Simulated Process Research Articles

Unfolding bovine serum albumin decorated selenium nanoparticles crosslinking with chitosan: Achieve stabilization of Pickering emulsions gel and enhance resveratrol bioaccessibility.

Resveratrol (Res) is a natural polyphenol exhibiting anti-oxidant and anti-inflammatory activity. However, the applications of Res have been limited due to its low stability and water solubility. To enhance the bioaccessibility of Res, unfolding bovine serum albumin-modified selenium nanoparticles (UBSA@SeNPs) encapsulated within chitosan (CS)-coated Pickering emulsions (CS-UBSA@SeNPs-PE) were used to load Res. The results showed that Res-loaded CS(0.06%)-UBSA@SeNPs-PE has small droplet size (16.13μm), high gel properties and excellent antioxidant properties. During the simulated digestion process, CS reduced the release rate of Res from Res-loaded CS(0.06%)-UBSA@SeNPs-PE (42.27%) to reach a slow release effect. Importantly, Res could quickly release from CS-UBSA@SeNPs-PE within intestinal fluid or in the presence of chitosanase. In simulated absorption experiments, the intestinal permeability of Res in Res-loaded CS(0.06%)-UBSA@SeNPs-PE were enhanced by 292.31% compare to Res-loaded CS(0%)-UBSA@SeNPs-PE. In pharmacokinetic studies, Res-loaded CS(0.06%)-UBSA@SeNPs-PE had an area under the curve (AUC) up to 3467.99±127.43ng*h/mL. Furthermore, CS also improved the mucoadhesive nature of UBSA@SeNPs-PE, resulting in a gut-retention time of Res-loaded CS(0.06%)-UBSA@SeNPs-PE that reached up to 60h. In conclusion, CS-UBSA@SeNPs-PE can serve as an effective oral delivery system for improving the bioaccessibility of Res.

Degradation of Oxolinic Acid in Soil Under Simulated Natural Degradation Processes

Oxolinic acid (OA), a quinolone-class antibiotic commonly used in domestic agriculture, exhibits low bioavailability, raising concerns about its potential environmental persistence. Residual OA in the environment can undergo partial degradation through natural processes, which are influenced by various factors. This study aimed to investigate the photodegradation and biodegradation patterns of OA under various environmental factors, including temperature, light intensity, soil usage, soil organic matter content (OM). Additionally, adsorption and desorption experiments were conducted to elucidate the relationship between OA degradation and its adsorption-desorption behavior in soil. In this study, two UV-A intensities (2.3 and 1.5 mW cm<sup>-2</sup>) and two temperatures (21.8 and 35.0<sup>o</sup>C) were applied to examine the OA degradation behavior. Biodegradation tests were conducted using soil samples with varying land uses (rice paddy, field) and OM (6.4% and 2.3%). Additionally, sorption tests were performed using the soil samples and OA solutions, followed by desorption tests on the OA-sorbed soil samples. In the photodegradation experiment, the OA degradation rate ranged from 16.6% to 51% across all conditions after 20 d. Compared to other antibiotics reported in previous studies, OA exhibited relatively slow photodegradation, and the variations in degradation rates under the tested experimental conditions were not statistically significant. In the case of biodegradation, similar degradation rates were observed in the field and rice paddy soils, with faster degradation occurring in soils with lower OM. The differing biodegradation patterns observed across soil samples could be partially explained by the adsorption-desorption characteristics of OA in soils. The degradation of antibiotics through simulated natural processes such as photodegradation and biodegradation did not exhibit consistent trends depending on the environmental factors or soil properties. This suggests that the degradation of antibiotics is a complex process influenced by various factors, including, but not limited to, environmental factors and soil properties. This study highlights the need for further research to better understand the behavior of residual antibiotics in soil environments.

