Simulated Model Research Articles

Large Eddy Simulations of a Medium-Scale Ethanol Pool Fire Using Conditional Source-Term Estimation Including Coupled Soot Radiation Effects

ABSTRACT The objective of this paper is to assess the combined capabilities of Conditional Source-Term Estimation with radiation and soot modeling in large eddy simulations of a medium-scale ethanol pool fire. Tabulated detailed chemistry is implemented including radiative losses. The radiative transfer equation is solved with the weighted sum of gray gas models to determine the gaseous absorption. Two subgrid soot models are considered using the laminar smoke point concept. The first approach calculates the soot formation and oxidation rates corrected to account for turbulent effects. The second determines the soot reaction rates in conditional space using analytical functions and the filtered reaction rates are determined by convolution with the filtered mixture fraction density function. Predictions of the time-averaged and root mean square temperature, species mole fractions and soot mass fraction are compared with experimental measurements. Numerical temperatures agree well with experiments except in the fire plume where some overpredictions are observed. Species concentrations match the measurements with some discrepancies observed in the products farther downstream, partly explained by the experimental uncertainty. The peak soot predicted with the first model is in reasonable agreement with the experiments but is much lower using the second approach. These differences are explained by the differences in the turbulence soot chemistry treatment and calibration of empirical constants. However, here, soot has a limited impact on the temperature, flow and mixing fields due to low soot concentrations produced by ethanol. The radiative heat fluxes are reasonably well predicted. Further validation is needed with additional experimental soot data.

Examination of the Bioavailability and Bioconversion of Wheat Bran-Bound Ferulic Acid: Insights into Gastrointestinal Processing and Colonic Metabolites.

The postingestion journey and bioconversion of wheat bran-bound ferulic acid, a known beneficial phytochemical, remain insufficiently understood. This study aims to systematically investigate its bioaccessibility, bioavailability, excretion, and colonic metabolism, both in vitro and in vivo. Initial analysis confirmed the abundance and bioactivity of ferulic acid in wheat bran. Using a simulated gastrointestinal model, 1.7% of the ferulic acid was found to be bioaccessible, in contrast to 43.4% for total phenolics. In vivo bioavailability was assessed in rats via oral gavage of cooked wheat bran, with a plasma ferulic acid level peaking at 32.5 ± 4.9 ng/mL, corresponding to an absorption rate of 0.3%, while 1% was excreted in urine. Fecal metabolomic analysis revealed extensive colonic bioconversion, with elevated levels of ferulic acid and its metabolites, including 3-phenylpropionic acid, dihydroferulic acid, 5-hydroxyferulic acid, and hippuric acid. Novel metabolites, such as 3-(2,5-dimethoxyphenyl)propionic acid and N-(2-furoyl)glycine, were detected for the first time. These findings shed light on the complex biotransformation of wheat bran-bound ferulic acid and its potential health implications.

A New Pabs Model for Quantitatively Diagnosing Phosphorus Nutritional Status in Corn Plants

Accurate diagnosis of plant phosphorus nutritional status is critical for optimizing agricultural practices and enhancing resource efficiency. Existing methods are limited to qualitatively assessing plant phosphorus nutritional status and cannot quantitatively estimate the plant’s phosphorus requirements. Moreover, these methods are time-consuming, making them impractical for large-scale application. In this study, we developed an advanced phosphorus absorption model (Pabs) that integrates the phosphorus nutrition index (PNI) and phosphorus use efficiency (PUE). The PUE, a critical metric for assessing phosphate fertilizer use efficiency, was quantified by comparing yields under fertilized and unfertilized conditions. Utilizing the Agricultural Production Systems Simulator (APSIM) model, we simulated maize (Zea mays L.) phosphorus concentration (P) and aboveground biomass (Bio) under varying phosphorus application rates. The model exhibited robust performance, achieving an R2 above 0.95 and an RMSE below 0.22. Based on the APSIM model simulations, a phosphorus dilution curve (Pc = 3.17 Bio−0.29, R2 = 0.98) was established, reflecting the dilution trends of phosphorus across growth stages. Furthermore, the use of vegetation indices (VIS) to evaluate phosphorus nutritional status also showed promising results, with inversion accuracies exceeding 0.70. To validate the model, field sampling was conducted in maize-growing regions of Changchun. Results demonstrated a correct diagnosis rate of 75%, underscoring the model’s capacity to accurately estimate phosphorus requirements on a regional scale. These findings highlight the Pabs model as a reliable tool for precision phosphorus management, offering significant potential to optimize fertilization strategies and support sustainable agricultural systems.

