bluuebunny/crossref_metadata_2025 huggingface dataset:
Numerical simulation of clogging in a microchannel with planar contraction
Authors: Trofa Marco , D'Avino Gaetano , Maffettone Pier Luca
Published: August 2021

Clogging is the mechanism that interrupts the flow in confined geometries due to the complete blockage of the channel cross section. It represents a critical issue in the processing of particle suspensions for both industrial and biological applications, and it is particularly relevant in microfluidics and membrane technology due to the high particle confinement and the difficult device cleaning. Although numerous experimental and numerical studies have been carried out to understand the mechanism governing this complex multiscale phenomenon, the picture is not yet clear and many questions still remain, especially at the particle level. In this regard, the numerical simulations may represent a useful investigation tool since they provide a direct insight to quantities not easily accessible from experiments. In this work, a detailed computational fluid dynamics-discrete element method simulation study on the clogging mechanism in a microchannel with planar contraction is carried out. Both constant flow rate and constant pressure drop conditions are investigated, highlighting the effect of flow conditions, particle volume fraction, cohesion forces, and contraction angle. The onset of clogging conditions is discussed.
ImmuneDEX: updated genomic estimates of genetic parameters and breeding values for Australian Angus cattle
Authors: Reverter Antonio , Hine Brad C. , Porto-Neto Laercio , Alexandre Pamela A. , Li Yutao , Duff Christian J. , Dominik Sonja , Ingham Aaron B.
Published: August 2021

Context Immune competence is a proxy trait for general disease resistance and is based on combined measures of an animal’s ability to mount both a cell-mediated immune response (Cell-IR) and an antibody-mediated immune response (Ab-IR). On the basis of previously described arithmetic, we combined these measures into a single proxy trait for immune competence, named ImmuneDEX (IDEX). Aims Using a population of 3715 Australian Angus steers (n = 2395) and heifers (n = 1320) with genotypes for 45 364 single-nucleotide polymorphisms, we provide the latest genomic estimates of heritability and genetic correlations for IDEX and the components Cell-IR and Ab-IR immune competence phenotypes. Accuracy and bias of genomic predictions of breeding values are also presented and discussed. Methods Measures of Cell-IR, Ab-IR and IDEX were analysed jointly in a tri-variate genomic restricted maximum-likelihood model that contained the fixed effects of contemporary group with 80 levels, the linear covariates of age at measurement and change in skin thickness at control site, and the random polygenic (genomic estimated breeding value, GEBV) and residual effects. Following Method LR procedures, we estimate accuracy, bias and dispersion of genomic predictions using a cross-validation scheme based on five year-of-birth cohorts. Key results We report genomic restricted maximum-likelihood model estimates of heritability of 0.247 ± 0.040 for Cell-IR, 0.326 ± 0.059 for Ab-IR, 0.275 ± 0.046 for IDEX. While a small positive genetic correlation (rg) was estimated between Cell-IR and Ab-IR (rg = 0.138 ± 0.095), strongly positive estimates were obtained between IDEX and Cell-IR (rg = 0.740 ± 0.044) and between IDEX and Ab-IR (rg = 0.741 ± 0.036). Averaged across the five validation sets, the accuracy of GEBV for Cell-IR, Ab-IR and IDEX was 0.405, 0.443 and 0.411 respectively. Also, some significant bias or dispersion can be expected depending on the cohort used as the validation population. Conclusions Consistent with previous findings, immune competence phenotypes are moderately heritable and accurate GEBV can be generated to allow the selection of cattle with an improved ability to mount a general immune response. Implications Our analyses suggest that ImmuneDEX will provide a tool to underpin long-term genetic strategies aimed at improving the immune competence of Australian Angus cattle in production systems, which, in turn, is expected to reduce the incidence of disease and our reliance on antibiotics to treat disease.
Corrigendum to: Convergent evolution of sexually dimorphic glands in an amphi-Pacific harvestman family
Authors: Gainett Guilherme , Willemart Rodrigo H. , Giribet Gonzalo , Sharma Prashant P.
Published: August 2021

