Model Simulations Research Articles

Temporal fine structure sensitivity measured with pulse-spreading harmonic complexes.

Two experiments investigated sensitivity to temporal fine structure (TFS) in a group of normal hearing participants. The stimuli were bandpass filtered pulse-spreading harmonic complexes (PSHCs) with a regular envelope repetition rate and a phase adjusted so that the TFS peaks were progressively shifted across envelope periods. For up-PSHCs, the TFS peaks were advanced, yielding a rising pitch percept, while for down-PSHCs, the peaks were delayed, yielding a falling pitch percept. Experiment 1 showed that in a fixed frequency region, there was a range of rates for which the direction of the pitch change could be identified. Cochlear model simulations suggested that participants may use either place-of-excitation and/or temporal cues to perform this task. Experiment 2 showed that there was an envelope rate below which down-PSHCs and up-PSHCs could not be discriminated. This lower envelope rate limit of TFS sensitivity significantly increased with increases in frequency region and was similar to the lower rate limit of melodic pitch. The results in high frequency regions suggest that TFS cues are available up to 10 kHz when the rank of the lowest component present in the passband is 18, and all harmonics are presumably unresolved.

A New Climatology of Depth of Nitracline in the Bay of Bengal for Improving Model Simulations

A New Climatology of Depth of Nitracline in the Bay of Bengal for Improving Model Simulations

상자모형을 이용한 서울 겨울철 질산염 생성 메커니즘 분석

상자모형을 이용한 서울 겨울철 질산염 생성 메커니즘 분석

The role of Nature-Based Solutions for the water flow management in a Mediterranean urban area

Due to climate change and rapid urban sprawl, central Mediterranean regions are subjected to short but intensive storm events resulting in a significant increase of flow rates and runoff volumes in low-lying coastal urban areas. Within the framework of green urban infrastructures (GUIs), a suitable combination of Nature-Based Solutions (NBS) with traditional grey infrastructures should be adopted to mitigate flood risk effects in urban and sub-urban areas contributing at the same time to achieve multiple benefits for both the environment and the community. The aim of this study is (i) to evaluate flood hazard maps for identifying the areas within a Sicilian hydrological river basin (Toscano catchment) with a high risk of flooding by implementing the HEC-RAS model at catchment scale; (ii) to quantify the peak flow and floodplain area reduction; (iii) to assess the effectiveness of small-scale NBS (green roofs, porous pavements, rain gardens and rain barrel), in terms of peak flow and runoff volume reductions, at urban block scale by using the EPA SWMM model Model simulations are performed integrating the hydraulic (HEC-RAS) and hydrological (EPA SWMM) models for return periods of 10, 50 and 200 years. The results showed that the estimated peak flow (m3 s−1) obtained from the simulations performed at catchment scale for each T in the current scenario (without NBS) using HEC-RAS and EPA SWMM models are very close to each other (R2 = 0.99). In addition, the utopian scenario simulation showed the HEC-RAS model sensitivity to CN calibration achieving a peak flow reduction up to about 60% with the floodplain area decreasing up to about 17%. Finally, the model EPA SWMM shows its sensitivity to NBS implementation at urban block scale with a peak flow reduction up to about 16% and a runoff volume (mm) reduction up to about 24%. These reductions decrease as T increases with a higher NBS mitigation effects for the lowest T. The results highlighted that the integration of NBS in urban areas could have hydrological and hydraulic positive effects, particularly in terms of peak flow and runoff volume reduction. Furthermore, the results suggest that small-scale NBS have a potential to be effective to smaller rainfall events, but a combination with large-scale NBS is necessary to cope with extreme events.

Theoretical study of a putative adsorption mechanism of arginine and glutamate on goldfish 5.24 and zebrafish Z06: Statistical physics modeling, thermodynamic study, and docking simulation

