Simulation Approach Research Articles

DNA-damage RBE assessment for combined boron and gadolinium neutron capture therapy.

Neutron capture therapy (NCT) by 10B and 157Gd agents is a unique irradiation-based method which can be used to treat brain tumors. Current study aims to quantitatively evaluate the relative biological effectiveness (RBE) and dose distributions during the combined BNCT and GdNCT modalities through a hybrid Monte Carlo (MC) simulation approach. Snyder head phantom as well as a cubic hypothetical tumor was at first modeled by Geant4 MC Code. Then, the energy spectra and dose distribution relevant to the released secondary particles during the combined Gd/BNCT were scored for different concentrations of 157Gd and 10B inside tumor volume. Finally, the scored energy spectra were imported to the MCDS code to estimate both RBESSB and RBEDSB values for different 157Gd concentrations. The results showed that combined Gd/BNCT increases the fluence-averaged RBESSB values by about 1.7 times when 157Gd concentration increments from 0 to 2000µg/g for both considered cell oxygen levels (pO2=10% and 100%). Besides, a reduction of about 26% was found for fluence-averaged RBEDSB values with an increment of 157Gd concentration in tumor volume. From the results, it can be concluded that combined Gd/BNCT technique can improve tumor coverage with higher dose levels but in the expense of RBEDSB reduction which can affect the clinical efficacy of the NCT technique.

Molecular modeling and simulation approaches to characterize potential molecular targets for burdock inulin to instigate protection against autoimmune diseases.

In the current study, we utilized molecular modeling and simulation approaches to define putative potential molecular targets for Burdock Inulin, including inflammatory proteins such as iNOS, COX-2, TNF-alpha, IL-6, and IL-1β. Molecular docking results revealed potential interactions and good binding affinity for these targets; however, IL-1β, COX-2, and iNOS were identified as the best targets for Inulin. Molecular simulation-based stability assessment demonstrated that inulin could primarily target iNOS and may also supplementarily target COX-2 and IL-1β during DSS-induced colitis to reduce the role of these inflammatory mechanisms. Furthermore, residual flexibility, hydrogen bonding, and structural packing were reported with uniform trajectories, showing no significant perturbation throughout the simulation. The protein motions within the simulation trajectories were clustered using principal component analysis (PCA). The IL-1β-Inulin complex, approximately 70% of the total motion was attributed to the first three eigenvectors, while the remaining motion was contributed by the remaining eigenvectors. In contrast, for the COX2-Inulin complex, 75% of the total motion was attributed to the eigenvectors. Furthermore, in the iNOS-Inulin complex, the first three eigenvectors contributed to 60% of the total motion. Furthermore, the iNOS-Inulin complex contributed 60% to the total motion through the first three eigenvectors. To explore thermodynamically favorable changes upon mutation, motion mode analysis was carried out. The Free Energy Landscape (FEL) results demonstrated that the IL-1β-Inulin achieved a single conformation with the lowest energy, while COX2-Inulin and iNOS-Inulin exhibited two lowest-energy conformations each. IL-1β-Inulin and COX2-Inulin displayed total binding free energies of - 27.76kcal/mol and - 37.78kcal/mol, respectively, while iNOS-Inulin demonstrated the best binding free energy results at - 45.89kcal/mol. This indicates a stronger pharmacological potential of iNOS than the other two complexes. Thus, further experiments are needed to use inulin to target iNOS and reduce DSS-induced colitis and other autoimmune diseases.

A Simulation Approach to Determine Dynamic Rollover Threshold of a Tractor Semi-Trailer Vehicle during Turning Maneuvers

A Simulation Approach to Determine Dynamic Rollover Threshold of a Tractor Semi-Trailer Vehicle during Turning Maneuvers

Evaluation of plastic injection molding for PA6/ABS/CaCO3 nanocomposites using Taguchi method and Moldflow simulation approach

Nowadays, nanocomposites are widely used in the industry. Polymer nanocomposites are widely used in the automotive industry because they have very favorable properties. These properties, including mechanical, electrical, and thermal characteristics, change depending on the combination of materials used in composite synthesis. In this paper, the injection molding of an automobile part called a control arm protector is investigated. Since warpage and shrinkage are general and important challenges in injection molded parts, Taguchi test design and Autodesk Moldflow® simulation approach are used to find the best injection condition for the mentioned part. To perform this, PA6/ABS polymer composite combined with nano CaCO3 is used. Three main injection molding process parameters, including melt temperature, mold temperature, and injection pressure, as well as nano CaCO3 amount, are evaluated. Moreover, analysis of the gate location is investigated. In the following, an analysis of variance is conducted to identify the significant parameters. Regression correlations were also established. Finally, optimization of the process is carried out by the desirability method.