Sexually dimorphic traits are widespread in animals, and include sex-specific weapons, ornamentation and, although less noticed, glands and associated structures. In arachnids, certain lineages of the order Opiliones exhibit diverse forms of dimorphism in the armature and length of appendages (common in Laniatores), as well as in the presence of sexually dimorphic glands (mostly investigated in Cyphophthalmi), positing harvestmen as promising models to study sexual dimorphism. Whereas the evolution and ecological significance of armature have been the focus of recent attention, sexually dimorphic glands remain understudied in groups other than Cyphophthalmi, despite being widespread in Opiliones. We therefore selected the amphi-Pacific family Zalmoxidae as an ideal taxon to investigate the evolutionary dynamics of this trait. We first describe four new species of Palaeotropical Zalmoxis, including a species with sexually dimorphic glands, and describe the morphology of zalmoxid species with sexually dimorphic glands using scanning electron microscopy. Using a previously assembled six-locus dataset supplemented with new terminals, and applying stochastic character mapping, we infer that sexually dimorphic glands evolved once in the Neotropics and at least four times in the Palaeotropic zalmoxids, revealing the evolutionary lability of this trait.
Spatial and temporal variations in particulate organic carbon in Indonesian waters over two decades
Authors: Triana Karlina , Wahyudi A’an Johan , Murakami-Sugihara Naoko , Ogawa Hiroshi
Published: August 2021

Particulate organic carbon (POC) is one of the essential variables in oceanic biogeochemical processes. Assessing the spatiotemporal variability of POC will help deepen our understanding of the carbon cycle. In this study we collected moderate-resolution imaging spectroradiometer (MODIS) Aqua satellite data for surface POC in Indonesian waters during the period 2002–21, together with in situ data from the south-western Sumatran waters (SSW), Sunda Strait, Sumba–Savu waters and the Halmahera Sea and surrounds. These data were analysed to gain an understanding of the spatial and temporal variations in POC. Generally, high POC concentrations in Indonesian waters were found at coastal and continental shelves connected to the estuaries of large rivers; we assume that the POC concentrations in these areas are affected by terrestrial input. Meanwhile, in Indonesian waters apart from these estuaries, marine-derived materials are the main components of POC. The seasonal pattern of POC in Indonesian waters generally shows highest levels during the south-east monsoon and lowest levels during the north-west monsoon. Trends in POC concentrations are positively correlated with chlorophyll-a and negatively correlated with sea surface temperature. This study suggests that the combination of natural physicochemical processes and anthropogenic perturbations has significant effects on spatial and temporal variations in POC in Indonesian waters.
Procedural policy tools in theory and practice
Authors: Bali Azad Singh , Howlett Michael , Lewis Jenny M , Ramesh M
Published: August 2021

Policy tools are a critical part of policy-making, providing the ‘means’ by which policy ‘ends’ are achieved. Knowledge of their different origin, nature and capabilities is vital for understanding policy formulation and decision-making, and they have been the subject of inquiry in many policy-related disciplines and sector-specific studies. Yet many crucial aspects of policy tools remain unexplored. Existing studies on policy tools used in policy formulation tend to focus on ‘substantive’ tools – those used to directly affect policy outcomes such as regulation or subsidies – and largely neglect ‘procedural’ tools used to indirectly but significantly affect policy processes and outcomes. A key aim of this special issue is to fill this knowledge gap in the field. This article introduces the issue by establishing that procedural tools play a more determining role in public policy-making than is generally acknowledged and deserve a more systematic inquiry into their workings, their impact on the policy process and the organization and delivery of public and private goods and services.
Dynamic Rac1 inhibition by CYRI helps cells drink, but stops them from driving
Authors: King Jason S.
Published: August 2021

In this issue, Le et al. (2021. J. Cell Biol.https://doi.org/10.1083/jcb.202012114) describe a new role for the recently discovered protein CYRI in controlling the protrusions that allow cells to engulf extracellular fluid by macropinocytosis. This study helps explain how these structures are disassembled, but also uncovers a new mechanism linking the ability of cells to drink and their capacity for invasive migration.
Unique reconstruction of simple magnetizations from their magnetic potential
Authors: Baratchart L , Gerhards C , Kegeles A , Menzel P
Published: August 2021

Inverse problems arising in (geo)magnetism are typically ill-posed, in particular they exhibit non-uniqueness. Nevertheless, there exist nontrivial model spaces on which the problem is uniquely solvable. Our goal is here to describe such spaces that accommodate constraints suited for applications. In this paper we treat the inverse magnetization problem on a Lipschitz domain with fairly general topology. We characterize the subspace of L
2-vector fields that causes non-uniqueness, and identify a subspace of harmonic gradients on which the inversion becomes unique. This classification has consequences for applications and we present some of them in the context of geo-sciences. In the second part of the paper, we discuss the space of piecewise constant vector fields. This vector space is too large to make the inversion unique. But as we show, it contains a dense subspace in L
2 on which the problem becomes uniquely solvable, i.e. magnetizations from this subspace are uniquely determined by their magnetic potential.
Holographic heat engine efficiency of hyperbolic charged black holes*
Authors: Sun Wei , Ge Xian-Hui
Published: August 2021