An adsorption phenomenon putatively involved in the sense of smell of arginine and glutamate amino acids in the goldfish olfactory receptor 5.24 and the zebrafish olfactory receptor Z06 was applied in this study to deeply interpret and characterize the olfaction process at a molecular level. As a result, the experimental concentration-olfactory response curves were adjusted using the mono-layer model with one energy (MLM1E). On the one hand, the physicochemical parameters involved in the chosen model were utilized to microscopically investigate the four olfactory systems. Indeed, the two amino acids were adsorbed via a non-parallel configuration, and the process of adsorption was multi-molecular. The molar adsorption energies, which ranged from 22.09 to 35.97 kJ/mol, could be utilized to define the energetic interaction types between the investigated amino acids and the two tested fish olfactory receptors. The size and adsorption energy heterogeneity of 5.24 and Z06 binding pockets were measured by estimating the pocket site size distributions or PSDs (stereographic characterization) and the adsorption energy distributions or AEDs (energetic characterization). On the other hand, these physicochemical parameters could also be applied to macroscopically investigate the four olfactory systems. Hence, three thermodynamic functions including the adsorption entropy Sa, the internal energy Eint, and the Gibbs free energy G were computed in order to investigate the disorder, the exothermicity, and the spontaneity of the studied systems, respectively. The docking modeling analysis of arginine and glutamate amino acids with goldfish 5.24 and zebrafish Z06 revealed simulated binding energies that closely matched the average adsorption energies (peaks of AEDs). These affinities corresponded to the adsorption energy bands known as olfactory bands or spectrums of vibration modes.

Intrinsically Disordered Proteins by Homology Modeling and Replica Exchange Molecular Dynamics Simulations: A Case Study of Amyloid-β42

Homology modeling emerges as a potent tool unveiling the structural enigma of intrinsically disordered proteins (IDPs), with recent advancements such as AlphaFold2 enhancing the precision of these analyses. The process usually involves identifying homologous proteins with known structures and utilizing their templates to predict the three-dimensional architecture of the target IDP. However, IDPs lack a well-defined three-dimensional structure, and their flexibility makes it difficult to accurately predict their conformations. On the other hand, special sampling molecular dynamics simulations have been shown to be useful in defining the distinct structural properties of IDPs. Here, the structural properties of the disordered amyloid-β42 peptide were predicted using various homology modeling tools including C-I-TASSER, I-TASSER, Phyre2, SwissModel and AlphaFold2. In parallel, extensive replica exchange molecular dynamics simulations of Aβ42 were conducted. Results from homology modeling were compared to our replica exchange molecular dynamics simulations and experiments for gaining insights into the accuracy of homology modeling tools for IDPs used in this work. Based on our findings, none of the homology modeling tools used in this work can capture fully the structural properties of Aβ42. However, C-I-TASSER yields a radius of gyration and tertiary structure properties that are more in accord with the simulations and experimental data rather than I-TASSER, Phyre2, SwissModel and AlphaFold2.

Role of Vaccination Strategies to Host-Pathogen Dynamics in Social Interactions.

This study presents extended Immunity Agent-Based Model (IABM) simulations to evaluate vaccination strategies in controlling the spread of infectious diseases. The application of IABM in the analysis of vaccination configurations is innovative, as a vaccinated individual can be infected depending on how their immune system acts against the invading pathogen, without a pre-established infection rate. Analysis at the microscopic level demonstrates the impact of vaccination on individual immune responses and infection outcomes, providing a more realistic representation of how the humoral response caused by vaccination affects the individual's immune defense. At the macroscopic level, the effects of different population-wide vaccination strategies are explored, including random vaccination, targeted vaccination of specific demographic groups, and spatially focused vaccination. The results indicate that increased vaccination rates are correlated with decreased infection and mortality rates, highlighting the importance of achieving herd immunity. Furthermore, strategies focused on vulnerable populations or densely populated regions prove to be more effective in reducing disease transmission compared to randomly distributed vaccination. The results presented in this work show that vaccination strategies focused on highly crowded regions are more efficient in controlling epidemics and outbreaks. Results suggest that applying vaccination only in the densest region resulted in the suppression of infection in that region, with less intense viral spread in areas with lower population densities. Strategies focused on specific regions, in addition to being more efficient in reducing the number of infected and dead people, reduce costs related to transportation, storage, and distribution of doses compared to the random vaccination strategy. Considering that, despite scientific efforts to consolidate the use of mass vaccination, the accessibility, affordability, and acceptability of vaccines are problems that persist, investing in the study of strategies that mitigate such issues is crucial in the development and application of government policies that make immunization systems more efficient and robust.

Cl--dependent amplification of excitatory synaptic potentials at distal dendrites revealed by voltage imaging.