Zuranolone Concentrations in the Breast Milk of Healthy, Lactating Individuals: Results From a Phase 1 Open-Label Study.

Zuranolone is a positive allosteric modulator of both synaptic and extrasynaptic γ-aminobutyric acid type A receptors and a neuroactive steroid approved as an oral, once-daily, 14-day treatment course for adults with postpartum depression in the United States. This study assessed zuranolone transfer into breast milk. Healthy, nonpregnant, lactating adult female participants received once-daily 30 mg zuranolone from day (D)1 through D5 in this phase 1 open-label study. The relative infant dose (RID; weight-adjusted proportion of the maternal dose in breast milk over 24 hours) for 30 mg zuranolone was assessed at D5. An RID for 50 mg zuranolone was estimated using a simulation approach across a range of infant ages and weights. Of 15 enrolled participants (mean age, 30.1 years), 14 completed the study. The mean RID for 30 mg zuranolone at D5 was 0.357%; the mean steady-state milk volume over D3 to D5 decreased from baseline by 8.3%. Overall unbound zuranolone in plasma was low (≤0.49%). Plasma concentrations peaked at D5 before decreasing in a biexponential manner. There was strong concordance between the temporal evolution of zuranolone concentrations in plasma and breast milk. The estimated mean RID for 50 mg zuranolone based on a milk intake of 200 mL/kg per day was 0.984%. All treatment-emergent adverse events reported by participants were mild, the most common being dizziness (n = 3). Zuranolone transfer into the breast milk of healthy, nonpregnant, lactating adult female participants was low; the estimated RID for 50 mg zuranolone was <1%, well below the <10% threshold generally considered compatible with breastfeeding.

Effect of Particle Size on Optical and Electrical Properties of Thin Films – A Simulation Approach

Abstract This work presents a simulated investigation of the relationship between surface roughness and particle size as well as the resulting impact on the thin film's physical, optical, and electrical properties. Non-porous thin films are created through computer simulation for a range of particle sizes. Random deposition with a surface relaxation technique is used for the generation of non-porous thin films. The fundamental data of two well-known materials, ZnO and CdSe, were used for the theoretical calculation of different parameters like bandgap, absorption coefficient, refractive index, dielectric constant conductivity, or others. It is also shown that the pre-assumed values of all these parameters are well matched with the experimental results reported by different groups. This is probably the first effort to develop a direct relation between the particle size with different fundamental optical or electrical properties of different materials. This would definitely help the experimental researchers in the field of material science to design their experiments as per the desired requirements.&amp;#xD;&amp;#xD;

Phase segregation and nanoconfined fluid O2 in a lithium-rich oxide cathode.

Lithium-rich oxide cathodes lose energy density during cycling due to atomic disordering and nanoscale structural rearrangements, which are both challenging to characterize. Here we resolve the kinetics and thermodynamics of these processes in an exemplar layered Li-rich (Li1.2-xMn0.8O2) cathode using a combined approach of ab initio molecular dynamics and cluster expansion-based Monte Carlo simulations. We identify a kinetically accessible and thermodynamically favourable mechanism to form O2 molecules in the bulk, involving Mn migration and driven by interlayer oxygen dimerization. At the top of charge, the bulk structure locally phase segregates into MnO2-rich regions and Mn-deficient nanovoids, which contain O2 molecules as a nanoconfined fluid. These nanovoids are connected in a percolating network, potentially allowing long-range oxygen transport and linking bulk O2 formation to surface O2 loss. These insights highlight the importance of developing strategies to kinetically stabilize the bulk structure of Li-rich O-redox cathodes to maintain their high energy densities.

A novel metric learning method based on constructing a uniform data hypersphere via simulated forging approach

A novel metric learning method based on constructing a uniform data hypersphere via simulated forging approach

Energetics of the Transmembrane Peptide Sorting by Hydrophobic Mismatch.