DynamicVLN: Incorporating Dynamics into Vision-and-Language Navigation Scenarios

Traditional Vision-and-Language Navigation (VLN) tasks require an agent to navigate static environments using natural language instructions. However, real-world road conditions such as vehicle movements, traffic signal fluctuations, pedestrian activity, and weather variations are dynamic and continually changing. These factors significantly impact an agent’s decision-making ability, underscoring the limitations of current VLN models, which do not accurately reflect the complexities of real-world navigation. To bridge this gap, we propose a novel task called Dynamic Vision-and-Language Navigation (DynamicVLN), incorporating various dynamic scenarios to enhance the agent’s decision-making abilities and adaptability. By redefining the VLN task, we emphasize that a robust and generalizable agent should not rely solely on predefined instructions but must also demonstrate reasoning skills and adaptability to unforeseen events. Specifically, we have designed ten scenarios that simulate the challenges of dynamic navigation and developed a dedicated dataset of 11,261 instances using the CARLA simulator (ver.0.9.13) and large language model to provide realistic training conditions. Additionally, we introduce a baseline model that integrates advanced perception and decision-making modules, enabling effective navigation and interpretation of the complexities of dynamic road conditions. This model showcases the ability to follow natural language instructions while dynamically adapting to environmental cues. Our approach establishes a benchmark for developing agents capable of functioning in real-world, dynamic environments and extending beyond the limitations of static VLN tasks to more practical and versatile applications.

A System Dynamics Simulating Model of Groundwater Level Changes and Its Impacts on Land Uplift

A System Dynamics Simulating Model of Groundwater Level Changes and Its Impacts on Land Uplift

The cognitive critical brain: modulation of criticality in perception-related cortical regions

The constantly evolving world necessitates a brain that can swiftly adapt and respond to rapid changes. The brain, conceptualized as a system performing cognitive functions through collective neural activity, has been shown to maintain a resting state characterized by near-critical neural dynamics, positioning it to effectively respond to external stimuli. However, how near-criticality is dynamically modulated during task performance remains insufficiently understood. In this study, we utilized the prototypical Ising Hamiltonian model to investigate the modulation of near-criticality in neural activity at the cortical subsystem level during perceptual tasks. Specifically, we simulated 2D-Ising models in silico using structural MRI data and empirically estimated the system's state in vivo using functional MRI data. We first replicated previous findings that the resting state is typically near-critical as captured by the Ising model. Importantly, we observed heterogeneous changes in criticality across cortical subsystems during a naturalistic movie-watching task, with visual and auditory regions fine-tuned closer to criticality. A more fine-grained analysis of the ventral temporal cortex during an object recognition task further revealed that only regions selectively responsive to a specific object category were tuned closer to criticality when processing that object category. In conclusion, our study provides empirical evidence from the domain of perception supporting the cognitive critical brain hypothesis that modulating the criticality of subsystems within the brain's hierarchical and modular organization may be a fundamental mechanism for achieving diverse cognitive functions.

