Form Of Kernel Research Articles

Peningkatan Kadar Protein Terlarut pada Larutan Tepung Jagung Menggunakan Saccharomyces cerevisiae

Poultry livestock are generally given feed in the form of corn kernels where the corn kernels contain high carbohydrates but have deficiencies of several amino acids. Amino acid deficiency can be overcome by increasing the protein content in the corn kernels. One way to increase the protein content in corn kernels is to carry out a fermentation process in corn flour solution. Therefore, this study aims to determine the effect of corn starch solution to increase dissolved protein levels in Saccharomyces cerevisiae biomass through a fermentation process. This study used a completely randomized design consisting of 8 treatments and 3 replications. The treatment volumes of corn flour solution were 0 mL, 5 mL, 10 mL, 15 mL, 20 mL, 25 mL, 30 mL and 35 mL. Data analysis used the calculation of variance and the BJND test. The results showed that the highest average dissolved protein content and total cell biomass of S. cerevisiae in the 15 ml treatment were 13.52%/g and 15.63 x 107 CFU/mL, the lowest average was in the 35 ml corn flour solution treatment, namely 0. 90%/gr and 3.01 x 107 CFU/mL. Based on the research, it can be concluded that corn flour solution can increase the dissolved protein content in S. cerevisiae biomass up to volume 15 mL/2 mL fermenter through the fermentation process. Based on the results of this study, it can be used as a basis for considering the use of S. cerevisiae fermenters to increase the nutritional value of corn seed-based animal feed.

Blind Nonparametric Estimation of SISO Continuous-time Systems

Blind system identification is aimed at finding parameters of a system model when the input is inaccessible. In this paper, we propose a blind system identification method that delivers a single-input single-output, continuous-time model in a nonparametric kernel form. We take advantage of the representer theorem to form a joint maximum a posteriori estimator of the input and system impulse response. The identified system model and input are optimised in sequence to overcome the blind problem with generalised cross validation used to select appropriate hyperparameters given some fixed input sequence. We demonstrate via Monte Carlo simulations the accuracy of the method in terms of estimating the input.

Geometric singular perturbation of a nonlocal partially degenerate model for <i>Aedes aegypti</i>

<p style='text-indent:20px;'>This paper is devoted to investigate the existence of traveling wave solutions for a partially degenerate <i>Aedes aegypti</i> model with nonlocal effects. By taking specific kernel forms and time scale transformation, we transform the nonlocal model into a singularly perturbed system with small parameters. A locally invariant manifold for wave profile system is obtained with the aid of the geometric singular perturbation theory, and then the existence of traveling wave solutions is proved provided that the basic reproduction number <inline-formula><tex-math id="M1">\begin{document}$ \mathcal{R}_0>1 $\end{document}</tex-math></inline-formula> through utilizing the Fredholm orthogonal method. Furthermore, we study the asymptotic behaviors of traveling wave solution with the help of asymptotic theory. The methods used in this work can help us overcome the difficulty that the solution map associated with the system is not compact. Numerically, we perform simulations to demonstrate the theoretical results.</p>

CONSUMPTION OF CASHEW KERNEL-BASED FOOD PRODUCTS AND ITS NUTRITIONAL POTENTIALITIES

Background: Ivory Coast is the first country producer and the third exporter cashew kernel in world. Consumption of cashew kernels remains popular and present in Ivorian eating habits. However, the form, moment, nutritional and microbiological characteristics have not been explored much.
 Aim of Study: This study aimed to determine the form, moment, nutriment, and microbial content of cashew kernels consumed.
 Materials and Methods: A survey has been carried out to determine the most widely consumed form and moment of consumption of cashew kernel. The physicochemical, biochemical, and microbiological parameters of roasted cashew kernels were analyzed.
 Results: The results showed that 74.5% of respondents consumed cashew kernels under roasted form and 87.5% used it as snack. The energy, carbohydrate, fat, moisture, fiber, Iron and Magnesium showed significant difference (P<0.05) between the samples. The microbiological analysis of the roasted cashew kernels samples showed that only mesophilic aerobic germ wers were found with a load of 2.46 ±0.05 (Log CFU/g) and 2.51±0.07 (Log CFU/g) for cashew supermarket (CKS) and cashew kernel local market (CKM) respectively.
 Conclusion: In sum, from the microbiological point of view, the roasted cashew kernels samples both were acceptable quality.