We consider a four-dimensional charged hyperbolic black hole as working matter to establish a black hole holographic heat engine, and use the rectangular cycle to obtain the heat engine efficiency. We find that when the increasing of entropy is zero, the heat engine efficiency of the hyperbolic black hole becomes the well-known Carnot efficiency. We also find that less charge corresponds to higher efficiency in the case of

q
∼

>
0

. Furthermore, we study the efficiency of the flat case and spherical case and compare the efficiency with that of the hyperbolic charged black holes. Finally, we use numerical simulation to study the efficiency in benchmark scheme.
Review of Raman spectroscopy of two-dimensional magnetic van der Waals materials*
Authors: Sun Yu-Jia , Pang Si-Min , Zhang Jun
Published: August 2021

Ultrathin van der Waals (vdW) magnets provide a possibility to access magnetic ordering in the two-dimensional (2D) limit, which are expected to be applied in the spintronic devices. Raman spectroscopy is a powerful characterization method to investigate the spin-related properties in 2D vdW magnets, including magnon and spin–lattice interaction, which are hardly accessible by other optical methods. In this paper, the recent progress of various magnetic properties in 2D vdW magnets studied by Raman spectroscopy is reviewed, including the magnetic transition, spin-wave, spin–lattice interaction, symmetry tuning induced by spin ordering, and nonreciprocal magneto-phonon Raman scattering.
New multiplexed system for synchronous measurement of out-of-plane deformation and two orthogonal slopes
Authors: Wang Yonghong , Zhang Xiao , Zhao Qihan , Yao Yanfeng , Yan Peizheng , Wang Biao
Published: August 2021

We propose a novel system for synchronous measurement of out-of-plane deformation and two orthogonal slopes using a single camera. The linearly polarized reference beam introduced by an optical fiber interferes with the unpolarized object beam to measure the out-of-plane deformation. A modified Mach–Zehnder interferometer is used to measure the two orthogonal slopes of the out-of-plane deformation. One of the object beams of the Mach–Zehnder interferometer is an unpolarized beam, and the other object beam is split into two orthogonal linearly polarized object beams by a polarizing prism. The two beams are orthogonally polarized. Hence, they will not interfere with each other. The two polarized beams respectively interfere with the unpolarized beam to simultaneously measure the two orthogonal slopes of the out-of-plane deformation. In addition, the imaging lens and apertures are respectively placed in three optical paths to independently control the carrier frequencies and shearing amounts. The effectiveness of this method can be proved by measuring two pressure-loaded circular plates.
A high-quality-factor ultra-narrowband perfect metamaterial absorber based on monolayer molybdenum disulfide
Authors: Jiang Liying , Yi Yingting , Tang Yijun , Li Zhiyou , Yi Zao , Liu Li , Chen Xifang , Jian Ronghua , Wu Pinghui , Yan Peiguang
Published: August 2021

In order to significantly improve the absorption efficiency of monolayer molybdenum disulfide (M-MoS2), an ultra-narrowband M-MoS2 metamaterial absorber was obtained through theoretical analysis and numerical calculation using the finite difference time domain method. The physical mechanism can be better analyzed through critical coupling and guided mode resonance. Its absorption rate at λ = 806.41 nm is as high as 99.8%, which is more than 12 times that of bare M-MoS2. From the simulation results, adjusting the geometric parameters of the structure can control the resonant wavelength range of the M-MoS2. In addition, we also found that the maximum quality factor is 1256.8. The numerical result shows that the design provides new possibilities for ultra-narrowband M-MoS2 perfect absorbers in the near-infrared spectrum. The results of this work indicate that the designed structure has excellent prospects for application in wavelength-selective photoluminescence and photodetection.
Inferring interactions of time-delayed dynamic networks by random state variable resetting
Authors: Deng Changbao , Jiang Weinuo , Wang Shihong
Published: August 2021

Time delays exist widely in real systems, and time-delayed interactions can result in abundant dynamic behaviors and functions in dynamic networks. Inferring the time delays and interactions is challenging due to systematic nonlinearity, noises, a lack of information, and so on. Recently, Shi et al. proposed a random state variable resetting method to detect the interactions in a continuous-time dynamic network. By arbitrarily resetting the state variable of a driving node, the equivalent coupling functions of the driving node to any response node in the network can be reconstructed. In this paper, we introduce this method in time-delayed dynamic networks. To infer actual time delays, the nearest neighbor correlation (NNC) function for a given time delay is defined. The significant increments of NNC originate from the delayed effect. Based on the increments, the time delays can be reconstructed and the reconstruction errors depend on the sampling time interval. After time delays are accurately identified, the equivalent coupling functions can also be reconstructed. The numerical results have fully verified the validity of the theoretical analysis.
Improving the performance of a GaAs nanowire photodetector using surface plasmon polaritons
Authors: Zhu Xiaotian , Meng Bingheng , Wang Dengkui , Chen Xue , Liao Lei , Jiang Mingming , Wei Zhipeng
Published: August 2021