Impact of simulated gastrointestinal conditions on polyphenol stability and antiglycoxidant potential of sage (Salvia officinalis) infusion

Sage (Salvia officinalis) is a medicinal plant commonly used in traditional medicine, particularly in the form of herbal tea. Sage tea is used, among others, in cases of dyspepsia, rheumatism, and excessive sweating and is known for its positive effects on oxidative stress. However, the impact of digestion on sage phenolic stability and antiglycoxidant properties is not known. This study aimed to assess the influence of the digestive process on phenolic contents, antiglycoxidant activities, and xanthine oxidase inhibition capacity using an in vitro simulated digestion model. Total polyphenol content was not altered by the digestion process, despite a moderate but significant decrease in total flavonoid and phenolic acid contents. HPLC analysis confirmed a significant drop in luteolin 7-O-glucuronide and rosmarinic acid contents (the main sage polyphenolic compounds) after the intestinal stage. However, simulated digestion did not generally alter antioxidant activities nor antiglycant activity and xanthine oxidase inhibition capacity. Consequently, the present study confirmed the potential bioaccessibility of sage tea polyphenolic compounds and suggested that sage tea could exert beneficial effects in view of its preserved antiglycoxidant properties after in vitro simulated digestion.

Lifetime Treatment Trajectories of Mantle Cell Lymphoma: Simulation Based Analysis of 20Years of Real-World Data.

Mantle cell lymphoma is a rare type of B-cell lymphoma, which is considered incurable yet treatable. In recent years, the treatment options of mantle cell lymphoma have multiplied, and the focus of treatment is expected to shift from traditional chemoimmunotherapy toward precision medicine. However, this development is hindered by the high costs of targeted therapies. To provide a baseline for future assessment of costs and benefits of new and emerging MCL treatments, we established a predictive simulated model of lifetime treatment trajectories based on a retrospective cohort of chemoimmunotherapy era patients diagnosed and treated between the year 2000 and 2020.

COMPUTER PROGRAM FOR MODELLING RAINFALL INTENSITY DURATION FREQUENCY (IDF) RELATIONSHIPS BY SHERMAN’S METHOD FOR ILORIN AREA IN NIGERIA

A computer program was developed for the modelling of rainfall data for a period of 30 years (1981-2010) for Ilorin area using a MATLAB software. The data was analyzed by sorting and ranking the maximum rainfall depths with their corresponding depths and their return periods. The rainfall depths were converted to rainfall intensities. An algorithm was developed in form of a flowchart which guided the development of computer program using Sherman’s method. Values of rainfall intensities with corresponding durations and return periods were exported to the MATLAB program for modelling of station constants and simulation of IDF curves for Ilorin area. The station constants were obtained as n = 0.5707, c = 131.0144, and m = 0.3425 for Ilorin area respectively. These were used to produce IDF curves and mathematical model for Ilorin area.

A geometry-based decomposition method for energy prediction in early design stages of residential buildings

PurposeThe purpose of the study is to develop a geometry-based energy estimation method for surrogate and metamodels to be used in the early design phase of buildings.Design/methodology/approachOptimizing building form and design variables in the early stages of the architectural design process, particularly during the conceptual phase, can significantly enhance overall design performance and energy efficiency at minimal cost. This study introduces a novel decomposition method for evaluating building energy performance by simplifying complex building forms into basic geometric shapes.FindingsThe developed method is applied to certain cases of design variation under specified boundary conditions, and the accuracy of heating and cooling energy loads is calculated with simulated energy models of these cases. As a result of the calculation, accuracy rates between 84.30 and 99.98% were founded.Originality/valueThis paper proposes a prediction model with a geometric identification method for an innovative geometry-based surrogate modeling method. This method also provides a way for artificial intelligence-based prediction models used in surrogate models to create a dataset and can be used in the training in future works.