Explicit analytical form for memory kernel in the generalized Langevin equation for end-to-end vector of Rouse chains.

The generalized Langevin equation (GLE) provides an attractive theoretical framework for investigating the dynamics of conformational fluctuations of polymeric systems. While the memory kernel is a central function in the GLE, explicit analytical forms for this function have been challenging to obtain, even for the simple models of polymer dynamics. Here, we achieve an explicit analytical expression for the memory kernel in the GLE for the end-to-end vector of Rouse chains in the overdamped limit. Our derivation takes advantage of the finding that the dynamics of the end-to-end vector of Rouse chains with both free ends are equivalent to those of Rouse chains with one free end and the other fixed. For the latter model, we first show that the equations of motion of the Rouse modes as well as their statistical properties can be obtained under the boundary conditions where the free end is held fixed temporarily. We then analytically solve the terms associated with intrachain interactions in the GLE. By formally comparing these terms with the GLE based on the Rouse modes, we obtain an explicit expression for the memory kernel, along with analytical forms for the potential field and the random colored noise force. Our analytical memory kernel is confirmed by numerical calculations in the Laplace space and is shown to yield asymptotic behaviors that are consistent with previous studies. Finally, we utilize our analytical result to simulate the cyclization dynamics of Rouse chains and discuss the scaling of the cyclization time with chain length.

A Novel Combinatoric Correntropy Algorithm: Properties and its Performance Analysis

In order to improve the flexibility of the correntropy that is usually in the form of a single kernel, this brief proposes a novel combinatoric maximum correntropy criterion (C-MCC), where the combinatoric correntropy (C-C) consists of two different single-type kernels. As a new form of correntropy, the C-C has a more generalized form than the traditional single-kernel correntropy, and the corresponding properties and proofs of the C-C are given in this brief. It is noticed that the combined kernel can become a single kernel by changing the combined parameters. Moreover, the adaptive filtering algorithm based on C-MCC is derived and the theoretical performance analysis of the C-MCC algorithm is also provided. Finally, the experimental simulations show that the proposed algorithm has better convergence speed and steady-state performance than MCC-type and other algorithms, and the proposed method of the theoretical analysis of C-MCC agrees well with simulation results.

Computational Fluid Dynamics Model for Analysis of the Turbulent Limits of Hydrogen Combustion

This paper presents a novel numerical approach for assessing the turbulent limits of hydrogen combustion. In the framework of this approach, the premixed combustion is studied numerically in the externally generated turbulent field with defined parameters. Two-dimensional calculations are carried out for hydrogen–air mixtures of different compositions, and all the possible modes of near-limit combustion are reproduced. Among these modes are: combustion in the form of spatially separated individual kernels and combustion in the form of kernels with subsequent quenching. The critical conditions between the mentioned two modes correspond to the turbulent limits of hydrogen combustion, which are necessary for the evaluation of the hazardous risks related to hydrogen explosions.

A deformation-dependent coupled Lagrangian/semi-Lagrangian meshfree hydromechanical formulation for landslide modeling