GaAs nanowires (NWs) are ideal materials for preparing near-infrared photodetectors owing to their high charge carrier mobility and direct band gap. Although the performance of GaAs NW photodetectors can be enhanced by surface passivation or doping, it still cannot meet the requirement for applications. In this paper we propose a method to greatly improve the performances of GaAs NW photodetectors by hot-hole injection via surface plasmon polaritons. In this case, the responsivity of a single GaAs NW photodetector is increased by a fact of 3.2 to 6.56 A⋅W−1 by attaching capsule-like Au nanoparticles to its surface. This research uses an efficient route to improve the NW photocurrent, which is also important for the development of a high-performance near-infrared NW photodetecor.
Effect of nonlinear translations on the pulsation of cavitation bubbles
Authors: Zhang Lingling , Chen Weizhong , Shen Yang , Wu Yaorong , Zhao Guoying , Kou Shaoyang
Published: August 2021

The pulsations and translations of cavitation bubbles obey combined ordinary differential equations, and their nonlinearities are studied by the bifurcation diagram and the phase diagram in a strong ultrasonic field. Bubble pulsation can change regularly or irregularly with changing driving pressure in the time domain. The bifurcation diagrams of the pulsation versus driving pressure show that the pulsations and translations of bubbles have nonlinear characteristics, and the nonlinear translations of bubbles can disorder the pulsations for certain parameters. Disorder of the pulsation can also be caused by nonlinear pulsation itself. In addition, the phase diagrams also show that the nonlinear translations make a large contribution to the pulsations. The same result can also be obtained when the ambient radii of two bubbles are different.
Long range electromagnetic field nature of nerve signal propagation in myelinated axons
Authors: Zhai Qing-Wei , Ooi Kelvin J A , Xu Sheng-Yong , Ong C K
Published: August 2021

The nature of saltatory conduction in myelinated axon described by equivalent circuit and circuit theory is still contentious. Recent experimental observations of action potentials transmitting through disjointed nerve fibers strongly suggest an electromagnetic wave propagation mechanism of the nerve signals. In this paper, we employ the electromagnetic wave model of the myelinated axon to describe action potential signal propagation. We use the experimental frequency-dependent conductivity and permittivity values of the nerve tissues in order to reliably calculate the electromagnetic modes by using electromagnetic mode solvers. We find that the electromagnetic waves above 10 kHz can be well confined in extracellular fluid–myelin sheath–intracellular fluid waveguide and propagate a distance of 7 mm without much attenuation. Our study may serve as one of the fundamental researches for the better understanding of the nervous system.
Effect of an electric field on dewetting transition of nitrogen-water system
Authors: Feng Qi , Li Jiaxian , Zhou Xiaoyan , Lu Hangjun
Published: August 2021

We investigate the influence of an external electric field on the dewetting behavior of nitrogen-water systems between two hydrophobic plates using molecular dynamics simulations. It is found that the critical distance of dewetting increases obviously with the electric field strength, indicating that the effective range of hydrophobic attraction is extended. The mechanism behind this interesting phenomenon is related to the rearrangement of hydrogen bond networks between water molecules induced by the external electric field. Changes in the hydrogen bond networks and in the dipole orientation of the water molecules result in the redistribution of the neutral nitrogen molecules, especially in the region close to the hydrophobic plates. Our findings may be helpful for understanding the effects of the electric field on the long-range hydrophobic interactions.
Correlations and structure of interfaces in the Ising model: theory and numerics
Authors: Squarcini Alessio , Tinti Antonio
Published: August 2021

We consider phase separation on the strip for the two-dimensional Ising model in the near-critical region. Within the framework of field theory, we find exact analytic results for certain two- and three-point correlation functions of the order parameter field. The analytic results for order parameter correlations, energy density profile, subleading corrections and passage probability density of the interface are confirmed by accurate Monte Carlo simulations we performed.
Comparative study of Stochastic Taylor Methods and Derivative-Free Methods for Stochastic Differential Equations
Authors: Fahmi Muhammad , Rosli Norhayati
Published: August 2021