Child standardized patients in pediatric OSCEs: a feasibility study for otoscope examination among undergraduate students in Rwanda

BackgroundOtoscope examinations are a fundamental skill in pediatric care, crucial for diagnosing and managing ear conditions such as otitis media. Traditional training methods for pediatric otoscopic examination often rely on adult standardized patients (SPs) or simulated models, which may not be adequate for pediatric examinations.ObjectivesThis study evaluates the feasibility and effectiveness of use of children as SPs in Objective Structured Clinical Examinations (OSCEs) to assess medical students’ competency in pediatric otoscopy.MethodsThis descriptive cross-sectional study was conducted at the University of Global Health Equity (UGHE), Rwanda during the final exit examinations. This study included 30 final-year medical students, and six child SPs aged 5–8 years, along with their guardians. Quantitative data were collected using structured questionnaires on students perceived self-efficacy and performance. Qualitative data were obtained through focus group discussions with guardians and child SPs.ResultsThe mean (standard deviation) performance of students at the otoscope examination station was 81.67 (5.7) %, with a significant positive correlation between perceived self-efficacy and actual performance (r = 0.493, p = 0.006). The mean performance at the OSCE station was slightly higher than perceived students’ self-efficacy, (72.5 (6.8) vs. 81.67%. p < 0.001). Students reported high levels of satisfaction with the use of child SPs, with 83.3% recommending their use in pediatric OSCEs. Guardians and child SPs also expressed overall satisfaction, though concerns were noted regarding students’ levels of confidence. and communication skills.ConclusionIncorporating children as SPs in pediatric OSCEs enhances the realism and educational value of otoscope training with positive correlation between perceived self-efficacy and actual performance.

Study results of the stress-strain states of the crown parts of molars restored with composite, ceramic and zirconium onlays

The relevance of the research is determined by the significant need for effective restorative treatment of caries decayed teeth. The purpose of the study is comparison of the stress-strain states in simulated models of non-homogeneous composite structural elements for typical geometric characteristics of onlays made of composite, ceramic, and zirconium dioxide in the restoration of the decayed mandibular molar. Computer simulation models of biomechanical systems were obtained by digital scanning of the mandibular molar in STEP format. Control was carried out in the form of numerical characteristics and graphical visualization in the EXOCAD program. The numerical method of finite elements, information technologies and program codes of the ANSYS Workbench 12.1 system were used to solve applied problems of biomechanics. After testing the developed discrete models, they were checked for adequacy and coincidence of numerical results in areas of high voltage gradients using the tools and methods of the ANSYS 12.1 code system. The maximum displacements, gradients, and amplitudes of the Mises-equivalent stress in the structural elements of each biomechanical system were evaluated. The stress values were calculated using the method of linear scaling of the results of the numerical solution of the boundary value problems of the theory of elasticity for small deformations to correspond to the functional force load of the mandibular molar of 100 N. The estimated values of the coefficients of the strength reserve of the structural elements were calculated as the ratio of the strength limit values to the maximum calculated values of the Mises-equivalent stress, scaled by a coefficient of 10 for a force load of 100 N. It was established that the largest voltage gradients are registered at the border of the cement layer. However, the nature of force transmission, as well as stress distribution, was different for different structural materials. The maximum stress was observed in the model with a composite onlay in the local area of the surface of the force load in the cement layer. For the ceramic onlay, the maximum stress was found on the lower support surface of contact with the onlay, where its values were 1.4 times higher than on other surfaces. The analysis of the zones of maximum stress for the zirconium onlay revealed their predominant localization in the center of its occlusal surface and in the zone of change in its spatial configuration at the border with cement. The highest stress values, along with the lowest coefficients of safety margin, were found for the molar model restored with a composite onlay, which indicated the lowest endurance of this material to functional load. While the zirconium onlay provided optimal stress distribution and it was characterized by the largest safety factor, which makes this method the most acceptable for molar restoration. The obtained results should be taken into account when choosing a material for the prosthetics of lateral teeth with onlays.

