Choice Of Parameters Research Articles

Using muscle-tendon load limits to assess unphysiological musculoskeletal model deformation and Hill-type muscle parameter choice.

Musculoskeletal simulations are a useful tool for improving our understanding of the human body. However, the physiological validity of predicted kinematics and forces is highly dependent upon the correct calibration of muscle parameters and the structural integrity of a model's internal skeletal structure. In this study, we show how ill-tuned muscle parameters and unphysiological deformations of a model's skeletal structure can be detected by using muscle elements as sensors with which modelling and parameterization inconsistencies can be identified through muscle and tendon strain injury assessment. To illustrate our approach, two modelling issues were recreated. First, a model repositioning simulation using the THUMS AM50 occupant model version 5.03 was performed to show how internal model deformations can occur during a change of model posture. Second, the muscle material parameters of the OpenSim gait2354 model were varied to illustrate how unphysiological muscle forces can arise if material parameters are inadequately calibrated. The simulations were assessed for muscle and tendon strain injuries using previously published injury criteria and a newly developed method to determine tendon strain injury threshold values. Muscle strain injuries in the left and right musculus pronator teres were detected during the model repositioning. This straining was caused by an unphysiologically large gap (12.92 mm) that had formed in the elbow joint. Similarly, muscle and tendon strain injuries were detected in the modified right-hand musculus gastrocnemius medialis of the gait2354 model where an unphysiological reduction of the tendon slack length introduced large pre-strain of the muscle-tendon unit. The results of this work show that the proposed method can quantify the internal distortion behaviour of musculoskeletal human body models and the plausibility of Hill-type muscle parameter choice via strain injury assessment. Furthermore, we highlight possible actions to avoid the presented issues and inconsistencies in literature data concerning the material characteristics of human tendons.

On the Peculiarities of Wire-Feed Electron Beam Additive Manufacturing (WEBAM) of Nickel Alloy–Copper Bimetal Nozzle Samples

In order to gain insight into the unique characteristics of manufacturing large-scale products with intricate geometries, experimental nozzle-shaped samples were created using wire-feed electron beam additive technology. Bimetal samples were fabricated from nickel-based alloy and copper. Two distinct approaches were employed, utilizing varying substrate thicknesses and differing fabrication parameters. The two approaches were the subject of analysis and comparison through the examination of the surface morphology of the samples using optical microscopy, scanning electron microscopy, and X-ray diffraction analysis. It has been demonstrated that the variation in heat flux distributions resulting from varying the substrate thicknesses gives rise to the development of disparate angles of grain boundary orientation relative to the substrate. Furthermore, it is demonstrated that suboptimal choice of the fabrication parameters results in large disparities in the crystallization times, both at the level of sample as a whole and within the same material volume. For example, for the sample manufacturing by Mode I, the macrostructure of the layers is distinguished by the presence of non-uniformity in their geometric dimensions and the presence of unmelted wire fragments. In order to characterize the experimental nozzle-shaped samples, microhardness was measured, uniaxial tensile tests were performed, and thermal diffusivity was determined. The microhardness profiles and the mechanical properties exhibit a higher degree of strength than those observed in pure copper samples and a lower degree of strength than those observed in Inconel 625 samples obtained through the same methodology. The thermal diffusivity values of the samples are sufficiently close to one another and align with the properties of the corresponding materials in their state after casting or rolling. The data discussed above indicate that Mode II yields the optimal mechanical properties of the sample due to the high cooling rate, which influences the structural and phase state of the resulting products. It was thus concluded that the experimental samples grown by Mode II on a thinner substrate exhibited the best formability.

Empirically exploring the space of monostationarity in dual phosphorylation

AbstractThe dual phosphorylation network provides an essential component of intracellular signaling, affecting the expression of phenotypes and cell metabolism. For particular choices of kinetic parameters, this system exhibits multistationarity, a property that is relevant in the decision-making of cells. Determining which reaction rate constants correspond to monostationarity and which produce multistationarity is an open problem. The system’s monostationarity is linked to the nonnegativity of a specific polynomial. A previous study by Feliu et al. provides a sufficient condition for monostationarity via a decomposition of this polynomial into nonnegative circuit polynomials. However, this decomposition is not unique. We extend their work by a systematic approach to classifying such decompositions in the dual phosphorylation network. Using this classification, we provide a qualitative comparison of the decompositions into nonnegative circuit polynomials via empirical experiments and improve on previous conditions for the region of monostationarity.

