Range Of Parameters Research Articles

A novel algorithmic approach for automatic virtual articulation to avoid dynamic interferences in dental restoration designs.

There is an ongoing debate about the benefits of the facebow and individual articulator settings in prosthodontics when compared with simpler methods. The present study aims to determine whether the implementation of novel algorithmic articulator concepts may be an alternative to avoid dynamic interference contacts during the design process of fixed posterior restorations, and to what extent the occlusal morphology of the restoration is affected. From a chairside CAD database, a total of 50 clinical patient cases documenting 61 planned fixed restorations in the posterior tooth region were selected. A common CAD software program was used for the automated knowledge-based design process. When designing the restorations, functional concepts were applied, including the pure static occlusion, the average articulation, three different articulator settings as a control, and a combination of a broad range of articulation parameters (the full range dynamic articulation). The resulting dynamic contact points were compared both visually and metrically with a monitoring software program. There is a highly significant difference in avoiding dynamic interference contacts when applying the full range dynamic articulation compared with the pure static occlusion (P < 0.001) and the average articulation (P < 0.001). Furthermore, the superimposition revealed that the surface of the restorations showed nearly no visual morphologic changes after virtually grinding-in the interpenetrating contact points. The full range dynamic articulation can be used for the design of small fixed posterior restorations to avoid most dynamic interference contacts without the need for determining individual parameters for each patient.

Experimental study and neural network model based prediction of layer thickness influence on LPBF IN625 single track geometry

The performance of interacting metal surfaces having sliding motion is enhanced by fabricating microfeatures on-top of the surfaces. Laser powder bed fusion (LPBF) is used to fabricate the microfeatures of IN625 on-top of a flat surface. In LPBF, geometrical characteristics of microfeatures are based on the energy supplied and the volume of material melted (layer thickness) at that instant of time. There is very few research reported in open literature on the effect of layer thickness on microfeatures geometry during LPBF. In this work, a series of single tracks is fabricated with different combinations of laser power and scanning speed for 75 μm, 100 μm, and 125 μm layer thickness and its effect on single track geometrical characteristics and microstructure was evaluated. It has been found that laser power and scanning speed have a significant influence on the track geometry irrespective of layer thickness. The minimum linear energy density of 2.5 J/mm is considered to fabricate the continuous track formation for investigated layer thickness. From statistical analysis, it is observed that the laser power and scanning speed shows higher contribution on track width and remelting depth, respectively. Whereas, layer thickness shows a higher influence on track height and contact angle of single track as compared to laser power and scanning speed. In 125 μm layer thickness, the volume of material melting is increased which encourages the gravity effect to deform the melt pool and produces larger track width compare to 100 μm layer thickness. Further, the cell spacing is gradually increased with layer thickness resulting increase in the solidification period. The shape controllability of the single track is significantly increased with layer thickness, but as keeps on increasing layer thickness due to the larger volume of molten metal, the melt pool losses ability to maintain convex shapes. An Artificial Neural Network (ANN) model is developed to understand the relationship between the LPBF process parameters and single track geometrical characteristics to predict the responses for a wide range of process parameters. The multiple response neural network model shows excellent agreement with experimental results with R2 value greater than 0.95.

Geothermal energy potential of basement hot springs: Case study of Ulu Slim (Perak, Malaysia)

Interest in geothermal energy as a clean, renewable and stable source of energy is mounting as part of the strive towards carbon emissions reduction and transition away from fossil fuels. Hot springs occur in locations of active hydrothermal systems that may have exploitation potential and this paper assesses the potential of Ulu Slim hot-spring, the warmest of some 60 basement hot-springs reported across Peninsular Malaysia. Available data and analogue inferences i.e., hot-spring surface temperature and flowrate, applicable ranges in geothermal gradients, geothermometer indications of source temperature, hydraulic head differences related to surface topography, indicative and tentative fault and fracture dimensions, geometry and distribution, are summarized and supplemented by conceptual hydrodynamic- and thermodynamic-model calculations to bracket the possible range in key subsurface parameters like source depth and geometry and properties of the fracture system that control extractable heat. Results are then used in another mathematical model that simulates the heat-extraction and electric power potential of hypothetical wells drilled into the hot-spring source, supported by injector wells (re-injecting the cool waste stream from the powerplant). Model outcomes suggest that premature cooling due to fluid circulation through narrow fracture/fault corridors is a significant risk. Overall, study results suggest that utilizing the geothermal heat of hot springs like Ulu Slim for electric power generation may be not so straightforward. Maybe the search for attractive geothermal locations should be less guided by hot-spring locations but instead, driven by proximity to infrastructure and electricity demand.