Ordinary differential equations (ODEs) have been widely used to model the dynamical behaviour of biological and physical systems. However, modelling these systems using deterministic model such as ODEs is inadequate as the system is subjected to the uncontrolled factors of environmental noise. Stochastic differential equations (SDEs) which are originating from the irregular Brownian motion can be applied to model such systems that subjected to the uncontrolled factors of noisy behaviour. Numerical methods are required to approximate the solution of the model due to the complexity of the equation. Theoretically, methods with a higher order of convergence lead to a better approximation of the solutions. Though, the implementation of the methods might not reflect the theoretical finding as generating a lot of random numbers might contribute to the instability of the methods. This research is aimed to investigate the performance of stochastic Taylor methods of Euler-Maruyama, Milstein scheme, and derivative-free methods of second and fourth-order stochastic Runge-Kutta in approximating the solution of SDEs. Four types of mathematical models which include the Black-Scholes model, logistic model, stochastic Gompertz model, and prey-predator model are simulated using the aforementioned numerical methods. Numerical solutions of the Black-Scholes model are compared with the analytical solution meanwhile, the numerical solutions of the logistic model and stochastic Gompertz models are compared with the experimental data of the fermentation process and cancer cell growth, respectively. The simulated results of the prey-predator model are compared with the experimental data of the interaction between cancer cells (prey) and anticancer Chrondoitin Sulfate (predator). The prediction performance of the methods is measured using global error and root mean square errors (RMSE).
Implementing the reliability of data information in multi-criteria decision making process based on fuzzy TOPSIS and fuzzy entropy
Authors: Mohd Jamal N.J. , Ku Khalif K.M.N. , Mohamad M.S.
Published: August 2021

A multi-criteria decision-making process utilizes real-time data information, which is inherently uncertain and imprecise. To be relevant in the decision-making process, real-time data information must be reliable. Because fuzziness alone is insufficient to solve decision-making problems, measuring the information’s reliability is critical. Z-number, which incorporates both restrictions and reliability in its definition is considered as a powerful tool to depict the imperfect information. In this paper, a new methodology is developed based on fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and fuzzy entropy for solving the multi-criteria decision-making problems where the weight information for decision makers and criteria is incomplete. The evaluation of the information is represented in the form of linguistic terms and the following calculation is performed using Z-numbers. Fuzzy entropy is applied to determine the weights of the criteria and fuzzy TOPSIS is used to rank the alternatives. An empirical study of subjective well-being of working women is used to demonstrate the proposed methodology.
Stochastic modelling of the oral cancer proliferation and death in the presence of Thymoquinone as anticancer therapeutics
Authors: Tabassum Shabana , Rosli Norhayati , Suriyah Wastuti Hidayati , Ichwan Solachuddin Jauhari Arief
Published: August 2021

Oral cancer is one of the most commonly known cancer worldwide. Thymoquinone (TQ) an extract from Nigella sativa, has clinically been proven as an anticancer therapeutic agent for oral cancer due to its intrinsic pharmacological characteristics. Understanding the mechanisms of oral cancer proliferation and death in the presence of TQ is crucial so that the insight of the interaction of cancer cells and TQ can be discovered. Cancer cells in the presence of TQ is subjected to the uncontrolled factors of the environmental noise. Deterministic model is inadequate to explain this behaviour. Herein, a stochastic model is proposed to illustrate the dynamics of HSC-3 oral cancer cell lines in the presence of TQ. The deterministic model is perturbed with the noisy behaviour which then leads to the stochastic model. The model is simulated by using a four-stage stochastic Runge-Kutta (SRK4) method and the kinetic parameters are estimated by using the maximum likelihood estimation (MLE) method. The prediction quality of the model is measured by using root mean square error (RMSE). The low values of RMSE show the best-fit of the stochastic model.
Performance of 5-stage, 4-stage and specific stochastic Runge-Kutta methods in approximating the solution of stochastic biological model
Authors: Ariffin Noor Amalina Nisa , Rosli Norhayati , Kasim Abdul Rahman Mohd , Mazlan Mazma Syahidatul Ayuni
Published: August 2021

In recent years, the transition on modelling physical systems via stochastic differential equations (SDEs) has attracted great interest among researchers. This is due to the limitations of ordinary differential equations in presenting the real phenomenon. To the fact that the stochastic models incorporate the random effects that may influence the behaviour of physical systems, SDEs seems to be the best model that can be used i n assessing those systems. The growing interest among researchers in modelling the systems via SDEs comes with the rise in the need of numerical methods to approximate the solutions for SDEs. This is because by taking into account the random fluctuations in SDEs resulting to the complexity of finding the exact solution of SDEs. Therefore, it contribute to the increasing number of research to decide on the best numerical approach to solve the systems of SDEs. This paper is devoted to investigate the performance of 5-stage stochastic Runge-Kutta ( SRK5) with order 2.0, 4-stage stochastic Runge-Kutta ( SRK4), specific stochastic Runge-Kutta with order 1.5 ( SRKS1.5) and commutative specific stochastic Runge-Kutta with order 1.5 (SRKST2) in approximating the solution of stochastic model in biological system. A comparative study of SRK5, SRK4, SRKS1.5 and SRKST2 methods will be presented in this paper. The linear SDE model and the stochastic model of C. Acetobutylicum cell growth will be used to examine the performance of those methods and the numerical experiment will be conducted. The numerical solutions obtained will be discussed.
Vector Soliton in Coupled Nonlinear Schrödinger Equation
Authors: Aklan N A B , Ishak N A S , Umarov B A
Published: August 2021