An integrated toolbox for creating neuromorphic edge applications

Abstract Spiking Neural Networks (SNNs) and neuromorphic models are believed to be more efficient in general and have more biological realism than the activation functions typically used in deep neural networks, transformer models and generative AI. SNNs have local learning rules, are able to learn on small data sets, and can adapt through neuromodulation. Although research has shown their advantages, there are still few compelling practical applications, especially at the edge where sensors and actuators need to be processed in a timely fashion. One reason for this might be that SNNs are much more challenging to understand, build, and operate due to their intrinsic properties. For instance, the mathematical foundation involves differential equations rather than basic activation functions. To address these challenges, we have developed CARLsim++, an integrated toolbox that facilitates the creation of neuromorphic applications. It extends the highly efficient CARLsim open-source SNN simulator. CARLsim++ encapsulates the mathematical intrinsics and low-level C++ programming by providing a graphical user interface for users to easily create their SNNs and a means to configure sensors and actuators for robotics and other edge devices. These can be accurately simulated before deploying on physical devices. CARLsim++ can lead to rapid development of neuromorphic applications for simulation or edge processing. We introduce CARLsim++ with a closed loop robotic demonstration using neuromorphic computing.

Growth-rate distributions of gut microbiota time series

Logarithmic growth-rates are fundamental observables for describing ecological systems and the characterization of their distributions with analytical techniques can greatly improve their comprehension. Here a neutral model based on a stochastic differential equation with demographic noise, which presents a closed form for these distributions, is used to describe the population dynamics of microbiota. Results show that this model can successfully reproduce the log-growth rate distribution of the considered abundance time-series. More significantly, it predicts its temporal dependence, by reproducing its kurtosis evolution when the time lag is increased. Furthermore, its typical shape for large is assessed, verifying that the distribution variance does not diverge with . The simulated processes generated by the calibrated stochastic equation and the analysis of each time-series, taken one by one, provided additional support for our approach. Alternatively, we tried to describe our dataset by using a logistic neutral model with an environmental stochastic term. Analytical and numerical results show that this model is not suited for describing the leptokurtic log-growth rates distribution found in our data. These results support an effective neutral model with demographic stochasticity for describing the considered microbiota.

Enhanced sampling of protein conformational changes via true reaction coordinates from energy relaxation

The bottleneck in enhanced sampling lies in finding collective variables that effectively accelerate protein conformational changes; true reaction coordinates that accurately predict the committor are the well-recognized optimal choice. However, identifying them requires unbiased natural reactive trajectories, which, paradoxically, require effective enhanced sampling. Using the generalized work functional method, we uncover that true reaction coordinates control both conformational changes and energy relaxation, enabling us to compute them from energy relaxation simulations. Biasing true reaction coordinates accelerates conformational changes and ligand dissociation in PDZ2 domain and HIV-1 protease by 105 to 1015-fold. The resulting trajectories follow natural transition pathways, enabling efficient generation of unbiased reactive trajectories. In contrast, biased trajectories from empirical collective variables display non-physical features. Furthermore, our method uses a single protein structure as input, enabling predictive sampling of conformational changes. These findings unlock access to a broader range of protein functional processes in molecular dynamics simulations.

Binaural speech intelligibility for combinations of noise, reverberation, and hearing-aid signal processing.

Binaural speech intelligibility in rooms is a complex process that is affected by many factors including room acoustics, hearing loss, and hearing aid (HA) signal processing. Intelligibility is evaluated in this paper for a simulated room combined with a simulated hearing aid. The test conditions comprise three spatial configurations of the speech and noise sources, simulated anechoic and concert hall acoustics, three amounts of multitalker babble interference, the hearing status of the listeners, and three degrees of simulated HA processing provided to compensate for the noise and/or hearing loss. The impact of these factors and their interactions is considered for normal-hearing (NH) and hearing-impaired (HI) listeners for sentence stimuli. Both listener groups showed a significant reduction in intelligibility as the signal-to-noise ratio (SNR) decreased, and showed a reduction in intelligibility in reverberation when compared to anechoic listening. There was no significant improvement in intelligibility for the NH group for the noise suppression algorithm used here, and no significant improvement in intelligibility for the HI group for more advanced HA processing algorithms as opposed to linear amplification in either of the two acoustic spaces or at any of the three SNRs.