The numerical modelling of natural disasters such as landslides presents several challenges for conventional mesh-based methods such as the finite element method (FEM) due to the presence of numerically challenging phenomena such as severe material deformation and fragmentation. In contrast, meshfree methods such as the reproducing kernel particle method (RKPM) possess unique features conducive to modelling extreme events such as the absence of a structured mesh and the ease of adaptive refinement, among others. While the semi-Lagrangian reproducing kernel (SL-RK) shape functions of RKPM defined in the current configuration have proven to be effective in extreme event modelling, the computational cost for the re-evaluation of the shape functions at every time step is costly. In this work, a deformation-dependent coupling of the Lagrangian reproducing kernel (L-RK) and SL-RK approximations is proposed for the solution of a hydro-mechanical formulation for effective simulations of landslides. The ramp function is constructed based on an equivalent plastic strain as a deformation-dependent transition from L-RK shape functions to SL-RK ones as the deformation progresses. The particular focus of the paper will be on modelling seepage-induced landslides with a mixed u–p formulation to couple the solid and fluid phases. Examples are presented to examine the effectiveness of this coupled Lagrangian/semi-Lagrangian reproducing kernel (L–SL RK) formulation and to highlight its performance in landslide modelling.

Kramers–Kronig relations for nonlinear rheology. Part II: Validation of medium amplitude oscillatory shear (MAOS) measurements

The frequency dependence of third-harmonic medium amplitude oscillatory shear (MAOS) modulus G33∗(ω) provides insight into material behavior and microstructure in the asymptotically nonlinear regime. Motivated by the difficulty in the measurement of MAOS moduli, we propose a test for data validation based on nonlinear Kramers–Kronig relations. We extend the approach used to assess the consistency of linear viscoelastic data by expressing the real and imaginary parts of G33∗(ω) as a linear combination of Maxwell elements: the functional form for the MAOS kernels is inspired by time-strain separability (TSS). We propose a statistical test based on fitting a sum of Maxwell elements using LASSO (least absolute shrinkage and selection operator) regression, and call it the SMEL test. It works well on a broad range of materials and models including those that do not obey TSS. It successfully copes with experimental data that are noisy or confined to a limited frequency range. When Maxwell modes obtained from the SMEL test are used to predict the first-harmonic MAOS modulus G31∗, it is possible to identify the range of time scales over which a material exhibits TSS.

Assistance in making corn silk juice for the Family Welfare Empowerment Group in Giripurno Village

Giripurno Village is one of the villages that has the largest corn agricultural commodity in Batu City. The abundance of corn harvests makes prices unstable. In addition, most farmers sell their corn harvest in the form of corn kernels, so it is not optimal in processing corn cobs, husks, and silk. Most of the people belong to the low economy. The community service program aims to provide ideas through assistance to the Family Welfare Empowerment Group (PKK) to process corn silk waste into drinks that have economic potential for the community. The assistance method used is in the form of training in making drinks, packaging, and selling. The evaluation was carried out to determine the improvement of skills in making corn silk juice drinks. This assistance program was attended by 15 participants. The results of the assistance showed that PKK women had understood how to process corn silk. This is evidenced by the fact that sales have reached 468 products sold in several cities, especially East Java. Hence, it is concluded that the assistance of this corn silk drink, can improve the welfare of the local community.

Gluon pseudo-distributions at short distances

We present the results that are necessary in the ongoing lattice calculations of the gluon parton distribution functions (PDFs) within the pseudo-PDF approach. We identify the two-gluon correlator functions that contain the invariant amplitude determining the gluon PDF in the light-cone z^2 \to 0z2→0 limit, and perform one-loop calculations in the coordinate representation in an explicitly gauge-invariant form. Ultraviolet (UV) terms, which contain \ln (-z^2)ln(−z2)-dependence cancel in the reduced Ioffe-time distribution (ITD), and we obtain the matching relation between the reduced ITD and the light-cone ITD. Using a kernel form, we get a direct connection between lattice data for the reduced ITD and the normalized gluon PDF.