Researchers are currently interested in studying the dynamics of the wave field in a nonlinear and dispersive medium. The Nonlinear Schrödinger Equation (NLSE), which is the fundamental equation that explains the phenomenon, has paved the way for research in a variety of fields, including soliton scattering. However, if the fields have a large number of components, the Coupled NLSE should be considered. We used orthogonally polarised and equal-amplitude vector solitons with two polarization directions to model the interactions. The effect of vector soliton scattering by external Delta potential in Coupled NLSE was studied in this paper. The scattering process is primarily determined by the initial velocity, amplitude of the soliton and potential strength. The variational approximation and direct numerical methods of Coupled NLSE were used to investigate the scattering process. The variational approximation (VA) method was used to analyse the dynamics of soliton’s width and center of mass position. The soliton may thus be reflected, transmitted or trapped within the potential. Uncoupled solitons may initially create a coupled state if their kinetic energy is less than the attractive interaction potential between solitons, but once their velocity surpasses the critical velocity, the soliton will easily pass through each other. To validate the approximation, a direct numerical simulation of CNLSE was performed. The results of the VA method and direct numerical simulation of Coupled NLSE are in good agreement when the parameters for both solutions are set to the same value. The initial velocity, potential strength and soliton amplitude play a role in the scattering of the vector soliton with Delta potential.
Analysis on sustainable manufacturing criteria of automotive industry
Authors: Jalaludin Siti Aisyah , Bakar Sumarni Abu
Published: August 2021

In this paper, criteria within the most significant domain of manufacturing in automotive industry in Malaysia is analysed and prioritized. This paper aims to propose a multi criteria decision making (MCDM) procedure using concept of fuzzy theory, graph theory and Laplacian matrix approach which is embedded into Graph Theory and Matrix approach (GTMA). The manufacturing domains are ranked using Laplacian energy while the criteria within the most significant domain is prioritized using method of graph drawing whereby the criteria’s is ranked based on the average distance among other criteria in Cartesian coordinate system. The result indicates that cost, quality and service in economic domain are among significant criteria’s that practitioners should give an attention in developing a quality sustainable manufacturing framework so that the industry could sustain for a longer period of time.
Directed network of Shariah-compliant stock in Bursa Malaysia
Authors: Musa Muhammad Hasannudin , Razak Fatimah Abdul
Published: August 2021

Stock network is a type of financial network based on stock price data used for analysing stock market dynamics. In this paper, a directed stock network is developed. This model was built using 480 shariah-compliant stocks traded in Bursa Malaysia from the year 2016 until 2018. Transfer Entropy was used as a measuring tool to build the stock network. Different networks are built and evaluated using network analysis methods. To determine the important stocks in the networks, centrality measures are applied such as degree centrality. The findings showed that Borneo Oil Berhad (BRNL) is the most influential and important stock among the 480 shariah-compliant stock in the Bursa Malaysia.
Level set method for free boundary of invasive cancer cell using different functions of matrix metalloproteinases
Authors: Yaacob Noorehan , Shafie Sharidan , Suzuki Takashi , Admon Mohd Ariff
Published: August 2021

The secondary tumor is stated to be more dangerous among cancer patients and this tumor is created through metastasis. Metastasis is the process of spreading a tumor from the primary location to the second part of the human body. This is an unpleasant problem among cancer patients because metastasis can contribute to high mortality cases among them. The presence of finger-like protrusions on the plasma membrane of cancer cells is known as the invadopodia. This structure can contribute to cancer cell invasion through the metastasis process. The formation of invadopodia involves several molecular interactions between extracellular matrix (ECM), ligand, actin, and matrix metalloproteinases (MMPs). The degradation of the ECM by the MMPs is mentioned as the starting point for the occurrence of cancer cell invasion. In this paper, the concentration of MMPs is taken in several functions of g to observe the formation of invadopodia on the plasma membrane. Two-dimensional mathematical model of ligand and signal is solved numerically using the method of level set, ghost fluid with linear extrapolation, and finite-difference. Credit is given to the level set method which successfully detected the movement of the free boundary interface (plasma membrane) by setting the interface as a zero-level set function. Also, the neighboring meshes can be identified using this method. Results showed that the above-mentioned integrated methods effectively describe the movement of the free boundary interface and this directly points out the formation of protrusions on the plasma membrane.
Generalized fuzzy number and graph theory matrix approach in fuzzy decision making of smartphone selection
Authors: Bakar Sumarni Abu , Fauzi Noor Syahida , Rahman Kahartini Abd
Published: August 2021