Detection of Brain Stroke Using Microstrip Slot Antenna

Stroke is one of the world’s most serious health issue. A decrease of blood flow to a portion of the brain that results in brain tissue damage is termed as stroke in medical science. Blood clots and ruptured blood arteries in the brain are the main causes of strokes. A brain stroke can be categorized under ischemic stroke and hemorrhagic stroke. Existing approaches are noninvasive, but they are constrained by cost and reliability concerns. These diagnostic approaches are insufficient to detect stroke in human head. Hence, a microstrip slot antenna has been designed with stroke model and human head phantom model, and stroke is detected with the help of antenna. In 2.45GHz ISM band frequency range proposed antenna with circular edge slots and circular slot in the front plane and ground slotted plane has been designed. A 3-D seven layer simulated head phantom model is designed and interfaced with the proposed antenna with and without stroke model. The stroke is detected by observing changes in antenna performance parameters viz. return loss, peak gain, radiation efficiency. Sphere shaped stroke is detected by observing variation in the antenna performance parameter. The stroke detection is applied on the cylindrical phantom on the HFSS software. The result shows that the change in performance is experienced as the distance between the antenna and the head phantom changed. The value of peak gain and radiation efficiency decreases thus depicting the presence of stroke.

NUMERICAL INVESTIGATION ON FLEXURAL PERFORMANCE OF BUILT-UP STEEL BEAMS WITH DIFFERENT WEB OPENINGS

Recently, the usage of Structural Steel Beams with Opening in the Web has spread extensively in all over the world, in various types of buildings such as high-rise buildings and industrial buildings. There are several advantages in using openings in beams. There for, an analytical investigation was carried out on fourSteel Beams with Opening (SBWO) models by using a powerful nonlinear simulation software ABAQUS. The initiative was to study the overall flexural behaviour of (SBWO’s) and to establish the maximum load carrying capacity, and deflection. Only vertical loads have been considered in the (SBWO’s) performance investigation. The Built-Up sections were tested up to failure. The simulated models were considered to be under simply supported condition at their edges and a uniform distributed load were applied over the upper flange of the beam along all beam's length. The flexural behaviour of beams with different opening shapes were tested and compared. The test results proved to be very useful in selecting the opening shape.

The effect of varying thicknesses of mineral trioxide aggregate (MTA) and Biodentine as apical plugs on the fracture resistance of teeth with simulated open apices: a comparative in vitro study.

This study evaluates the fracture resistance of apical plugs created from Biodentine and mineral trioxide aggregate (MTA) in thicknesses of 3 and 5 mm within simulated open apex tooth models. Fifty human maxillary central incisors were obtained from a pool of freshly extracted teeth. In order to replicate open apices without cavity preparation, ten teeth in the control group received apical-to-coronal preparation with Peeso reamers. The remaining 40 teeth were randomly assigned to four experimental groups and received either 3 or 5 mm Biodentine or MTA apical plugs. The mean fracture loads observed in this study were as follows: control group, 431.48 N (±34.55); 3 mm MTA, 774.88 N (±62.74); 5 mm MTA, 752.65 N (±73.79); 3 mm Biodentine, 918.25 N (±59.09); and 5 mm Biodentine, 903.42 N (±24.48). Specifically, teeth in the Biodentine group demonstrated considerably stronger fracture resistance compared to those in the MTA group (p < 0.001). However, no significant differences were observed between the 3 and 5 mm thicknesses (MTA: p = 0.98, Biodentine: p = 0.99), suggesting that plug thickness did not affect fracture resistance within both groups. Biodentine apical plugs provided the highest fracture resistance among the materials, regardless of thickness.

Factors influencing the current and future distribution of the fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), in Ethiopia

Abstract The fall armyworm, Spodoptera frugiperda (Lepidoptera: Noctuidae), is among the key invasive pests attacking maize and sorghum, the staple cereals in many countries in Africa. The determination of habitat suitability of invasive species via correlative model is among the priority tasks that provide basic information for achieving sustainable plant protection. In this study, we developed a species distribution model of S. frugiperda and identified the key influencing environmental factors under current and future climatic conditions in Ethiopia via the MaxEnt program. The results showed that the area under the curve (AUC) of the simulated model was 0.856 (±0.010), confirming the good predictive ability of the model. The isothermality and precipitation of the driest month are the most dominant bioclimatic variables with a percentage contribution of 39.4% and 11.6%, respectively, in the model. The percentages of very highly suitable, highly suitable, moderately suitable, low‐suitable, and unsuitable areas were 21.24%, 21.17%, 28.22%, 16.34% and 13.03%, respectively, of the total Ethiopian land mass. From the present to the 2070s, the areas of highly suitable and very highly suitable habitats for S. frugiperda will increase due to global warming. This study noted that the pest was a major threat to maize and sorghum in Ethiopia. Hence, due emphasis should be given to strengthening monitoring and management in a suitable range, which would lessen economic losses due to invasion and ensure agricultural safety.