Theoretically grounded approaches to account for polarization effects in fixed-charge force fields.

Non-polarizable, or fixed-charge, force fields are the workhorses of most molecular simulation studies. They attempt to describe the potential energy surface (PES) of the system by including polarization effects in an implicit way. This has historically been done in a rather empirical and ad hoc manner. Recent theoretical treatments of polarization, however, offer promise for getting the most out of fixed-charge force fields by judicious choice of parameters (most significantly the net charge or dipole moment of the model) and application of post facto polarization corrections. This Perspective describes these polarization theories, namely the "halfway-charge" theory and the molecular dynamics in electronic continuum theory, and shows that they lead to qualitatively (and often, quantitatively) similar predictions. Moreover, they can be reconciled into a unified approach to construct a force field development workflow that can yield non-polarizable models with charge/dipole values that provide an optimal description of the PES. Several applications of this approach are reviewed, and avenues for future research are proposed.

Transfer learning for accurate description of atomic transport in Al-Cu melts.

Machine learning interatomic potentials (MLIPs) provide an optimal balance between accuracy and computational efficiency and allow studying problems that are hardly solvable by traditional methods. For metallic alloys, MLIPs are typically developed based on density functional theory with generalized gradient approximation (GGA) for the exchange-correlation functional. However, recent studies have shown that this standard protocol can be inaccurate for calculating the transport properties or phase diagrams of some metallic alloys. Thus, optimization of the choice of exchange-correlation functional and specific calculation parameters is needed. In this study, we address this issue for Al-Cu alloys, in which standard Perdew-Burke-Ernzerhof (PBE)-based MLIPs cannot accurately calculate the viscosity and melting temperatures at Cu-rich compositions. We have built MLIPs based on different exchange-correlation functionals, including meta-GGA, using a transfer learning strategy, which allows us to reduce the amount of training data by an order of magnitude compared to a standard approach. We show that r2SCAN- and PBEsol-based MLIPs provide much better accuracy in describing thermodynamic and transport properties of Al-Cu alloys. In particular, r2SCAN-based deep machine learning potential allows us to quantitatively reproduce the concentration dependence of dynamic viscosity. Our findings contribute to the development of MLIPs that provide quantum chemical accuracy, which is one of the most challenging problems in modern computational materials science.

BioRxToolbox: A computational framework to streamline genetic circuit design in molecular data communications

ABSTRACT Developments in bioengineering and nanotechnology have ignited the research on biological and molecular communication systems. Despite potential benefits, engineering communication systems to carry data signals using biological messenger molecules and engineered cells is challenging. Diffusing molecules may fall behind their schedule to arrive at the receiver, interfering with symbols of subsequent time slots and distorting the signal. Existing theoretical molecular communication models often focus solely on the characteristics of a communication channel and fail to provide an end-to-end system response since they assume a simple thresholding process for a receiver cell and overlook how the receiver can detect the incoming distorted molecular signal. In this paper, we present a model-based and computational framework called BioRxToolbox for designing diffusion-based and end-to-end molecular communication systems coupled with synthetic genetic circuits. We describe a novel framework to encode information as a sequence of bits, each transmitted from the sender as a burst of molecules, control cellular behavior at the receiver, and minimize cellular signal interference by employing equalization techniques from communication theory. This approach allows the encoding and decoding of data bits efficiently using two different types of molecules that act as the data carrier and the antagonist to cancel out the heavy tail of the former. Here, BioRxToolbox is demonstrated using a biological design and computational simulations for various communication scenarios. This toolbox facilitates automating the choice of communication parameters and identifying the best communication scenarios that can produce efficient cellular signals.

DETERMINATION OF DIAGNOSTIC REFERENCE LEVEL (DRL) AND STUDY OF EXPOSURE PARAMETER SELECTION IN HEAD AND ABDOMEN CT SCAN AT BANGIL REGIONAL HOSPITAL