The processing of synaptic signals in somatodendritic compartments determines neuronal computation. Although the amplification of excitatory signals by local voltage-dependent cation channels has been extensively studied, their spatiotemporal dynamics in elaborate dendritic branches remain obscure owing to technical limitations. Using fluorescent voltage imaging throughout dendritic arborizations in hippocampal pyramidal neurons, we demonstrate a unique chloride ion (Cl-)-dependent remote computation mechanism in the distal branches. Excitatory postsynaptic potentials triggered by local laser photolysis of caged glutamate spread along dendrites, with gradual amplification toward the distal end while attenuation toward the soma. Tour de force subcellular patch-clamp recordings from thin branches complemented by biophysical model simulations revealed that the asymmetric augmentation of excitation relies on tetrodotoxin-resistant sodium ion (Na+) channels and Cl- conductance accompanied by a more hyperpolarized dendritic resting potential. Together, this study reveals the cooperative voltage-dependent actions of cation and anion conductance for dendritic supralinear computation, which can locally decode the spatiotemporal context of synaptic inputs.

Enhancing middle ear implants: Study of biocompatible materials with hydroxyapatite coating

In this manuscript, the application of hydroxyapatite coatings to total ossicular reconstruction prostheses (TORPs) using finite element modeling simulations was investigated to enhance the biocompatibility and mechanical performance of these prosthetic devices for middle ear implants. We focused on evaluating biocompatible materials, particularly polyetheretherketone (PEEK) and titanium, by analyzing their mechanical behavior under simulated conditions. The results revealed that PEEK demonstrates mechanical performance almost on par with titanium, exhibiting excellent stability and resilience within the middle ear environment. PEEK offers several key advantages over titanium, including easier fabrication, greater availability, and a simplified application process for hydroxyapatite coatings. These benefits suggest that PEEK could be a highly effective alternative to titanium for use in middle ear prostheses. The findings of this study highlight the potential of PEEK to improve the design and functionality of middle ear implants, providing a promising direction for future research and development in this field. By leveraging the advantages of PEEK, we can advance the effectiveness and accessibility of middle ear prosthetic devices, ultimately benefiting patients requiring such interventions.

Transfer-AE: A novel autoencoder-based impact detection model for structural digital twin

Accurately detecting the location and intensity of impacts is crucial for ensuring structural safety. Currently, AI-based structural impact detection methods are widely used for their excellent detection accuracy. However, their generalization capability is limited by the scenarios present in the training data. Many complex and dangerous impact scenarios are difficult to conduct real-world experiments on to collect sufficient samples. To capture all impact scenarios and fully leverage the advantages of AI-based detection technologies, advanced methods involve combining real-world structural monitoring data with corresponding numerical models to construct digital twins. These methods continuously refine the created numerical models with limited real-world data and provide diverse impact scenarios through numerical model simulations. However, there are inevitable differences between digital models and physical models that are challenging to correct through mechanical means. This discrepancy in data distribution between the two models significantly hinders the application of digital twin technology in impact/event identification tasks. To address this challenge, this study proposes a novel model based on autoencoders, named Transfer-AE. Transfer-AE encodes the common features of digital twins in the latent space to bridge the uncertainty gap at a macro scale between numerical models and physical models and synchronously fits the magnitude and location of the impact load in the decoder. This enables consistent detection results for the same impact event, whether the sample comes from the numerical model or the physical model. Transfer-AE includes two operating modes: Mode 1 has a fixed computational complexity with stable inference speed, but the training cost and difficulty increase with data distribution. Mode 2's computational complexity increases with data distribution, but it has a fixed training cost and speed. In both cases involving the geodesic dome structure simulating a deep space habitat and the IASC-ASCE benchmark structure, Transfer-AE demonstrated the best performance in impact localization and quantification tasks compared to mainstream domain-adaptive transfer models.

Research on Application of Composite Facades for Civilian Reconstruction of Industrial Heritage in Cold Regions Based on Thermal Buffering Effect

