our volcanic flux map to the surface heat flow distribution expected from models of Io's tidal heat deposition (summarized in de Kleer, Park, et al. (2019, https://doi.org/10.26206/d4wc‐6v82). Our observations confirm previously detected systems of bright volcanoes at high latitudes. Our study finds that both poles are comparably active and that the observed flux distribution is inconsistent with an asthenospheric heating model, although the south pole is viewed too infrequently to establish reliable trends.

What sizes of droplets contribute to long-range airborne transmission?

The size range of respiratory droplets contributing to long-range airborne transmission of infections determines the targeted intervention methods. However, the exact size range remains unknown, and the influencing parameters are also undetermined. Here, we investigated the size-resolved transport and fate of respiratory droplets in four reported venues of COVID-19 outbreaks. We utilised a transient number balance model, a set of expired droplet size distributions, existing formulas for size-resolved settling rates and filtration efficiencies, and a deposition model from the International Commission on Radiological Protection. This enabled us to obtain the size-resolved concentrations of exhaled droplets in indoor air, the size-resolved number of droplet nuclei in the inhaled air, and the number of droplets deposited throughout the respiratory tract. The newly defined airborne transmission size range of expired droplets depends on the effective dilution flow rate of the infection venue under consideration. Three criteria were proposed for determining the sizes of droplets involved in long-range airborne transmission. The airborne transmission droplets typically featured an initial diameter of 0.1–4–6 µm, with an hourly volume generation rate of 0.38–0.42 nL/h per index case in the four venues. This newly estimated volume of airborne transmission droplets provides an essential input into the viral load method for estimating the infectious quanta generation rate. Practical significanceOur size-resolved estimation reveals that only a tiny fraction of expired infectious droplets within an airborne transmission size range survives after the removal effects of ventilation, settling, deactivation, and filtration, as well as the transient dilution effect. These droplets remain in indoor air, potentially contributing to long-range airborne transmission. The airborne transmission size range depends on the size-dependent dilution capacity of a room.

Ballistic deposition with memory: A new universality class of surface growth with a new scaling law

Motivated by recent experimental studies in microbiology, we suggest modifying the classic ballistic deposition model of surface growth, where the memory of a deposition at a site induces more depositions at that site or its neighbors. By studying the statistics of surfaces in this model, we obtain three independent critical exponents: the growth exponent β=5/4, the roughening exponent α=2, and the new (size) exponent γ=1/2. The model requires modifying the Family-Vicsek scaling, resulting in the dynamical exponent z=α+γβ=2. This modified scaling collapses the surface width vs time curves for various lattice sizes. This previously unobserved universality class of surface growth could describe the surface properties of a wide range of natural systems. Published by the American Physical Society 2024

CFD-PK model for nasal suspension sprays: Validation with human adult in vivo data for triamcinolone acetonide

The objectives of this study were to expand and implement a Computational Fluid Dynamics (CFD)-Dissolution, Absorption and Clearance (DAC)-Pharmacokinetics (PK) multi-physics modeling framework for simulating the transport of suspension-based nasal corticosteroid sprays. The mean CFD-predicted peak plasma concentration (Cmax) and area under the curve (AUC) of the plasma concentration–time profile, based on three representative nasal airway models (capturing low, medium and high posterior spray deposition), were within one standard deviation of available in vivo PK data for a representative corticosteroid drug (triamcinolone acetonide). The relative differences in mean Cmax between predictions and in vivo data for low dose (110 µg) and high dose (220 µg) cases were 27.8% and 10.1%, respectively. The models confirmed the dose-dependent dissolution-limited behavior of nasally delivered triamcinolone acetonide observed in available in vivo data. The total uptake from the nasal cavity decreased from 68.3% to 51.3% for the medium deposition model as dose was increased from 110 to 220 µg due to concentration-limited dissolution. The modeling framework is envisioned to facilitate faster development and testing of generic locally acting suspension nasal spray products due to its ability to predict the impact of differences in spray characteristics and patient use parameters on systemic PK.