Hydrophobic mismatch between a lipid membrane and embedded transmembrane peptides or proteins plays a role in their lateral localization and function. Earlier studies have resolved numerous mechanisms through which the peptides and membrane proteins adapt to mismatch, yet the energetics of lateral sorting due to hydrophobic mismatch have remained elusive due to the lack of suitable computational or experimental protocols. Here, we pioneer a molecular dynamics simulation approach to study the sorting of peptides along a membrane thickness gradient. Peptides of different lengths tilt and diffuse along the membrane to eliminate mismatch with a rate directly proportional to the magnitude of mismatch. We extract the 2-dimensional free energy profiles as a function of local thickness and peptide orientation, revealing the relative contributions of sorting and tilting, and suggesting their thermally accessible regimes. Our approach can readily be applied to study other membrane systems of biological interest where hydrophobic mismatch, or membrane thickness in general, plays a role.

Improving instrumental neutron activation analysis detection limit using Monte Carlo simulation for lanthanides determination in Algerian phosphate

ABSTRACT Instrumental Neutron Activation Analysis (INAA) is one of the best methods to analyse Rare Earth Elements (REE) with a low detection limit in phosphate samples. Since most lanthanides emit gamma rays at the energy below 1000 keV, this energy range is affected by the Bremsstrahlung noise of beta emission produced by the 31P(n,γ)32P reaction, when the irradiation of the P2O5 composing the phosphate matrix (approximately 30%). This beta (β−) spectrum with a maximum energy of 1.71 MeV (average energy of 695 keV) affects the gamma spectrum and will reduce the detection limit significantly, other factors decrease the detection limit of lanthanides like neutron self-shielding and interference. In the present work, an analysis methodology based on optimising the measurement parameters of the INAA technique was implemented to improve the detection limits for the precise evaluation of lanthanide concentrations in Algerian phosphate deposits. The complete procedure was developed using a combination of a Monte Carlo simulation approach and experimental measurements. Two models were developed based on Monte Carlo simulation for the calibration of HPGe detector efficiency and the optimisation of type and filter thickness to reduce the beta spectrum (Bremsstrahlung) emitted by the 32P produced by neutron capture reaction 31P(n, γ) 32P. The developed model allowed a considerable improvement in the detection limit of the INAA technique and reduced the uncertainty in the lanthanide concentration. Finally, the methodology was applied to determine lanthanide elements in phosphate samples with good precision.

Disulfide/α-Amide-Bridged Doxorubicin Dimeric Prodrug: Effect of Aggregation Structures on pH/GSH Dual-Triggered Drug Release.

Disulfide bonding has attracted intense interest in the tumor intracellular microenvironment-activated drug delivery systems (DDSs) in the last decades. Although various molecular structures of redox-responsive disulfide-containing DDSs have been developed, no investigation was reported on the effect of aggregation structures. Here, the effect of aggregation structures on pH/GSH dual-triggered drug release was investigated with the simplest pH/GSH dual-triggered doxorubicin-based drug self-delivery system (DSDS), the disulfide/α-amide-bridged doxorubicin dimeric prodrug (DDOX), as a model. By fast precipitation or slow self-assembly, DDOX nanoparticles were obtained. With similar diameters, they exhibited different pH/GSH dual-triggered drug releases, demonstrating the effect of aggregation structures. The π-π stacking in different degrees was revealed by the UV-vis, fluorescence, and BET analysis of the DDOX nanoparticles. The effect of the π-π stacking between the dimeric prodrug and its activated products on drug release was also explored with the molecular simulation approach. The finding opens new ideas in the design of high-performance DDSs for future precise tumor treatment.