A number of studies have proposed a method of ranking a smartphone due to the fact that newly smartphones in the market are offering more features which could give more benefit to the user and thus become increasingly important as a tool in helping them to make everyday decisions. But most of the studies have exhibited shortcoming associated to level of confidence of decision makers’ in giving a judgement, which significantly influences final ranking result. This study proposes Graph Theory and Matrix Approach (GTMA) on ranking smartphone alternatives that ensures consideration of uncertainty and confidence level upon their judgement towards smartphone selection. A Generalized Triangular Fuzzy Number (GTFN) is used in the calculation of interrelation matrix which leads to give more meaningful value of importance weights of the attributes. Selection index is then calculated to rank the smartphone through fuzzy determinant. A numerical example is provided to illustrate the proposed approach whereby five well-known smartphones brand are considered which are apple, Samsung, Huawei, OPPO and Asus. The result shows that Huawei is the most preferred brand followed by OPPO and Apple in selecting the best smartphone.
Numerical construction of deformation field in converging channel
Authors: Damanhuri N A , Ayob S , Sabri I S
Published: August 2021

This work proposes the computational method for the construction of the stress field in the deformation region in a converging channel. The stress components are assumed to satisfy Mohr-Coulomb yield criteria under plane strain condition. The governing equation for the model is the first-order partial differential equation, which is the stress equilibrium equations. The deformation region is made up of the union of adjacent elementary boundary value problem and solved numerically. The region is constructed by using Matlab, and it shows the formation of the two symmetrical deformation region at both upper and lower part of the converging channel. From the computation, we obtained the stress variables and the velocity distribution in the deformation region. The work rate for the corresponding velocity was calculated, then it is shown that the solutions are physically significant since the condition of the work rate is everywhere positive. This method is of great interest as it will bring about an increase in efficiency and hence improvement in industrial productivity, especially in designing granular flow device. The technique is also an alternative for the solution of the deformation problems as it is simple and more reliable.
Mathematical modeling on application of wireless networks for industrial automation-factory automation
Authors: Ming W H , Hawari M Z K , Apandi N I
Published: August 2021

Since traditional automation relies on wires, the machines’ versatility will be restricted. Thus maintenance is required to prevent cable wear and breakage, which would be costly and highlighted the importance of wireless connectivity in overcoming some of the limitations of conventional factory automation. Moreover, two of the most critical considerations, reliability and latency, need to be fulfilled so that a factory automation system can perform flawlessly. However, in factory automation, 0ms is the perfect condition since many machines share the same network. Furthermore, it can only reduce latency to a certain extent but not to zero. This study focuses on wireless networks for Industrial Automation Factor Automation’s system architecture, including network devices and topology, and then demonstrates one of the wireless networks’ main technologies, retransmission. This paper develops a mathematical analysis based on Negative Acknowledgement (NACK)-based retransmission mode as default retransmission for field devices to send data frames to the gateway device periodically. The results demonstrate an automatic on-demand retransmission (AODR) scheme able to provide higher efficiency of retransmission rate.
Mathematical foundations of modeling economic indicators
Authors: Abilkayeva Zh N , Gabbassov M B
Published: August 2021

This paper describes the mathematical foundations for modeling multidimensional economic indicators that form a linear space with mathematical operations defined therein, such as addition and multiplication. The concept of factors is introduced as an enumerated type of possible values, as well as the concept of indicators that can depend on factors and have a multidimensional structure. We determined the space of factors and the space of measurements in which the basic arithmetic operations are identified and their properties are proved. Examples of modeling real economic indicators are given on the example of calculating the cost of services for the transportation of goods by rail. An important advantage of using the described abstract mathematical space of meters is the ability to automatically track the integrality or differentiability of economic indicators in the corresponding economic information systems. The proposed mathematical apparatus can be used to solve various economic problems and to design the structure of an economic information systems’ database. References are given to the results of specific projects carried out in the Republic of Kazakhstan, in which the proposed mathematical apparatus is used.
Group decision making-based TODIM under Linguistic Aggregation Majority Additive operator
Authors: Rosli N N N C , Yusoff B , Wahab A F , Madi E N
Published: August 2021