A systematic analysis of the memory term in coarse-grained models: The case of the Markovian approximation

The systematic development of coarse-grained (CG) models via the Mori–Zwanzig projector operator formalism requires the explicit description of a deterministic drift term, a dissipative memory term and a random fluctuation term. The memory and fluctuating terms are related by the fluctuation–dissipation relation and are more challenging to sample and describe than the drift term due to complex dependence on space and time. This work proposes a rational basis for a Markovian data-driven approach to approximating the memory and fluctuating terms. We assumed a functional form for the memory kernel and under broad regularity hypothesis, we derived bounds for the error committed in replacing the original term with an approximation obtained by its asymptotic expansions. These error bounds depend on the characteristic time scale of the atomistic model, representing the decay of the autocorrelation function of the fluctuating force; and the characteristic time scale of the CG model, representing the decay of the autocorrelation function of the momenta of the beads. Using appropriate parameters to describe these time scales, we provide a quantitative meaning to the observation that the Markovian approximation improves as they separate. We then proceed to show how the leading-order term of such expansion can be identified with the Markovian approximation usually considered in the CG theory. We also show that, while the error of the approximation involving time can be controlled, the Markovian term usually considered in CG simulations may exhibit significant spatial variation. It follows that assuming a spatially constant memory term is an uncontrolled approximation which should be carefully checked. We complement our analysis with an application to the estimation of the memory in the CG model of a one-dimensional Lennard–Jones chain with different masses and interactions, showing that even for such a simple case, a non-negligible spatial dependence for the memory term exists.

A New Ostrowski’s Type Inequality for Quadratic Kernel

From the past few decades, the integral inequalities have been extensively researched. Integral inequalities are applied in innumerable mathematical problems. In current paper, we obtain new versions of Ostrowski’s type integral inequalities by implementing proposed general form of 7-step quadratic kernel. Applications for cumulative distribution are also provided.

Exploring Radial Kernel on the Novel Forced SEYNHRV-S Model to Capture the Second Wave of COVID-19 Spread and the Variable Transmission Rate

The transmission rate of COVID-19 varies over time. There are many reasons underlying this mechanism, such as seasonal changes, lockdowns, social distancing, and wearing face masks. Hence, it is very difficult to directly measure the transmission rate. The main task of the present paper was to identify the variable transmission rate (β1) for a SIR-like model. For this, we first propose a new compartmental forced SEYNHRV-S differential model. We then drive the nonlinear differential equation and present the finite difference technique to obtain the time-dependent transmission rate directly from COVID-19 data. Following this, we show that the transmission rate can be represented as a linear combination of radial kernels, where several forms of radial kernels are explored. The proposed model is flexible and general, so it can be adapted to monitor various epidemic scenarios in various countries. Hence, the model may be of interest for policymakers as a tool to evaluate different possible future scenarios. Numerical simulations are presented to validate the prediction of our SEYNHRV and forced SEYNHRV-S models, where the data from confirmed COVID-19 cases reported by the Ministry of Health in Saudi Arabia were used. These confirmed cases show the second wave of the infected population in Saudi Arabia. By using the COVID-19 data, we show that our model (forced SEYNHRV-S) is able to predict the second wave of infection in the population in Saudi Arabia. It is well known that COVID-19 epidemic data cannot be accurately represented by any compartmental approach with constant parameters, and this is also true for our SEYNHRV model.

Nuclear configurational entropy and high-energy hadron-hadron scattering reactions

In this work, the high-energy hadron-hadron scattering is studied in the framework of holographic AdS/QCD models, using the Brower–Polchinski–Strassler–Tan Pomeron exchange kernel and gravitational form factors. We apply the configurational entropy techniques to estimate the slope of the total cross section for the total hadron-hadron cross sections at high-energies. A good agreement is derived between our approach and the total cross section for combinations that include the pion-nucleon, nucleon-nucleon, and pion-pion, as well as for any high-energy data with inclusion of data from the TOTEM collaboration at the LHC and approximated by the Pomeron exchange. In the case of pion-nucleon and pion-pion scattering, the agreement for the critical points to the differential configurational entropy can be reached within 1.1% even without the involvement of any extra parameters.

Hierarchical Bayesian Gaussian process regression model for loss reserving using combinations of squared exponential kernels

This paper extends the work of Lally and Hartman (2018) on the Gaussian Process (GP) regression with input warping to model claims development and to estimate loss reserves. In an attempt to provide more structure to the loss reserving GP model in improving predictive accuracy and reducing predictive uncertainties, the effects of applying combinations of additive and multiplicative squared exponential kernels into the GP model are being studied. There are evidences of improvements in the estimates of loss reserves when any form of additive kernel is applied in the GP model compared to the multiplicative squared exponential kernel that was proposed in the earlier work.