A gut-derived Streptococcus salivarius produces the novel nisin variant designated nisin G and inhibits Fusobacterium nucleatum in a model of the human distal colon microbiome.

Fusobacterium nucleatum is a human pathogen associated with intestinal conditions including colorectal cancer. Screening for gut-derived strains that exhibit anti-F. nucleatum activity in vitro revealed Streptococcus salivarius DPC6487 as a strain of interest. Whole-genome sequencing of S. salivarius DPC6487 identified a nisin operon with a novel structural variant designated nisin G. The structural nisin G peptide differs from the prototypical nisin A with respect to seven amino acids (Ile4Tyr, Ala15Val, Gly18Ala, Asn20His, Met21Leu, His27Asn, and His31Ile), including differences that have not previously been associated with a natural nisin variant. The nisin G gene cluster consists of nsgGEFABTCPRK with transposases encoded between the nisin G structural gene (nsgA) and nsgF, notably lacking an equivalent to the nisI immunity determinant. S. salivarius DPC6487 exhibited a narrower spectrum of activity in vitro compared to the nisin A-producing Lactococcus lactis NZ9700. Nisin G-producing S. salivarius DPC6487 demonstrated the ability to control F. nucleatum DSM15643 in an ex vivo model colonic environment while exerting minimal impact on the surrounding microbiota. The production of this bacteriocin by a gut-derived S. salivarius, its narrow-spectrum activity, and its anti-F. nucleatum activity in a model colonic environment indicates that this strain merits further attention with a view to harnessing its probiotic potential.IMPORTANCEFusobacterium nucleatum is a human pathogen associated with intestinal conditions, including colorectal cancer, making it a potentially important therapeutic target. Bacteriocin-producing probiotic bacteria demonstrate the potential to target disease-associated taxa in situ in the gut. A gut-derived strain Streptococcus salivarius DPC6487 was found to demonstrate anti-F. nucleatum activity, which was attributable to a gene encoding a novel nisin variant designated nisin G. Nisin G-producing S. salivarius DPC6487 demonstrated the ability to control an infection of F. nucleatum in a simulated model of the human distal colon while exerting minimal impact on the surrounding microbiota. Here, we describe this nisin variant produced by S. salivarius, a species that is frequently a focus for probiotic development. The production of nisin G by a gut-derived S. salivarius, its narrow-spectrum activity against F. nucleatum, and its anti-F. nucleatum activity in a model colonic environment warrants further research to determine its probiotic-related applications.

Tailoring Ga‐Doped ZnO Thin Film Properties for Enhanced Optoelectric Device Performance: Argon Flow Rate Modulation and Dynamic Sputtering Geometry Analysis

The impact of dynamic sputtering geometry on the properties of ZnO: Ga (GZO) thin film nanomaterials is investigated by systematically varying Ar flow rates and substrate positions during the film growth. The structural, optical, and electrical characteristics of GZO layers, deposited from a ZnO: Ga (5.7 wt%) ceramic‐type sputtering target, are comprehensively evaluated to reveal the relationship between the sputtering geometry and material properties. The obtained electrical properties, comparatively high carrier mobility 11.3 × 101 cm2 V−1 s−1 and the lowest resistivity 1.13 × 10−3 Ω‐cm, together with a moderately high optoelectric figure of merit with the films prepared using around 6 sccm Ar‐flow rate (corresponding to around 4.92 mTorr Ar partial pressure) reveal distinct correlations between the sputtering conditions and thin film properties, providing insights into the optimization of sputtering parameters for tailored material synthesis required for advanced and emerging applications. The GZO thin film (prepared with the optimal setting of 6 sccm Ar flow rate) exhibits remarkable optoelectronic capabilities as a transport layer in solar cells, reaching peak efficiencies of 26.34% for CIGS, 14.142% for CdTe, and 24.289% for Cs2AgBiBr6 perovskite in SCAPS‐1D simulated models. This study advances sputtering techniques for precise engineering of functional nanomaterials with enhanced performance and versatility, contributing to material synthesis optimization for emerging applications.