Numerical analysis of aerodynamic performance characteristics of NACA 2412 and NACA 4412 at Re = 4000000

This paper conducts a numerical analysis of the two-dimensional aerodynamic characteristics of the NACA 2412 and NACA 4412 aerofoils at a Reynolds number of Re = 4106. Employing the fluid simulation software Ansys Fluent, which is based on the finite volume method, for numerical analysis. Both the geometric model and mesh of the aerofoil are established by using Fluent Meshing, and the simulation calculation is performed based on the pressure solver. Based on the Navier-Stokes equations, the SST k- turbulence model and coupled algorithm are employed for the simulation processing. The paper systematically compares the aerodynamic characteristics of NACA 2412 and NACA 4412, including the pressure and velocity distributions, as well as the variations in the lift coefficient, drag coefficient, and lift-to-drag ratio concerning the angle of attack. The results indicate that at Re = 4106, the peak value of the lift-to-drag ratio of the NACA 2412 aerofoil is attained under the 8 condition, for the NACA 4412 aerofoil, the lift-to-drag ratio reaches its peak value at a 6 angle of attack. Additionally, the stall angles of both types of aerofoils under the studied operating conditions are 16.

N2 influences on CH4 accumulation and displacement in shale by molecular dynamics

N2 is generally employed as a displacement agent to enhance gas recovery in shale gas-bearing reservoirs. However, the primary displacement mechanism in the subsurface still needs to be clarified due to the characteristics of shale reservoirs with low porosity and abundant nanopores. This study employs the Molecular Dynamics (MD) simulation method to investigate the effects of N2 on the CH4 accumulation and displacement processes by adopting practical conditions in the subsurface environment. In equilibrium MD simulation processes, including the N2 from outside and inner kerogen matrix, keeping the gas ratio of 1:3 for CH4 and N2, the displacement is 52.4% and 65.3%, respectively, which suggests that CH4 cannot be entirely displaced by surrounding N2 particles, owing to the strong interaction between CH4 and the kerogen matrix. For the straightforward displacement process by N2, the displacement efficiency is enhanced by 71.7% at the 1:1 gas ratio. Another case of N2, in which generation is accompanied by displacement processes, at the ratio 1:2 for N2:CH4, shows a 47.1% displacement efficiency. This work evidences that the straightforward displacement process is more efficient on CH4 displacement, which enhances CH4 production at a pronounced scale and sheds light on the N2 displacement process in industrial shale gas reservoir production.

Computational simulation of the Aerodynamic performance of NACA2412 and NACA25112 in low Reynolds numbers

The present study introduces the basic definition of aerofoil and NACA series aerofoil. Then numerically investigates the two-dimensional aerodynamic characteristics of NACA 2412 and NACA 25112 aerofoils at a Reynolds number of 2. 0106. This study utilises the fluid dynamics simulation tool ANSYS Fluent, which is based on the finite volume method, to acquire the necessary data. The geometric model and grid of aerofoil were built with ANSYS Meshing and simulated with the pressure-based solver. In addition, the experimental environment of this study is the inlet speed of 30m/s and the air pressure of 1ATM. The study based on the Nabier-Strokes control equation completes simulation processing with SSTK-Omega. The aerodynamic characteristics of NACA2412 and NACA25112 were compared, including the pressure, velocity distribution map and the lift resistance coefficient change with the angle of attack. These experimental results are presented in the form of graphs. This experiment can be used for subsequent wind tunnel experiments or for developing a new aerofoil.

Comparison of aerodynamic characteristics of NACA 2415 and NACA 4415 Aerofoils

This study compared the two-dimensional aerodynamic characteristics of NACA 2415 and NACA 4415 at different angles of attack. In this study, the Reynolds number is 2.3e6, under which the velocity of the air is 33 m/s. The mesh of C-type is established based on ANSYS Meshing; to simplify the calculation, the chord length is set to 1 m. The fluid simulation is done by ANSYS Fluent, and the simulation calculation is performed based on the pressure solver. The N-S equation is used as the governing equation. Velocity inlet and pressure outlet are set as the boundary condition, and the k-omega SST viscous model is chosen for the simulation processing. This study compares the aerodynamics of NACA 2415 and NACA 4415 at different angles of attack, including the pressure and velocity distribution, lift and drag coefficient, and lift-drag ratio. The results of this research would help optimize wing design and develop new aerofoil and testing.