Abrogation of ORF8–IRF3 binding interface with Carbon nanotube derivatives to rescue the host immune system against SARS-CoV-2 by using molecular screening and simulation approaches

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has led to over six million deaths worldwide. In human immune system, the type 1 interferon (IFN) pathway plays a crucial role in fighting viral infections. However, the ORF8 protein of the virus evade the immune system by interacting with IRF3, hindering its nuclear translocation and consequently downregulate the type I IFN signaling pathway. To block the binding of ORF8–IRF3 and inhibit viral pathogenesis a quick discovery of an inhibitor molecule is needed. Therefore, in the present study, the interface between the ORF8 and IRF3 was targeted on a high-affinity carbon nanotube by using computational tools. After analysis of 62 carbon nanotubes by multiple docking with the induced fit model, the top five compounds with high docking scores of − 7.94 kcal/mol, − 7.92 kcal/mol, − 7.28 kcal/mol, − 7.19 kcal/mol and − 7.09 kcal/mol (top hit1-5) were found to have inhibitory activity against the ORF8–IRF3 complex. Molecular dynamics analysis of the complexes revealed the high compactness of residues, stable binding, and strong hydrogen binding network among the ORF8-nanotubes complexes. Moreover, the total binding free energy for top hit1-5 was calculated to be − 43.21 ± 0.90 kcal/mol, − 41.17 ± 0.99 kcal/mol, − 48.85 ± 0.62 kcal/mol, − 43.49 ± 0.77 kcal/mol, and − 31.18 ± 0.78 kcal/mol respectively. These results strongly suggest that the identified top five nanotubes (hit1-5) possess significant potential for advancing and exploring innovative drug therapies. This underscores their suitability for subsequent in vivo and in vitro experiments, marking them as promising candidates worthy of further investigation.

Numerical and experimental investigation of temperature dependence vs. mobility degradation on I–V characteristics in N-LDMOS structure

The thermal behavior analysis is undoubtedly the main concern when studying semiconductor devices' and structures' physical mechanics. To the best of our knowledge, simulations studies with an experimental validation of the temperature effect vs. mobility on electrical characteristics in semiconductor devices, specifically in LDMOSFET devices are not well explored in the research literature. Considering this, this paper investigates the thermal influence vs. mobility degradation in the N-LDMOS structure and its impact on electrical performance. It also addresses the temperature impact on channel current Ids and these effects on component performance. The zero-temperature coefficient (ZTC) is evaluated in a N-LDMOS structure using numerical simulations and experimental tests. A study of the drain current behavior at ZTC (IZTC) is proposed in the linear and saturation regions. The influence of temperature mobility degradation on IZTC is analyzed. The consequences of mobility degradation show that the temperature increase gives rise to two contradictory phenomena: firstly, the channel current Ids increases when its value is lower than the current level (IZTC) and secondly, decreases when is higher. These two phenomena are studied by using simulated and experimental approaches, in order to extract and prove the physical aspects near the gate-drain access region (hot spot, electric field, electron concentration, surface carrier density, electron mobility), at the parameter evaluation origin, using SILVACO-TCAD based numerical simulation. Mobility degradation due to the temperature effect is compared to the critical value in N-LDMOS based on I–V behavior obtained with experimentation and simulations. This is explained by the role of negative thermal coefficient in LDMOS transistors. This coefficient proves to be particularly beneficial in terms of mobility gain at low inversion densities.

Atomistic molecular dynamics simulation and COSMO-SAC approach for enhanced 1,3-propanediol extraction with imidazolium-based ionic liquids.

1,3-Propanediol (1,3-PDO) is a key chemical in various industries, including pharmaceuticals and material sciences, and is projected to see significant market growth. However, the current challenges in its downstream processing, particularly in terms of cost and efficiency, highlight the need for innovative solutions. Our study delves into using ionic liquids (ILs) as a potential alternative, aiming to address these critical separation challenges more sustainably and efficiently. In this study, we utilized molecular dynamics (MD) simulations and the COSMO-SAC to examine 1,3-propanediol (1,3-PDO) extraction using four imidazolium-based ionic liquids with 1-butyl-3-methylimidazolium [Bmim] cation and with different anions bis(pentafluoroethanesulfonyl)imide [NPF2]-, bis(trifluoromethylsulfonyl)imide [NTF2]-, thiocyanate [SCN]-, and trifluoromethanesulfonate [TFO]-. Molecular dynamics simulations, incorporating analysis of radial distribution functions (RDF) and spatial distribution functions (SDF), revealed that [Bmim][SCN] and [Bmim][TFO] exhibit enhanced interactions with 1,3-PDO. Notably, [Bmim][SCN] formed the most hydrogen bonds, averaging 1.639 per molecule, due to its coordinating [SCN]- anion. This was in contrast to the fewer hydrogen bonds formed by non-coordinating anions in [Bmim][NPF2] and [Bmim][NTF2]. In ternary systems, [Bmim][SCN] and [Bmim][TFO] demonstrated superior selectivity for 1,3-PDO extraction compared to the other ionic liquids, with selectivity values around 29. These findings, supported by COSMO-SAC predictive modeling, highlight the potential of [Bmim][SCN] as a promising candidate for 1,3-PDO extraction, emphasizing the importance of anion selection in optimizing ionic liquid properties for this application. In our study, we employed MD simulations, incorporating the OPLS-AA force field, and COSMO-SAC to investigate the extraction of 1,3-PDO using imidazolium-based ionic liquids: [Bmim][NTF2], [Bmim][NPF2], [Bmim][SCN], and [Bmim][TFO]. The MD simulations were conducted using LAMMPS software, focusing on elucidating the RDF, SDF, and hydrogen bonding. Analysis of the distribution coefficient (β) and selectivity (S) for the ternary mixture was also conducted. These aspects of the simulation were analyzed using TRAVIS and VMD software. Additionally, the COSMO-SAC model was employed to determine the activity coefficients of 1,3-PDO in the ionic liquids, with molecular optimization conducted using Gaussian16 and sigma profile calculations performed using COSMO-SAC.