An Interior/Exterior Collaboration-Enhanced Intestinal Anastomosis (IECIA) for Multi-Tiered Leakage Complication Management.

Anastomotic leakage (AL) is a pervasive and risky postoperative complication that presently features inaccessible prevention, delayed diagnosis, and intractable remediation, resulting in distressing morbidity and mortality. Herein an interior/exterior collaboration-enhanced neoteric intestinal anastomosis (IECIA) is developed, which consists of an interior hydrogel-based protective barrier adhering to mucosa, and exterior synergistic leakage-prevention safeguard sutured to serosa, for multi-tiered leakage complication management. Noticeably, the hydrogel barrier protects anastomosis stoma against injurious stimulation from digestive liquid, consequently reducing leakage risk effectively and comfortably in place of painful gastric tube insertion. The exterior safeguard encompassing fluorescein-loaded hydrogel and electrospun film functions as a secondary defense, exhibiting critical leakage-prevention capability to refrain from lethal intra-abdominal infection. Meanwhile, fluorescein is released to the enteric cavity for following detection within the excrement in case anastomotic leakage occurs, achieving presymptomatic alarming in providing valuable prompts for timely clinical intervention. Importantly, IECIA has been investigated in realistic in vivo end-to-end intestinal anastomosis scenarios as well as simulated leakage models, which present satisfactory postoperative recovery of gastrointestinal functions and systematic indexes. Moreover, the IECIA system is endowed with guaranteed biocompatibility, effective durability, comprehensibility for surgical operation, comfort, and compliance for patients, which demonstrates precious value for clinical translation.

On the use of meteorological parameters and satellite image-based indices for improving solar radiation estimation.

Solar radiation (Rs) is a major renewable energy source and also a crucial factor in designing solar panels, determining water requirement, and irrigation scheduling. In this study, meteorological parameters (air temperature, average air temperature, and relative humidity; Scenario 1), satellite image-based indices (normalized difference vegetation index: NDVI and land surface temperature: LST; Scenario 2), and their combination (Scenario 3) were used as predictors of Rs simulator models in Mashhad watershed (2005-2015). To this end, three different transfer function algorithms of the multi-layer perceptron (MLP), namely Levenberg-Marquardt backpropagation (MLP-LVM), gradient descend backpropagation (MLP-GDB), and batch training with weight and bias learning rules (MLP-BTWB), as well as two other machine learning models, M5 Tree and XGB (eXtreme Gradient Boosting), were employed. In addition, hybrid models obtained through coupling the best MLP transfer function with genetic algorithm (MLP-LVM-GA) and coupling Variational Mode Decomposition with M5 Tree and XGB (VMD-M5 Tree and VMD-XGB, respectively) were also investigated. In the case of MLP-based models, the third scenario proved to be more efficient, with RMSEs equal to 404.2, 424.5, and 423.8J.cm-2.day-1 for the aforementioned transfer functions, respectively. The results showed that GA coupled with the best transfer function algorithm of MLP improved Rs estimates, decreasing estimation error by 14.7, 30.65, and 32.67% in the three defined scenarios, respectively. In training set, VMD-M5 Tree and VMD-XGB hybrid models outperformed corresponding base models under all three scenarios; but in testing set, estimation error was decreased only in the third scenario (by 37 and 42%, respectively). Overall, all models (base and hybrid) had the least Rs estimation errors in the third scenario (application of both meteorological parameters and satellite image-based data).