Previous studies on the civil transformation of industrial heritage have been conducted mainly from the perspective of architectural history, culture and aesthetics, but rarely focus on energy-saving and the comfort of the new users. Most industrial heritage facades are of high conservation value, but efforts to preserve the authenticity of the facade can lead to the application of limited energy-saving technologies, ultimately resulting in poor indoor thermal environments. Therefore, it is valuable to research how to solve the contradiction between protecting the authenticity of the preserved facades of industrial heritage and improving the indoor environmental performance. This paper proposes two composite facade application strategies based on thermal buffer effects, takes two composite facades renovation methods of Shenyang Dongmao No. 2 Warehouse as an example, utilizes the natural environmental resources to enhance the spatial quality of industrial heritage. With the help of DesignBuilder software modelling simulation analysis, in-depth comparative analysis of the two types of composite facades on the indoor thermal environment of the industrial heritage of the impact and scope. Key findings show that the application of two different composite facade retrofitting techniques not only protects the skin texture of the wall, but also effectively increases the indoor temperature and reduces the indoor energy consumption of the industrial heritage. The composite facade of the external solid wall and the internal glass is more stable in raising the indoor temperature, more effective in reducing the building energy consumption, and more suitable for the civilian transformation of industrial heritage in cold areas. The research findings provide reference for studies on the civil transformation of industrial heritage, and serve as technical references for architects.

Integrating 3DVAR and ANN for inversion optimization of physical models of fuel-assembly bowing

This study introduces a novel inversion optimization method for the core physical model of fuel-assembly bowing, integrating measurement data based on three-dimensional variational (3DVAR) data assimilation and artificial neural network (ANN) techniques. Recognizing the deviation between theoretical physical models and actual core conditions due to factors like uneven coolant distribution and fuel-assembly bowing, this work aims to enhance model reliability and simulation accuracy. By generating a dataset through random perturbation and employing ANN for training, the method establishes a relationship between the core physical model and model-simulated values corresponding to measurement data. The construction of the cost function, essential for optimizing the inversion process, is executed using 3DVAR. To verify its validity, the method is implemented, and an inversion optimization process is developed using our self-developed Bamboo-C code system. The optimization process, validated through application in a commercial pressurized water reactor (PWR) in a nuclear power plant (NPP) in China, demonstrates a significant reduction in the relative errors of power distribution, thus affirming the method’s efficacy in achieving a more realistic model of fuel-assembly bowing. The integration of measurement data into the optimization process addresses the critical need for accurate core physical models in nuclear engineering, offering a promising avenue for enhancing the safety and efficiency of nuclear reactor operations.

Thermomechanical Modeling and Numerical Simulation of Orthogonal Turning of 42CrMo4 Steel: Case of Workpiece/Tool Studies

Thermomechanical Modeling and Numerical Simulation of Orthogonal Turning of 42CrMo4 Steel: Case of Workpiece/Tool Studies

Modeling and Numerical Simulation of a Parabolic Trough Solar Collector Connected to a Solar Tracker

Modeling and Numerical Simulation of a Parabolic Trough Solar Collector Connected to a Solar Tracker

Effect of the Tundish Inhibitor Design on the Flotation Efficiency of Nonmetallic Inclusions: Water Modeling and Mathematical Simulations by the Reynolds Stress Model

Effect of the Tundish Inhibitor Design on the Flotation Efficiency of Nonmetallic Inclusions: Water Modeling and Mathematical Simulations by the Reynolds Stress Model

In silico identification of dual HDAC8 and MMP9 inhibitors by pharmacophore modeling, molecular docking, and molecular dynamics simulation studies for development of antitumour agent

In silico identification of dual HDAC8 and MMP9 inhibitors by pharmacophore modeling, molecular docking, and molecular dynamics simulation studies for development of antitumour agent

Research on the regenerative design and practice of the residential architecture atlases in Jiangnan during the Ming and Qing dynasties: a case study of the Mingyue Bay village in Suzhou

ABSTRACT The residential architecture atlases, chronicling the design motifs and craftsmanship of residences in Jiangnan during the Ming and Qing dynasties, serves as a cornerstone in deciphering the cultural metamorphosis and unearthing the subtle architectural essence specific to the region. With the advent of modern digital paradigms, this atlas has undergone a regeneration, evolving into a digital, real-time, and interactive embodiment of architectural lore. This study delves into the contents and characteristics of traditional and informational architectural atlases in Jiangnan during the Ming and Qing dynasties. It includes detailed surveys and mappings of the Mingyue Bay village in Suzhou, focusing on its geographic location, historical culture, and residential architectures. Utilizing AutoCAD and Photoshop, the study delineates the architectural plan atlas, elevation atlas, wooden frame atlas, and decoration atlas. It suggests regenerative design strategies for these traditional atlases. Furthermore, through MasterGo and SketchUp, this study elaborated on the regenerative design strategies of residential architecture information atlases in the Mingyue Bay village, including spatial-temporal information atlas, cultural tourism service atlas, scene experience atlas, model simulation atlas, and game interaction atlas. These atlases are integrated into a service platform of rural intelligent tourism, aimed at fostering the global inheritance of residential architecture culture and the revitalization of rural intelligent tourism.