A study has been conducted to determine the local diagnostic reference level (DRL) value of CT scans at Bangil Regional Hospital. The determination and calculation of the DRL value are based on the measurement of the patient's dose, namely using the CT scan examination results in the form of CTDIVol values and DLP values. The DRL value is determined from the CTDIVol and DLP data distribution in quartile 3. Patient dose data uses a Toshiba 16-slice CT scan and a Canon 160-slice CT scan. Seven hundred twenty data were obtained, distinguished by 680 adults and 40 children. The local DRL value at Bangil Regional Hospital for CT scans of the Head without contrast for the adult group CTDIVol 47.5 mGy and DLP 1162 mGy.cm. CT scans of the Head with contrast for the adult group CTDIVol 47.22 mGy and DLP 2784.38 mGy.cm. DRL on CT scan Abdomen without contrast adult age group at Bangil Hospital CTDIVol 3.7 mGy and DLP 179.9 mGy.cm. CT scan of Abdomen with contrast CTDIVol 3.9 mGy and DLP 774.92 mGy.cm. When compared to the National DRL value, this value is still below the National DRL value. However, the nature of DRL is dynamic, so each period is expected to be lower. Efforts should focus on achieving lower DRL values by considering the selection of parameters and the skills of radiographers that influence the dose administered to patients. Values that exceed the DRL value are evaluated using the choice of parameters. Factors that affect the DRL value include kV, mAs, rotation time, pitch, iterative reconstruction, and number of phases. The parameters used in CT scans at Bangil Hospital must be adjusted to provide optimal doses to patients. Keywords: diagnostic reference level (DRL), dose length product (DLP), CT dose index (CTDI), CT Head, CT Abdomen, dose delivery parameters.

Third-Order Differential Subordination Features of Meromorphic Functions: Erdelyi–Kober Model Integral Operator Application

This study is concerned with the class of p-valent meromorphic functions, represented by the series f(ζ)=ζ−p+∑k=1−p∞dkζk, with the domain characterized by 0<|ζ|<1. We apply an Erdelyi–Kober-type integral operator to derive two recurrence relations. From this, we draw specific conclusions on differential subordination and differential superordination. By looking into suitable classes of permitted functions, we obtain various outcomes, including results analogous to sandwich-type theorems. The operator used can provide generalizations of previous operators through specific parameter choices, thus providing more corollaries.

Effect of Einasto spike on the gravitationally decoupled self-gravitating dark matter halos

Abstract In this work, we consider the possibility of constructing gravitationally bound, charged dark matter halos motivated by Einasto density model. This model generalizes the concept of charged, non-commutative mini-compact objects by including dark matter as its primary component through the principles of the minimal geometric deformation strategy. We point out that the coupling of the non-commutativity inspired Einasto spike density model with a non-isotropic fluid, within the context of gravitational decoupling allows the formation of different minimally deformed dark matter halos, corresponding to each value of the deformation parameter. We assume the Tolman-Kuchowicz cosmological model as a seed metric within the geometric deformation scheme to initially generate an electrically charged isotropic solution. Subsequently, we employ a density-like constraint to produce a second anisotropic charged dark matter stellar model via the Einasto density profile. A complete graphical analysis of the structural variables and stability of both models indicate that, for the considered choice of parameters, both cosmological models are well-behaved, exhibiting expected physical behavior.

Does Price Personalization Ethically Outperform Unitary Pricing? A Thought Experiment and a Simulation Study

AbstractMerchants often use personalized pricing: they charge different consumers different prices for the same product. We assess the ethicality of personalized pricing by generalizing and extending an earlier model by Coker and Izaret (Journal of Business Ethics 173:387–398, 2021) who found that price personalization ethically outperforms unitary pricing. Using a simulation analysis, we show that these results crucially depend on the choice of parameters and do not hold universally. We further incorporate additional sources of marginal cost into the utility function that will likely arise from personalized pricing. These include the expectation that personalized pricing is widely considered unfair by consumers who prefer that all consumers are charged the same price (unitary pricing), and that firms often approximate the consumers’ willingness-to-pay in ways that may raise negative sentiments among consumers who feel that their privacy is breached. By extending our model with disutility from unfairness perception and disutility from surveillance aversion, we demonstrate that personalized pricing is quickly outperformed by unitary pricing under social welfare functions that tend to prioritize total utility (utilitarianism and prioritarianism), whereas personalized pricing can ethically outperform unitary pricing under social welfare functions that tend to prioritize equality (egalitarianism and leximin). Our findings illustrate various intricacies and dynamics regarding the circumstances under which personalized pricing can be considered ethical.