Phase-contrast neutron imaging compared with wave propagation and McStas simulations

Propagation-based phase contrast, for example in the form of edge enhancement contrast, is well established within X-ray imaging but is not widely used in neutron imaging. This technique can help increase the contrast of low-attenuation samples but may confuse quantitative absorption measurements. Therefore, it is important to understand the experimental parameters that cause and amplify or dampen this effect in order to optimize future experiments properly. Two simulation approaches have been investigated, a wave-based simulation and a particle-based simulation conducted in McStas [Willendrup &amp; Lefmann (2020). J. Neutron Res. 22, 1–16], and they are compared with experimental data. The experiment was done on a sample of metal foils with weakly and strongly neutron absorbing layers, which were measured while varying the rotation angle and propagation distance from the sample. The experimental data show multiple signals: attenuation, phase contrast and reflection. The wave model reproduces the sample attenuation and the phase peaks but it does not reproduce the behavior of these peaks as a function of rotation angle. The McStas simulation agrees better with the experimental data, as it reproduces attenuation, phase peaks and reflection, as well as the change in these signals as a function of rotation angle and distance. This suggests that the McStas simulation approach, where the particle description of the neutron facilitates the incorporation of multiple effects, is the most convenient way of modeling edge enhancement in neutron imaging.

Parking recommendation with meta-heuristic algorithms

Due to the exponential growth of cars in urban areas, parking problems have become a significant concern. Addressing this issue requires efficient methods for locating available parking spaces, enhancing the overall experience for drivers. This paper introduces a parking lot recommendation model leveraging meta-heuristic algorithms to generate a list of potential parking locations based on the users travel destinations. The primary objectives of these algorithms include minimizing travel distance, reducing total parking fees, and selecting parking lots with ample available spaces. The proposed model incorporates bio-inspired algorithms, including simulated annealing, genetic algorithms, and their adaptive variants. Our evaluation compares the performance of these algorithms, highlighting the adaptive simulated annealings superior quality of solutions and robustness against local minima. However, it is important to note that this approach comes with a trade-off, requiring longer execution times. In summary, this research contributes a novel parking lot recommendation model that effectively addresses the challenges posed by urban parking. The performance evaluation underscores the efficacy of the adaptive simulated annealing approach, showcasing its potential for practical implementation despite its relatively longer execution time.

Dynamic stress prediction for a Pump-Turbine in Low-Load Conditions: Experimental validation and phenomenological analysis