Simulating the tidal disruption of stars by stellar-mass black holes using moving-mesh hydrodynamics

In the centers of dense star clusters, close encounters between stars and compact objects are likely to occur. We studied tidal disruption events of main-sequence (MS) stars by stellar-mass black holes (termed μTDEs), which can shed light on the processes occurring in these clusters, including being an avenue in the mass growth of stellar-mass BHs. Using the moving-mesh hydrodynamics code AREPO, we performed a suite of 58 hydrodynamics simulations of partial μTDEs of realistic, MESA-generated MS stars by varying the initial mass of the star (0.5 M⊙ and 1 M⊙), the age of the star (zero-age, middle-age and terminal-age), the mass of the black hole (10 M⊙ and 40 M⊙), and the impact parameter (yielding almost no mass loss to full disruption). We then examined the dependence of the masses, spins, and orbital parameters of the partially disrupted remnant on the initial encounter parameters. We find that the mass lost from a star decreases roughly exponentially with increasing approach distance and that a 1 M⊙ star loses less mass than a 0.5 M⊙ one. Moreover, a more evolved star is less susceptible to mass loss. Tidal torques at the closest approach spin up the remnant very close to break-up velocity when the impact parameter is low. The remnant star can be bound (eccentric) or unbound (hyperbolic) to the black hole; hyperbolic orbits occur when the star’s central density concentration is relatively low and the black-hole-star mass ratio is high, which is the case for the disruption of a 0.5 M⊙ star. Finally, we provide best-fit analytical formulae for the aforementioned range of parameters that can be incorporated into cluster codes to model star-black-hole interaction more accurately.

Estimation of the number of motor units in the human extensor digitorum brevis using MScanFit.

Our aim was to determine the number and size parameters of EDB motor units in healthy young adults using MScanFit, a novel approach to motor unit number estimation (MUNE). Since variability in MUNE is related to compound muscle action potential (CMAP) size, we employed a procedure to document the optimal EDB electromyographic (EMG) electrode position prior to recording MUNE, a neglected practice in MUNE. Subjects were 21 adults 21-44 y. Maximum CMAPs were recorded from 9 sites in a 4 cm2 region centered over the EDB and the site with the largest amplitude was used in the MUNE experiment. For MUNE, the peroneal nerve was stimulated at the fibular head to produce a detailed EDB stimulus-response curve or "MScan". Motor unit number and size parameters underlying the MScan were simulated using the MScanFit mathematical model. In 19 persons, the optimal recording site was superior, superior and proximal, or superior and distal to the EDB mid-belly, whereas in 3 persons it was proximal to the mid-belly. Ranges of key MScanFit parameters were as follows: maximum CMAP amplitude (3.1-8.5 mV), mean SMUP amplitude (34.4-106.7 μV), mean normalized SMUP amplitude (%CMAP max, 0.95-2.3%), largest SMUP amplitude (82.7-348 μV), and MUNE (43-103). MUNE was not related to maximum CMAP amplitude (R2 = 0.09), but was related to mean SMUP amplitude (R2 = -0.19, P = 0.05). The EDB CMAP was highly sensitive to electrode position, and the optimal position differed between subjects. Individual differences in EDB MUNE were not related to CMAP amplitude. Inter-subject variability of EDB MUNE (coefficient of variation) was much less than previously reported, possibly explained by better optimization of the EMG electrode and the unique approach of MScanFit MUNE.