Chemical characteristics and viscoelastic properties of Nothofagus alpina thinning wood thermally modified using a dynamic mechanical analysis (DMA)

ABSTRACT This study investigated variations in the chemical characteristics and viscoelastic properties of Nothofagus alpina wood from thinning during a thermal modification. In order to study the viscoelastic properties during an in-situ thermal modification process, a dynamic mechanical analysis apparatus was used. The initial moisture content of wood, modification temperature and the heating rate to reach the modification temperature were used as variables to assess their effect on viscoelastic properties. Furthermore, changes in the chemical characteristics before and after the simulated thermal modification process were analyzed by FTIR. The results underlined the importance of water content in wood, as it influenced the chemical characteristics of the modified wood in relation to the initial moisture content, and the changes of viscoelasticity in the variation of the storage modulus (E′) and loss modulus (E″), with E″ being more sensitive to the higher humidity used in this study. The modification temperature conditioned the effect of the moisture content, with a second additional peak being observed in E″ and tan δ (damping factor) at the modification of 210°C and 12% moisture content, but not in the oven-dry samples. Additionally, the effect of the heating rate was more pronounced at the lower modification temperature.

A system of trading in the foreign exchange market based on multi-criteria optimization under Belief-Plausibility uncertainty

A new Forex multi-criteria trading model based on the Belief-Plausibility (Bel−Pl) extension is developed and validated. The Bel−Pl approach is, in fact, a meta-theory in relation to the classical theory of fuzzy sets FST and the intuitionistic theory of fuzzy sets (IFST). This allows us to use more available information about the simulated process than these theories. The developed model consists of two interconnected, but different parts combined in the automated trading system (ATS). The first part of the Forex trading model is responsible for generating multi-indicator trading signals based on a set of new proposed technical analysis indicators that have been extended in the framework of the Bel−Pl approach. The second part of the model is a multiple-criteria Bel−Pl extended hierarchical trading model estimation. These two parts of the model are combined into the developed ATS, which implements the appropriate optimization procedure at the optimization stages and the simulation of the trading process at the testing or real trading stages. The advantages of the developed model and ATS were shown by comparing their results with the results obtained using fuzzy multi-criteria models and a single-criterion model. All studies were conducted over the past two years (2022-2023) for the H1 and H4 timeframes and three currency pairs EURUSD, USDJPY and GBPUSD.

Electrodynamic Tether and Brake Sails Combination Deorbit Design

Given the growing threat of an impending space debris crisis, nations worldwide have intensified their research efforts in satellite deorbiting technologies. Electrodynamic tether and braking sails stand out as popular methods for spacecraft deorbiting that do away with the necessity for propellant. However, these methods possess their own set of limitations. This paper presents a holistic dynamical model for a fusion of electrodynamic tether and braking sails. The aim is to avoid the complex nonlinear dynamics during the deployment, retrieval, and dwell time of electrodynamic tether, while compensating for the insufficient trust generated by braking sails in high orbital environments. The objective is to enable satellite to deorbit swiftly and stably under a broader range of conditions. Specifically accomplishing the following three aspects: conceptualizing the design of an ideal equipment, implementing simulated deorbiting process, and conducting an efficiency comparative analysis with prevalent current deorbiting methods. Through numerical simulations, the effectiveness and feasibility of this proposed design have been validated.

Development and characterization of quinoa protein-fucoidan emulsion gels with excellent rheological properties for 3D printing and curcumin encapsulation stability.