An investigation of firm size distributions involving the growth functions

Following the ideas of prospect theory, a class of growth functions is used to characterize deterministic variations of firm size, which portrays the asymmetric efforts of the firm to achieve the desired size. Considering the differences in the ability of different firm size to cope with uncertainties, the Boltzmann equation for the evolution of firm size is constructed. Utilizing a suitable scaling limit, the Fokker–Planck equation is acquired and its explicit steady-state solution is derived. Our results illustrate that different choices of parameters in the growth function lead to various statistical laws for firm size, such as the Amoroso distribution, the lognormal distribution and Zipf’s law. Under certain conditions, inequality for the distribution of firm size decreases as firm size increases. The numerical analyses are presented to illustrate our results.

Investigation of the aerodynamic performance of the dragonfly-inspired tandem wings considering the coupling between the stroke plane and phase difference

The dragonfly's tandem wings can make full use of the interference of various spatial vortices to obtain efficient flight capability. The complex coupling among multiple motion parameters will have an important influence on the interference between the forewing (FW) and hindwing (HW). In this paper, the aerodynamic performance of the dragonfly-inspired tandem wings is analyzed using the Computational Fluid Dynamics (CFD) method considering the coupling effect of the stroke plane and phase difference. The variation of the force coefficient, vortex structure and aerodynamic efficiency of the tandem wings in forward flight are analyzed, respectively. The results show that the stroke plane angle affects the distribution of the leading edge vortex (LEV) and trailing edge vortex (TEV), which primarily controls the trend of horizontal force variation. The phase difference of tandem wings will change the fluctuation of the horizontal force coefficient curve by affecting the meeting time of the forewing and hindwing. However, with the increase of stroke plane angle, the fluctuation of aerodynamic coefficient caused by phase difference will decrease. The propulsion efficiency(η) and power loading(PL) can be improved through increasing the stroke plane angle and selecting a reasonable phase difference. The conclusion can provide theoretical guidance for the design of the dragonfly-inspired tandem flapping wing aircraft (DTFWA) and the choice of motion parameters.

Sensitivity-Aware Density Estimation in Multiple Dimensions.

We formulate an optimization problem to estimate probability densities in the context of multidimensional problems that are sampled with uneven probability. It considers detector sensitivity as an heterogeneous density and takes advantage of the computational speed and flexible boundary conditions offered by splines on a grid. We choose to regularize the Hessian of the spline via the nuclear norm to promote sparsity. As a result, the method is spatially adaptive and stable against the choice of the regularization parameter, which plays the role of the bandwidth. We test our computational pipeline on standard densities and provide software. We also present a new approach to PET rebinning as an application of our framework.

Testing Astronomical Solutions With Geological Data for the Latest Cretaceous: An Astronomically Tuned Time Scale

AbstractAstronomical solutions form the backbone of accurate dating for geology and paleoclimate studies. Beyond 50 Ma, however, the chaos inherent in the solar system makes it impossible to calculate a unique astronomical solution. Geological data have been used to constrain the chaos in order to arrive at an astronomically calibrated time scale up to the end‐Cretaceous. Here, we adopt and extend this approach into the latest Cretaceous, by re‐analyzing the Zumaia and Sopelana composite proxy records from the Maastrichtian. We find that the filtered total light reflectance () record is most compatible with the astronomical solution ZB20a. However, the results are sensitive to parameter choices in our algorithm, which we describe in detail. Nevertheless, we present evidence in favor of using solution ZB20a for cyclostratigraphic applications during the latest Cretaceous. Intervals with very long eccentricity nodes (VLNs) (low amplitude in the short eccentricity cycle) in the astronomical solutions that coincide with large amplitudes in the short eccentricity‐related peaks in the filtered proxy record rule out alternatives.

Influence of Gas Oven Temperature on the Microstructure and Extrudability of Al-Mg-Si Aluminium Alloys

The microstructure of Al-Mg-Si aluminium alloys is well characterised when it comes to the initial state of the cast billet or the artificially aged profile. Typically, a gas oven coupled with an induction oven is used to preheat the billets before extrusion. Preheating reduces the flow stress of the aluminium and dissolves the phases that have precipitated during cooling after homogenisation. In this paper, the influence of the gas oven temperature on the partial or complete dissolution of the precipitated phases will be shown. In addition, the negative effect of a wrong choice of parameters on the volume content of the MgSi phases will be shown.