Prognostic Utility of Left Atrial Strain From MRI Feature Tracking in Ischemic and Nonischemic Dilated Cardiomyopathy: A Multicenter Study.

BACKGROUND. MRI-based prognostic evaluation in patients with dilated cardiomyopathy (DCM) has historically used markers of late gadolinium enhancement (LGE) and feature tracking (FT)-derived left ventricular global longitudinal strain (LVGLS). Early data indicate that FT-derived left atrial strain (LAS) parameters, including reservoir, conduit, and booster, may also have prognostic roles in such patients. OBJECTIVE. The purpose of our study was to evaluate the prognostic utility of LAS parameters, derived from MRI FT, in patients with ischemic or nonischemic DCM, including in comparison with the traditional parameters of LGE and LVGLS. METHODS. This retrospective study included 811 patients with ischemic or nonischemic DCM (median age, 60 years; 640 men, 171 women) who underwent cardiac MRI at any of five centers. FT-derived LAS parameters and LVGLS were measured using two- and four-chamber cine images. LGE percentage was quantified. Patients were assessed for a composite outcome of all-cause mortality or heart failure hospitalization. Multivariable Cox regression analyses including demographic characteristics, cardiovascular risk factors, medications used, and a wide range of cardiac MRI parameters were performed. Kaplan-Meier analyses with log-rank tests were also performed. RESULTS. A total of 419 patients experienced the composite outcome. Patients who did, versus those who did not, experience the composite outcome had larger LVGLS (-6.7% vs -8.3%, respectively; p < .001) as well as a smaller LAS reservoir (13.3% vs 19.3%, p < .001), LAS conduit (4.7% vs 8.0%, p < .001), and LAS booster (8.1% vs 10.3%, p < .001) but no significant difference in LGE (10.1% vs 11.3%, p = .51). In multivariable Cox regression analyses, significant independent predictors of the composite outcome included LAS reservoir (HR = 0.96, p < .001) and LAS conduit (HR = 0.91, p < .001). LAS booster and LGE were not significant independent predictors in the models. LVGLS was a significant independent predictor only in a model that initially included LAS booster but not the other LAS parameters. In Kaplan-Meier analysis, all three LAS parameters were significantly associated with the composite outcome (p < .001). CONCLUSION. In this multicenter study, LAS reservoir and LAS conduit were significant independent prognostic markers in patients with ischemic or nonischemic DCM, showing greater prognostic utility than the currently applied markers of LVGLS and LGE. CLINICAL IMPACT. FT-derived LAS analysis provides incremental prognostic information in patients with DCM.

Wake Formation Flow Physics and Boundary Layer Analysis on the Sides of the Isosceles Triangular Cylinder with Apex Pointing Downstream

Boundary layer interaction with downstream flow structures was numerically studied to find the region of inactivity behind an 75° isosceles triangular cylinder with apex pointing downstream at intermediate Reynolds numbers (Re = 520, 640, 840 and 1040). The Standard k-ε model in OpenFOAM was used in the study. Numerical results were validated against Particle Image Velocimetry data. Results revealed the stable region of inactivity characterized by low turbulent kinetic energy and vorticity. The onset of secondary vortex and separation point, independent of Reynolds number, was identified. The onset of the secondary vortex was located at (x = 2 mm) from the base and (y = 1.5 mm) from the apex on either side of the cylinder. The ratio of modulus of absolute primary z-component of vorticity, |ω_z^1 |, to the modulus of secondary z-component of vorticity, |ω_z^2 |, was found to be approximately equal to 1.2. This ratio is invariant of the Reynolds number of the study. These findings have practical implications. The unique properties of the inactivity region forms an ideal location that can be used for injecting fluid, placing measurement probe, active flow control and drag reduction. The research problem is formulated in the introduction. Literature is reviewed next providing the background. Details about the range of parameters, governing equations, numerical study details and software used are given in the methodology section. The results section gives the numerical results, verified by mesh refinement test and validated against experimental results. The results are finally discussed in the next section.