Using of low-fat emulsion gels stabilized by quinoa protein (QP) for 3D food printing was limited by their defective rheological properties. The study was to explore the feasibility of using fucoidan (FU) to improve the printability and curcumin encapsulation stability of QP emulsion gel. The gels with 0.5-0.75% FU incorporated were proved to be the most promising ink. Rheological analysis confirmed their great printing potential from the three-stages simulated 3D printing process. The incorporation of FU into emulsions induced more QP molecules adsorbed at the oil-water interface and smaller droplets size. When gel was induced by gluconate δ-lactone, these electrostatic interactions transformed into electrostatic attraction, resulting in a denser gel network. Adding FU to the gel improved its textural properties. Moreover, the gels with FU incorporated exerted better curcumin storage stability. This study provides a simple way to develop and improve the edible 3D printing inks for future food manufacturing.

Multi-scale structural evolution during simulated gelatinization process of sweet potato starch by heat-moisture treatment.

The changes in properties and structures of raw sweet potato starch (RAW-SPS) and heat-moisture treatment (HMT) sweet potato starch (HMT-SPS) during gelatinization process (S1-S6) was investigated to elucidate the improvement effect of HMT on SPS. It was found that SPS exhibited the characteristics of pseudoplastic fluids, characterized by shear thinning and thixotropy, belonged to the C-type starch crystal. The gelatinization temperature of SPS was increased to 82.55°C by HMT. HMT-SPS had better viscoelasticity in S3-S6. The particle size was smaller than that of RAW-SPS during the gelatinization process. The starch paste of S2 was gelatinized by heating at 95°C, and the original crystalline structure of the starch was destroyed, where layered structure formed by recrystallization was observed. HMT-SPS showed a clear polarization cross, while disappeared after S2. HMT also improved the ordering degree. The results explained the mechanism of changes in HMT modified starch during the gelatinization process.

Application of environmental thermal energy simulation and audio image processing in film and television animation sound design

Application of environmental thermal energy simulation and audio image processing in film and television animation sound design

MetaRange.jl: A Dynamic and Metabolic Species Range Model for Plant Species.

Process-based models for range dynamics are urgently needed due to increasing intensity of human-induced biodiversity change. Despite a few existing models that focus on demographic processes, their use remains limited compared to the widespread application of correlative approaches. This slow adoption is largely due to the challenges in calibrating biological parameters and the high computational demands for large-scale applications. Moreover, increasing the number of simulated processes (i.e., mechanistic complexity) may further exacerbate those reasons of delay. Therefore, balancing mechanistic complexity and computational effectiveness of process-based models is a key area for improvement. A promising research direction is to expand demographically explicit metapopulation models by integrating metabolic constraints. We translated and expanded a previously developed R metapopulation model to Julia language and published it as a Julia module. The model integrates species-specific parameters such as preferred environmental conditions, biomass and dispersal ability with demographic rates (e.g., reproductive and mortality rates) derived from local temperature and biomass via the metabolic theory of ecology. We provide a simple application example for the model in which we illustrate a typical use case by predicting the future occurrence of Orchis militaris in Bavaria under different climate change scenarios. Our results show that climate change reduces habitat suitability overall, but some regions like the Franconian Forest and the Alps see increased suitability and abundance, confirming their role as refugia. Simulating metapopulation dynamics reveals that local population dynamics and dispersal are crucial for accurate predictions. For instance, increasing dispersal distance reduces overall abundance loss but also lessens population growth in refugia. This highlights the importance of measuring traits like dispersal ability to improve climate change forecasts.

A MODIFIED NUMERICAL METHOD OF DETERMINING HYDRAULIC SYSTEM PARAMETERS FOR THE DEVELOPMENT OF MATHEMATICAL MODELS AND INFORMATION COMPLEXES OF COMPUTER SIMULATION MODELS FOR INDUSTRIAL CHEMICAL PRODUCTION