STUDY OF OCTUPOLE DEFORMATION OF NUCLEI IN CHAIN OF ISOTONS IN THE REGION OF ACTINIDES IN THE MEAN FIELD APPROXIMATION

Calculations of the properties of even-even isotones N = 134 of nuclei with Z = 86–96 were carried out in the Hartree-Fock-Bogolyubov approximation, taking into account the axial symmetry of nuclei with forces Skyrme (SkM*, SLy4). Pairing of nucleons in nuclei is described by zero-range pairing forces of mixed type with different sets of pairing force constants. In the calculations we used constrained conditions on the parameters of the quadrupole and octupole deformations of the nuclei. It is shown that for the considered chain of isotones the octupole deformation of nuclei strongly depends on the choice of parameters of the nucleon pairing force and weakly depends on the type of parameterization of the Skyrme forces used in this study.

Hybrid star model with Tolman–Buchdahl metric potentials in non-conservative theory of gravity

In this study, we propose a streamlined approach to analyze the characteristics of compact stars with a unique equation of state resulting from the hybridization of dark matter and baryonic matter within the framework of Rastall gravity. The impact of dark energy on the star’s interior is investigated by introducing a linear coupling parameter β (called the Rastall parameter). The interior space–time model is developed using metric potentials eν=A+Br2 and eλ(r)=a(1+br2)a−br2 for temporal and spatial coordinates, respectively. The parameter b is set to 0.005 km−2 for the specific stellar candidate PSRJ1614-2230. Physical features derived from the exact solutions of the Einstein field equations are analyzed by considering various choices of the Rastall parameter. The results indicate that the proposed model satisfies the necessary conditions for a stable and physically plausible stellar structure.

A Space Distributed Model and Its Application for Modeling the COVID-19 Pandemic in Ukraine

A space distributed model based on reaction–diffusion equations, which was previously developed, is generalized and applied to COVID-19 pandemic modeling in Ukraine. Theoretical analysis and a wide range of numerical simulations demonstrate that the model adequately describes the second wave of the COVID-19 pandemic in Ukraine. In particular, comparison of the numerical results obtained with the official data shows that the model produces very plausible total numbers of the COVID-19 cases and deaths. An extensive analysis of the impact of the parameters arising from the model is presented as well. It is shown that a well-founded choice of parameters plays a crucial role in the applicability of the model.

Refining software defect prediction through attentive neural models for code understanding

Identifying defects through manual software testing is a resource-intensive task in software development. To alleviate this, software defect prediction identifies code segments likely to contain faults using data-driven methods. Traditional techniques rely on static code metrics, which often fail to reflect the deeper syntactic and semantic features of the code. This paper introduces a novel framework that utilizes transformer-based networks with attention mechanisms to predict software defects. The framework encodes input vectors to develop meaningful representations of software modules. A bidirectional transformer encoder is employed to model programming languages, followed by fine-tuning with labeled data to detect defects. The performance of the framework is assessed through experiments across various software projects and compared against baseline techniques. Additionally, statistical hypothesis testing and an ablation study are performed to assess the impact of different parameter choices. The empirical findings indicate that the proposed approach can increase classification accuracy by an average of 15.93% and improve the F1 score by up to 44.26% compared to traditional methods.

Techno-economic optimization and feasibility of PCM-based seasonal thermal energy storage systems for district heating and cooling

Phase change materials (PCM) are an attractive seasonal thermal energy storage solution for load shifting due to relatively high energy density. Nevertheless, the choice of the right design parameters, such as storage size and phase-change temperature, is nontrivial, as these are tightly linked to the expected seasonal operation of the storage. This paper presents a combined design and operation optimization framework for sizing PCM-based seasonal thermal storage, which can capture dynamic behaviour of the storage in sensible and latent phases, and its impact on the efficiency of connected heat pumps and chillers. The proposed method, formulated as a mixed integer quadratically-constrained programming problem, was applied to a case study of heating-dominated district. It was found that the optimal PCM melting temperature equals to the heating demand supply temperature, thus removing the need of a heat pump to discharge the storage. The optimal operation of storage requires a full charging and discharging cycle of both latent and liquid phase. Higher CO2 emission price does not lead to a significant reduction of CO2 emissions, but the storage size does, leading to a higher heating coverage ratio of the storage, and consequently CO2 emissions and cost savings, which can be further enhanced with PV integration. The economic analysis indicates that, unless other benefits such as storage volume reduction are accounted for, PCM cost should drop by a factor 4 to make this solution economically viable for seasonal storage.