Generalized Mittag-Leffler Kernel Form Solutions of Free Convection Heat and Mass Transfer Flow of Maxwell Fluid with Newtonian Heating: Prabhakar Fractional Derivative Approach

In this article, the effects of Newtonian heating along with wall slip condition on temperature is critically examined on unsteady magnetohydrodynamic (MHD) flows of Prabhakar-like non integer Maxwell fluid near an infinitely vertical plate under constant concentration. For the sake of generalized memory effects, a new mathematical fractional model is formulated based on a newly introduced Prabhakar fractional operator with generalized Fourier’s law and Fick’s law. This fractional model has been solved analytically and exact solutions for dimensionless velocity, concentration, and energy equations are calculated in terms of Mittag-Leffler functions by employing the Laplace transformation method. Physical impacts of different parameters such as α, Pr, β, Sc, Gr, γ, and Gm are studied and demonstrated graphically by Mathcad software. Furthermore, to validate our current results, some limiting models such as classical Maxwell model, classical Newtonian model, and fractional Newtonian model are recovered from Prabhakar fractional Maxwell fluid. Moreover, we compare the results between Maxwell and Newtonian fluids for both fractional and classical cases with and without slip conditions, showing that the movement of the Maxwell fluid is faster than viscous fluid. Additionally, it is visualized that both classical Maxwell and viscous fluid have relatively higher velocity as compared to fractional Maxwell and viscous fluid.

Bergman kernel and period map for curves

As for any symmetric space the tangent space to Siegel upper-half space is endowed with an operation coming from the Lie bracket on the Lie algebra. We consider the pull-back of this operation to the moduli space of curves via the Torelli map. We characterize it in terms of the geometry of the curve, using the Bergman kernel form associated to the curve. It is known that the second fundamental form of the Torelli map outside the hyperelliptic locus can be seen as the multiplication by a certain meromorphic form. Our second result says that the Bergman kernel form is the harmonic representative—in a suitable sense—of this meromorphic form.

Approach for noncollinear GGA kernels in closed-shell systems

Exchange-correlation kernels in density functional theory are the second-order derivatives of the exchange-correlation functionals with respect to the density matrix. For collinear functionals, the forms of kernels are well known, and their applications in calculating responses of electrons to predict properties of molecules and materials are mature. However, kernels of noncollinear functionals in closed-shell systems, except for LDA (local density approximation), are generally unknown, at least mathematically ill-defined, suffering from the indeterminate forms of 0 divided by 0. We find that such singularities in noncollinear GGA (generalized gradient approximation) kernels can be removed by introducing a proper limit process and approaching the limit after the calculations of derivatives have been done. Following this idea, mathematically well-defined noncollinear GGA kernels for closed-shell systems emerge naturally. Theoretically, these kernels are shown to be numerically stable and spin-rotational symmetry preserved. Numerical tests on excitation energies and spectroscopy parameters present reasonable results, indicating the applicability of this methodology.

Fractional order modeling and analysis of dynamics of stem cell differentiation in complex network

<abstract><p>In this study, a mathematical model for the differentiation of stem cells is proposed to understand the dynamics of cell differentiation in a complex network. For this, myeloid cells, which are differentiated from stem cells, are introduced in this study. We introduce the threshold quantity $ \mathcal{R}_{0} $ to understand the population dynamics of stem cells. The local stability analysis of three equilibria, namely $ (i) $ free equilibrium points, $ (ii) $ absence of stem and progenitor cells, and $ (iii) $ endemic equilibrium points are investigated in this study. The model is first formulated in non-fractional order and after that converted into a fractional sense by utilizing the Atangana-Baleanu derivative in Caputo (ABC) sense in the form of a non-singular kernel. The model is solved by using numerical techniques. It is seen that the myeloid cell population significantly affects the stem cell population.</p></abstract>