Uncertainty assessment of aquifer hydraulic parameters from pumping test data

Data from pumping tests is a noisy process, and therefore, performing the pumping test numerous times will not get the same drawdown values. As a consequence, various pumping experiments lead to different values for aquifer parameter estimates. The data of pumping tests are usually analyzed using traditional methods (aquifer tests and AQtesolv software), which depend on trial and error technique. During these methods, non-unique values of hydraulic parameters are selected, which usually have a high level of uncertainty. Uncertainty must be taken into account in determining aquifer parameters, especially when using groundwater models for decision makers. The main goal of this study is to build a comprehensive tool for quantifying uncertainty associated with hydraulic parameter estimation from different pumping test conditions for fully penetrating wells in confined and semi-confined aquifers. To achieve the previous objective, a FORTRAN code was developed to apply the Markov Chain Monte Carlo (MCMC) algorithm using different likelihood functions (exponential, inverse, and log). This developed tool can be used to detect the most probable range of aquifer parameters that are consistent with pumping test data with a high degree of confidence. The tool was successfully used to several hypothetical cases to demonstrate the uncertainty in the quantification of aquifer parameters and compare the findings to the standard method's results. Also, the concept was verified numerically (using Modflow program) with satisfactory results using a hypothetical case with well-known aquifer parameters. Finally, the tool was applied for actual pumping test data with good results.

Exact Insulated-Tip Fin Length Correction for Tip Convection Compensation

Abstract This study details the derivation of a length correction term for computing the heat transfer performance of one-dimensional, straight, convecting-tip fins using the insulated-tip fin solution. Use of this corrected length in the insulated-tip fin solution produces the identical heat transfer rate and temperature profile as those computed using the more complex convecting-tip fin equations. The analysis derives the length correction equation from fundamental principles and produces a simple, closed-form expression valid for all fin cross-sectional shapes. Furthermore, the valid parameter range where this length correction is applicable, and outside of which no exact length correction is possible, is quantified.

Interactive simulation and visualization of point spread functions in single molecule imaging

The point spread function (PSF) is fundamental to any type of microscopy, most importantly so for single-molecule localization techniques, where the exact PSF shape is crucial for precise molecule localization at the nanoscale. Optical aberrations and fixed fluorophore dipoles often result in non-isotropic and distorted PSFs, impairing and biasing conventional fitting approaches. Further, PSF shapes are deliberately modified in PSF engineering approaches for providing improved sensitivity, e.g., for 3D localization or determination of dipole orientation. As this can lead to highly complex PSF shapes, a tool for visualizing expected PSFs would facilitate the interpretation of obtained data and the design of experimental approaches. To this end, we introduce a comprehensive and accessible computer application that allows for the simulation of realistic PSFs based on the full vectorial PSF model. Our tool incorporates a wide range of microscope and fluorophore parameters, including orientationally constrained fluorophores, as well as custom aberrations, transmission and phase masks, thus enabling an accurate representation of various imaging conditions. An additional feature is the simulation of crowded molecular environments with overlapping PSFs. Further, our app directly provides the Cramér–Rao bound for assessing the best achievable localization precision under given conditions. Finally, our software allows for the fitting of custom aberrations directly from experimental data, as well as the generation of a large dataset with randomized simulation parameters, effectively bridging the gap between simulated and experimental scenarios, and enhancing experimental design and result validation.

Lie group and stability analysis of tangent hyperbolic fluid flow driven by a shrinking sheet

This study elaborates on the mathematical modeling of tangent hyperbolic fluid flow driven by a shrinking sheet in a porous medium. The roles of Soret-Dufour and thermal radiation are considered to model the energy and concentration equations. The primary objective is to find an appropriate similarity transformation through Lie group analysis, which helps to produce the self-similar equations from the governing nonlinear partial systems. The similarity solutions are calculated numerically using the “bvp4c” solver in Matlab. Additionally, adequate suction is required to obtain the similarity solutions. As expected, dual solutions are found within a certain range of the suction parameter. The skin friction coefficient, heat, and mass transfer rates at the sheet are observed for pertinent flow constraints of physical interest. It reveals that the dual solutions bifurcate from a critical point, and beyond this point, no solution exists. Furthermore, the branches of dual solutions on the nondimensional velocity, temperature, and concentration profiles depict different characteristics. Thus, a linear temporal stability analysis has been employed to test the flow stability, revealing that the upper branch is physically reliable. The heat transfer rate increases by 7.69% and 9.55% in the upper and lower branches, respectively, for Soret parameter changes from 0.6 to 0.9. Meanwhile, the mass transfer rate decreases by 85.30% and 324.60% in the upper and lower branches, respectively. The consequences of Weissenberg and suction parameters show an opposite character on the velocity, temperature, and concentration profiles in the upper branch.