The paper introduces a modified numerical method for determining the parameters of hydraulic systems used in mathematical modeling and simulation-based computer systems for industrial chemical production. It explores the dynamics of fluids, gases, and their mixtures as they traverse pipelines equipped with valves, compressors, and other complex components. Traditional methods for solving nonlinear equation systems often face limitations, including sensitivity to initial approximations and the need for relaxation coefficient adjustments, which complicate simulation processes. The proposed method converts nonlinear equations into an optimization problem, us- ing the Nelder-Mead algorithm to minimize deviations between initial estimates and comput- ed parameters. This derivative-free approach employs a simplex geometric transformation, overcoming issues associated with iterative methods and delivering high accuracy, stable convergence, and computational efficiency. Its adaptability makes it suitable for handling in- tricate hydraulic systems. To validate the method, a practical example involving a pipeline system with multiple restricting devices is analyzed. The mathematical model includes equations for pressures and flow rates, supplemented by material balance constraints at branching points. Numerical ex- periments evaluate how input pressure influences system parameters, demonstrating the mod- el's robustness and precision. The results confirm that the method accurately simulates system parameters under steady-state conditions and identifies critical optimization points. This innovative approach offers significant advantages for designing and managing industrial chemical facilities. By simplifying model construction, enhancing reliability, and accelerating simulation processes, the method provides a powerful tool for optimizing the op- eration and control of complex technological systems.

Machine learning-driven thermal management and output behavior prediction for a multi-segment bonded Tm:YAG laser.

This paper addresses the thermal instability of lasers resulting from the thermal effects of the 2 µm gain medium, proposing what we believe to be a novel compensation scheme that integrates machine learning technology with multi-segment bonded Tm: YAG crystals and negative lenses, based on the thermal focal length model of a thick thermal lens. This approach significantly optimizes thermal compensation and facilitates rapid assessment of the light-emitting behavior trends of Tm: YAG lasers. Firstly, the thermal behavior of conventional and multi-segment bonded Tm: YAG crystals is analyzed. An apparently new thermal focal length model for thick lenses is established based on thin lens theory, and BP neural networks are employed to screen and predict the performance of both models. It demonstrates superior predictive capability at specific power levels, achieving a maximum error of 1.8 mm and a minimum error rate of 1.9%. Following this, we select negative lenses with varying focal lengths for thermal compensation experiments, revealing that the compensation effects differ based on the focal lengths and positions of the negative lenses at varying pump powers. To address this complex nonlinear relationship, we utilize a random forest optimization algorithm, which successfully predicts the impact of negative lens positioning on output power across three different cavity lengths, resulting in prediction errors of 1.4%, 1.1%, and 2.1%. The model performs particularly well when the Tm: YAG laser approaches destabilization. This high-accuracy predictive model enables rapid identification of the optimal position for the negative lens, facilitating effective thermal compensation while streamlining traditional numerical simulation processes. Moreover, it provides critical guidance for the thermal management of 2 µm lasers and enhances the precision of assessments related to their light-emitting behavior.

Effects of Redox Condition on Bacteria-Mediated Hydrochemical Processes and Bacterial Community During Managed Aquifer Recharge

During the process of managed aquifer recharge (MAR), when the aerobic surface water is recharged into the reductive aquifer, the redox environment changes along the water pathway. MAR practice can reshape the initial groundwater bacterial community, and further induce variations in the bacteria-mediated hydrochemical reactions. In this study, laboratory-scale column experiments were conducted to simulate the processes of aerobic/anaerobic recharge to aquifer. The results showed that the concentration of DO during the aerobic recharge was higher than that of the anaerobic recharge, and ORP showed a similar trend. Active nitrogen transformation was observed during the simulated MAR processes. In the early stages of both the aerobic and anaerobic recharges, nitrate reduction occurred due to denitrification and DNRA. However, in the late stages, nitrification might happen in the aerobic column, and nitrate reduction remained the major process in the anaerobic column. For the bacterial community, Massilia, Ralstonia, Legionella, and Curvibacter predominated under the aerobic recharge. Comparatively, Cedecea, Cupriavidus, and Ralstonia maintained high relative abundances under the anaerobic recharge. Our study provides essential information about the characteristics of bacterial-mediated hydrochemical reactions during the MAR process. The result would enhance understanding of MAR activities and provide valuable insights into the groundwater resources’ sustainable development and management.