To meet the increasing demand for higher flexibility in hydropower, an operating range extension in an existing hydroelectric powerplant is considered. To this end, the dynamic flow and structural behavior of the low-head pump-turbine is investigated in turbine mode in partial load and deep partial load conditions, to evaluate the feasibility of this flexibilization due to the increased high cycle fatigue damage. In a first step, different numerical simulation approaches that combine fluid dynamics and structural dynamics are applied and compared to in-situ dynamic strain and pressure measurements on the impeller. As a result, the modelling requirements for a numerical workflow that leads to unmatched accuracy in predicting the broad-band dynamic stresses of deep partial load are identified. In a second step, the operating-point-dependent fatigue crack initiation spots are identified based on dynamic stresses. Herein, the emergence of an additional dominant critical spot near the blade leading edge is observed, which is unexpected for low-head pump turbines. Thanks to the detailed numerical flow and structural analyses, the root cause for the dynamic stress concentration is studied and the emergence of the new critical spot is understood. It turns out in deep partial load, that the main source of pressure oscillations on the impeller blade surfaces is the vortex-dominated flow detachment zone around the blade leading edge, which, in combination with the geometry of the investigated impeller, translates into the main stress oscillations. The results of this work were later used to extend the operating range of the hydroelectric powerplant from initially 25% to 100% power output to now 0% to 100%.

Preliminary investigation of the sea-rail intermodal system's efficiency using a simulation approach: case of the Port of Trois-Rivieres

Sea-rail intermodal transportation around the globe faces complex challenges that affect the satisfaction of shippers' needs. An efficient cargo flow between the port and its hinterland depends particularly on efficient connectivity between the seaport and rail. Sea-rail intermodal can be a cost-efficient and green alternative to unimodal road transportation. Inefficient sea-rail connectivity in the seaport slows cargo flow and affects port capacity. Various factors could affect the system's efficiency and create bottlenecks in the system. A case study adopts a discrete event-based simulation approach to assess bottlenecks in the sea-rail connection that affect cargo flow and generate congestion. The data were collected from the Port of Trois-Rivières, the focus of our investigation. Our objective is to identify bottlenecks in the sea-rail intermodal system in the port, identify strategies to mitigate bottlenecks and accelerate cargo flow. To this end, we examined various scenarios, including an increase in the share of trains for cargo transportation and an increase in the number of daily train convoys. The findings underscore that elevating the train share to 40% and introducing two daily train services yield significant enhancements in key performance indicators. Noteworthy advantages encompass a reduction in the average time ships spend in the port, a decrease in the average waiting time for trains to depart from the port, an overall improvement in cargo handling efficiency within the port, and a notable alleviation of bottlenecks within the system.

Use of a Modified Threshold Function in Fuzzy Cognitive Maps for Improved Failure Mode Identification

Fuzzy cognitive maps (FCMs) provide a rapid and efficient approach for system modeling and simulation. The literature demonstrates numerous successful applications of FCMs in identifying failure modes. The standard process of failure mode identification using FCMs involves monitoring crucial concept/node values for excesses. Threshold functions are used to limit the value of nodes within a pre-specified range, which is usually [0, 1] or [-1, + 1]. However, traditional FCMs using the tanh threshold function possess two crucial drawbacks for this particular.Purpose(i) a tendency to reduce the values of state vector components, and (ii) the potential inability to reach a limit state with clearly identifiable failure states. The reason for this is the inherent mathematical nature of the tanh function in being asymptotic to the horizontal line demarcating the edge of the specified range. To overcome these limitations, this paper introduces a novel modified tanh threshold function that effectively addresses both issues.

Computationally Efficient and Interface Accurate Dual-Grid Phase-Field Simulation of Turbulent Drop-Laden Flows

Abstract In this work, we develop a dual-grid approach for the direct numerical simulations (DNS) of tur- bulent multiphase flows in the framework of the phase-field method (PFM). With the dual-grid approach, the solution of the Navier-Stokes equations (flow-field) and of the Cahn-Hilliard equa- tion (phase-field) are performed on two different computational grids. In particular, a base grid - fine enough to resolve the flow down to the Kolmogorov scale - is used for the solution of the Navier-Stokes equations, while a refined grid - required to improve the description of small interfacial structures - is used for the solution of the Cahn-Hilliard equation (phase-field method). The proposed approach is validated, and its computational efficiency is evaluated considering the deformation of a drop in a two-dimensional shear flow. Analyzing the computational time and memory usage, we observe a reduction between ≃30% and ≃40% (with respect to the single-grid approach), depending on the grid refinement factor employed for the phase-field variable. The applicability of the approach to a realistic three-dimensional case is also discussed, by focusing on the breakage of a thin liquid sheet inside a turbulent channel flow. Indications on the grid resolution representing a good compromise between accuracy and computational efficiency in drop-laden turbulence are also provided.