Monitoring of multiple fabrication parameters of electrospun polymer fibers using mueller matrix analysis

Electrospun polymer fiber mats feature versatile applications in tissue engineering, drug delivery, water treatment and chemical processes. The orientation of fibers within these mats is a crucial factor that significantly influences their properties and performance. However, the analysis of fiber samples using scanning electron microscopy (SEM) has limitations such as time consumption, fixed assembly, and restricted field of vision. Therefore, a fast and reliable method for qualitative measurements of fiber orientation is required. Mueller matrix polarimetry, a well-established method for measuring orientation of chemical and biological species, was employed in this case. We investigated the effect of four important parameters of the electrospinning process, namely collector speed, applied voltage, needle-to-collector distance, and solution concentration, on fiber orientation using Mueller matrix polarimetry thus extending the range of parameters analyzed. Measurements were performed using two extreme values and a central optimized value for each fabrication parameter. Changes in matrix values were observed for each fabrication parameter, and their correlation with fiber orientation was analyzed based on the Lu-Chipman decomposition. The results were compared with SEM images, which served as the ground truth, and showed overall good agreement. In the future, the analysis of electrospun polymer fibers can be done by using Mueller matrix polarimetry as alternative to current technology and fabrication parameters, including solution concentration for the first time in this context and the production can quickly be adjusted based on the outcome of the measurements.

Linker-Preserved Iron Metal-Organic Framework-Based Lateral Flow Assay for Sensitive Transglutaminase 2 Detection in Urine Through Machine Learning-Assisted Colorimetric Analysis.

A groundbreaking demonstration of the utilization of the metal-organic framework MIL-101(Fe) as an exceptionally perceptive visual label in colorimetric lateral flow assays (LFA) is described. This pioneering approach enables the precise identification of transglutaminase 2 (TGM2), a recognized biomarker for chronic kidney disease (CKD), in urine specimens, which offers a remarkably sensitive naked-eye detection mechanism. The surface of MIL-101(Fe) was modified with oxalyl chloride, adipoyl chloride, and poly(acrylic) acid (PAA); these not only improved the labeling material stability in a complex matrix but also achieved a systematic control in the detection limit of the TGM2 concentration using our LFA platform. The advanced LFA with the MIL-101(Fe)-PAA label can detect TGM2 concentrations down to 0.012, 0.009, and 0.010 nM in Tris-HCl buffer, urine, and desalted urine, respectively, which are approximately 55-fold lower than those for a conventional AuNP-based LFAs. Aside from rapid TGM2 detection (i.e., within 20 min), the performance of the MIL-101(Fe)-PAA-based LFA on reproducibility [coefficients of variation (CV) < 2.9%] and recovery (95.9-103.2%) along with storage stability within 25 days of observation (CV < 6.0%) shows an acceptable parameter range for quantitative analysis. A sophisticated sensing method grounded in machine learning principles was also developed, specifically aimed at precisely deducing the TGM2 concentration by analyzing immunoreaction sites. More importantly, our developed LFA offers potential for clinical measurement of TGM2 concentration in normal human urine and CKD patients' samples.

Neural criticality from effective latent variables.