Tropical Pacific trends explain the discrepancy between observed and modelled rainfall change over the Americas

Understanding the causes for discrepancies between modelled and observed regional climate trends is important for improving present-day climate simulation and reducing uncertainties in future climate projections. Here, we analyse the performance of coupled climate models in reproducing regional precipitation trends during the satellite era. We find statistically significant observed drying in southwestern North America and wetting in the Amazon during the period 1979–2014. Historical climate model simulations do not capture these observed precipitation trends. We trace this discrepancy to the inability of coupled simulations to capture the observed Pacific trade wind intensification over this period. A linear adjustment of free running historical simulations, based on the observed strengthening of the Pacific trade winds and modeled ENSO teleconnections, explains the discrepancy in precipitation trends. Furthermore, both the Pacific trade wind trends and regional precipitation trends are reproduced in climate simulations with prescribed observed sea surface temperatures (SST), underscoring the role of the tropical Pacific SST patterns.

Modeling of cotton yield responses to different irrigation strategies in Southern Xinjiang Region,China

Southern Xinjiang region represents a prototypical oasis agricultural area, and cotton is the primary cash crop. The current cotton water productivity for this area remains room for improvement. In order to refine cotton drip irrigation strategy in Southern Xinjiang, this study combined field experiment with crop model simulation and prediction. In this experiment, two irrigation methods, furrow irrigation and drip irrigation, and different degrees of deficit irrigation were set up. The impacts of soil moisture on cotton yield and quality were assessed, with the additional utilization of the Root Zone Water Quality Model (RZWQM2) for simulating irrigation scenarios and predicting cotton yield field data showed that during the 2021–2022 growing season, drip irrigation significantly increased boll weight, yield, and Water Productivity compared to furrow irrigation. The deficit irrigation with 90 % of full irrigation during the flowering period resulted in the highest yield among all drip irrigation treatments, while simultaneously improving the fiber quality. The RZWQM2 model was calibrated and validated using 2021 and 2022 cotton field experimental data, respectively. The calibrated and verified RZWQM2 model shows good performance. In terms of soil water storage, cotton yield and evapotranspiration. The simulated value output by the model is close to the measured value in the field. Model prediction data suggest that there is still room for improvement in cotton yield, accompanied by an increase in evapotranspiration. But deficit irrigation below 80 % of the full irrigation quotas poses a notable risk of yield reduction. Targeting higher yields, the predicted scenario suggests an increase in water application (irrigation quota:314.8 mm). Additionally, this study proposes irrigation regimes with water savings of 10 % and 20 %, with irrigation quotas of 290.5 mm and 266.5 mm during the growth period, respectively. Based on this study, we provide a more detailed and reliable water-saving scheme for cotton drip irrigation in southern Xinjiang region.

Development of a new indicator for identifying vegetation destruction events using remote sensing data

Frequent climate change and intense anthropogenic activity increase the risk of vegetation destruction. Remote sensing technology, known for its timely observations and wide coverage, is a crucial tool for monitoring vegetation growth. However, accurately detecting vegetation destruction events remains challenging due to their spectral diversity, particularly in complex environments. Existing spectral indices (VIs) have limitations in effectively capturing vegetation dynamics as they are only sensitive to specific physiological parameters of vegetation, such as foliage, canopy, or water content, and are prone to background interference. To address this issue, we proposed the Slope Vegetation Index (SVI) based on Sentinel-2 imagery and PROSAIL model simulation data. Five representative VIs were selected for comprehensive comparison. The results showed that, compared with other VIs, SVI had the highest sensitivity to vegetation physiological parameters, with a correlation coefficient (R2) greater than 0.98. SVI performed best across all vegetation change scenes, with producer accuracy (PA), user accuracy (UA), and F1 score all exceeding 0.90. SVI proved effective in detecting various vegetation destruction events, including logging, insect infestation, landslides, and wildfires. Moreover, SVI was suitable for Landsat-8/9 imagery, achieving an F1 score of over 0.89. Overall, SVI is an effective and robust vegetation monitoring index, offering valuable insights for vegetation resource management and post-disaster ecological restoration.