Observations of power laws in neural activity data have raised the intriguing notion that brains may operate in a critical state. One example of this critical state is 'avalanche criticality', which has been observed in various systems, including cultured neurons, zebrafish, rodent cortex, and human EEG. More recently, power laws were also observed in neural populations in the mouse under an activity coarse-graining procedure, and they were explained as a consequence of the neural activity being coupled to multiple latent dynamical variables. An intriguing possibility is that avalanche criticality emerges due to a similar mechanism. Here, we determine the conditions under which latent dynamical variables give rise to avalanche criticality. We find that populations coupled to multiple latent variables produce critical behavior across a broader parameter range than those coupled to a single, quasi-static latent variable, but in both cases, avalanche criticality is observed without fine-tuning of model parameters. We identify two regimes of avalanches, both critical but differing in the amount of information carried about the latent variable. Our results suggest that avalanche criticality arises in neural systems in which activity is effectively modeled as a population driven by a few dynamical variables and these variables can be inferred from the population activity.

Metallurgical, mechanical, and corrosion behavior of AISI 304L joints welded using variable arc energy inputs and subjected to thermal aging

The effect of three levels of welding arc energy input on the metallurgical, mechanical, and corrosion behavior of AISI 304L stainless steel was studied with the aim of investigating and recommending the most useful range of process parameters for improved performance of engineering structures made from this industrially important alloy. The gas tungsten arc welding process was employed, and all the joints were butt-welded using a single-V groove design. With an increase in heat input, the δ-ferrite phase changed from lathy to vermicular, besides the heat-affected zones of all the welds exhibiting grain coarsening effects. Postweld thermal aging led to the preferential occurrence of carbides in the interdendritic regions, which degraded their corrosion performance. Thermal aging did not affect the tensile strength of these welds, but their ductility was significantly impacted. The extent of segregation of Cr and C, especially, was observed to be the least in the case of low heat input welds. This study establishes that while designing welding procedures for AISI 304L structures, low welding arc energy should be used as it promotes better mechanical as well as corrosion properties.

Double-diffusive mixed convection in an inclined square cavity filled with nanofluid: A numerical study with external magnetic field and heated square blockage effects

This study explores the influence of Fe3O4 – water nanofluid, magnetic forces, and double-diffusive mixed convection characteristics on a steady-state, two-dimensional, laminar flow within an inclined square cavity containing four heated square blockages. The governing equations are solved using the Finite Volume Method (FVM). In this configuration, the temperature and concentration inside the square blockages are higher than those on the left and right walls, which are moving in opposite directions to each other. The remaining two are adiabatic and impermeable. A wide range of parameters is investigated, including cavity nanoparticle volume fractions (φ = 0.0, 0.02, 0.04, 0.06), inclination angle (γ = 0°, 30°, 60°), Richardson number (Ri = 0.1, 1.0, 10), Hartmann number (Ha = 0, 50, 100), heated block ratio (B = 1/8), Lewis number (Le = 5.0), Prandtl number (Pr = 0.71), and Buoyancy ratio (N = 2.0). The study extensively analyzes temperature, concentration, and streamline contours based on these parameters. Furthermore, the research examines the heat and mass transfer rates on the heated block surfaces by analyzing local and average Nusselt (Nuavg) and Sherwood numbers (Shavg). The results suggest that introducing nanofluid has a more pronounced influence on the flow fields than the temperature and concentration patterns. Both the inclination angle and the Hartmann number have a significant impact on both the flow and temperature patterns. At higher Ri, an increase in φ reduces the Nuavg and Shavg. However, the total Nuavg and Shavg decrease at any Ri and γ in a magnetic field.

The role of heterogeneity in autonomous perimeter defense problems

When is heterogeneity in the composition of an autonomous robotic team beneficial and when is it detrimental? We investigate and answer this question in the context of a minimally viable model that examines the role of heterogeneous speeds in perimeter defense problems, where defenders share a total allocated speed budget. We consider two distinct problem settings and develop strategies based on dynamic programming and on local interaction rules. We present a theoretical analysis of both approaches and our results are extensively validated using simulations. Interestingly, our results demonstrate that the viability of heterogeneous teams depends on the amount of information available to the defenders. Moreover, our results suggest a universality property: across a wide range of problem parameters the optimal ratio of the speeds of the defenders remains nearly constant.

A Comparative Study of Embedded Wall Displacements Using Small-Strain Hardening Soil Model

Traditional analysis of embedded earth-retaining walls relies on simplistic lateral earth pressure theory methods, which do not allow for direct computation of wall displacements. Contemporary numerical models rely on the Mohr–Coulomb model, which generally falls short of accurate wall displacement prediction. The advanced constitutive small-strain hardening soil model (SS-HSM), effectively captures complex nonlinear soil behavior. However, its application is currently limited, as SS-HSM requires multiple input parameters, rendering numerical modeling a challenging and time-consuming task. This study presents an extensive numerical investigation, where wall displacements from numerical models are compared to empirical findings from a large and reliable database. A novel automated computational scheme is created for model generation and advanced data analysis is undertaken for this objective. The main findings indicate that the SS-HSM can provide realistic predictions of wall displacements. Ultimately, a range of input parameters for the utilization of SS-HSM in earth-retaining wall analysis is established, providing a good starting point for engineers and researchers seeking to model more complex scenarios of embedded walls with the SS-HSM.

Research on a Vibrationally Tuned Directional Seed Supply Method Based on ADAMS-EDEM Coupling and the Optimization of System Parameters

We have combined the theory of bulk dynamics and the agronomic requirements of precision sowing with the aim of resolving the technical problems of poor seed mobility and the difficulty in controlling suction posture, which leads to an increase in the leakage rate and a reduction in seed qualification index scores. In this study, a vibrationally tuned directional seed supply method and system are proposed. We carried out a force analysis of seeds, constructed kinematic equations for seeds and seed boxes to specify the state of the seed motion, and determined the structural parameters and the range of structural parameters that affect the seed suction posture. In addition, we coupled the ADAMS-EDEM simulation of the motion process of the seed and seed boxes and analyzed the vibrational tuning process of the seeds and the angle of inclination of the bottom surface of the seed box. The speed of the eccentric wheel and the eccentric distance were used as test factors. Three-factor and three-level Box–Behnken central combination testing with a single-grain rate, multiple-grain rate, and cavity rate were used as response indicators. Mathematical models were obtained between the experimental factors and the response indicators. Multi-objective optimization of mathematical regression models was carried out with Design-Expert 10.0.4 software. The optimal parameter combination obtained was a tilt angle of 14.27°, an eccentric wheel speed of 4.48 rad/s, and an eccentricity of 1.94 mm. The rate of single grains was 90.75%, the rate of multiple grains was 3.63%, and the rate of cavities was 5.62%. In bench performance tests, using an angle of inclination of 14°, the speed of the eccentric wheel was 4.50 rad/s and the eccentricity was 2 mm. The mean value of the single-grain rate was 89.28%, the mean value of the multiple-grain rate was 3.89%, and the mean value of the cavity rate was 6.83%. The test error was within permissible limits, and reliable results were achieved for parameter optimization. The results met the technical requirements for precision sowing. The results of the study can provide academic references for theoretical research on the methodology of posturing and directional seed supply. They can also provide ideas for the design and development of seed supply systems for precision sowing machinery.

Building Water Models Compatible with Charge Scaling Molecular Dynamics.

Charge scaling has proven to be an efficient way to account in a mean-field manner for electronic polarization by aqueous ions in force field molecular dynamics simulations. However, commonly used water models with dielectric constants over 50 are not consistent with this approach leading to "overscaling", i.e., generally too weak ion-ion interactions. Here, we build water models fully compatible with charge scaling, i.e., having the correct low-frequency dielectric constant of about 45. To this end, we employ advanced optimization and machine learning schemes in order to explore the vast parameter space of four-site water models efficiently. As an a priori unwarranted positive result, we find a sizable range of force field parameters that satisfy the above dielectric constant constraint providing at the same time accuracy with respect to experimental data comparable with the best existing four-site water models such as TIP4P/2005, TIP4P-FB, or OPC. The present results thus open the way to the development of a consistent charge scaling force field for modeling ions in aqueous solutions.