This paper proposes an extension of TODIM (interactive multi-criteria decision making) under group decision making (GDM) using the Linguistic Aggregation Majority Additive (LAMA) operator. TODIM is an effective method in modelling experts’ psychological behaviour in the decision-making process. However, under the GDM, the method is based solely on the average of all experts’ judgments without any consideration to soft aggregation processes that include majority and/or minority concepts. In this work, the LAMA operator is used to be integrated with TODIM-GDM to aggregate the experts’ opinions with respect to the majority concept under the linguistic domain. This is to provide a greater flexibility in reaching a consensus instead of only considering equally average using the classical averaging operators. Two linguistic representations, namely, symbolic approach and 2-tuple linguistic approach for LAMA operator are proposed to be utilised in the method. A numerical example in investment selection problem is provided to illustrate the applicability of the proposed method. Finally, the comparison of these two linguistic approaches is presented. The results show that LAMA under the 2-tuple linguistic approach is preferable to the symbolic approach in case of there is a tie between alternatives in the final ranking.
Numerical solution of third-order Robin boundary value problems using diagonally multistep block method
Authors: Nasir N M , Majid Z A , Ismail F , Bachok N
Published: August 2021

This numerical study exclusively focused on developing a diagonally multistep block method of order five (2DDM5) to get the approximate solution of the third-order Robin boundary value problems directly. The mathematical derivation of the developed 2DDM5 method is by approximating the integrand function with Lagrange interpolation polynomial. The proposed direct integrator scheme was applied to compute numerical solution at two-point concurrently. Shooting technique adapted with the Newtons divided difference interpolation method was implemented throughout the proposed algorithm. The theoretical characteristics of the developed method including the order, consistency, zero-stable and convergence are discussed. The method are tested on four Robin boundary value problems. The numerical results signify that the computational performances of the proposed method is competitive in terms of accuracy and efficiency than the existing method.
Variable step block backward differentiation formula with independent parameter for solving stiff ordinary differential equations
Authors: Zawawi I S M , Ibrahim Z B , Othman K I
Published: August 2021

Over the last decade, the evolution of block backward differentiation formulas (BBDF) has involved the modifications of the formulation techniques in order to solve ordinary differential equations (ODEs). Better still, if the modified methods have the ability of computing solutions efficiently with any prescribed parameter. Therefore, this research focuses on the derivation of 2-point variable step block backward differentiation formulas (VSBBDF) that possesses independent parameter in the coefficients. In this formula, each block contains two points, which compute two approximate solutions simultaneously. Varying the value of parameter will lead to multiple choice of solutions with different level of accuracy. Since the method is derived using variable step size scheme, the strategy in controlling the step size ratio is also discussed. The capability of the derived method is demonstrated by solving initial value problem of stiff ODEs. A comparison of its performance with several existing methods is made to shed light on the superiority and shortcomings of VSBBDF with respect to independent parameter.
Numerical method in solving neutral and retarded Volterra delay integro-differential equations
Authors: Ismail Nur Inshirah Naqiah , Majid Zanariah Abdul , Senu Norazak , Wahi Nadihah
Published: August 2021

The aim of this research is to produce accurate numerical results in solving neutral Volterra delay integro-differential equations (NVDIDE) and retarded Volterra delay integro-differential equations (RVDIDE) of constant type. A third-order explicit multistep block method is derived by applying the Taylor series. The consistency, zero stability, and convergence of the method are determined. The problems are solved by approximating two points simultaneously with constant step size. The delay arguments are approximated using previously calculated values while the integration part is approximated using the quadrature rule. The numerical results obtained have shown that the proposed explicit method is comparable with the other methods and is assumed to be reliable in solving NVDIDE and RVDIDE of constant type.
Development of GUI for Malaysian herbs plant image identification
Authors: Halim Suhaila Abd , Lazim Syafiqah Md
Published: August 2021

In the previous era, sickness and diseases were treated using traditional herbs since medical technology had yet to be developed. Due to massive development in medicine, more herbs species are facing the risk of extinction due to not being well conserved. This paper describes the development of a graphical user interface (GUI) for identification of Malaysian Herbs Plant from image data using MATLAB. Besides, the GUI development will contribute to the database development of herbs species that are much needed to systematically stores relevant information. It can provide valuable knowledge for society. It is quite challenging for people including the herbs’ expert, to differentiate herbs’ plants since there are too many of them and limited knowledge and experiences. Fortunately, this can be overcome by using image processing approaches specifically image segmentation and classification. A set of image data consists of five types of Malaysian herbs plants is used in this study. The types are Rerama, Sirih, Mexican Mint, Belalai Gajah dan Senduduk. Sobel edge detection operator is a segmentation approach that works by computing the gradient of image intensity at each point and measuring the pixel value changes in horizontal and vertical directions by using two convolution masks. The shape and texture features are used in multiclass Support Vector Machine (SVM) model to classify the species of the herbs. Results show that performance of model are 95.56% for accuracy and sensitivity, 98.89% for specificity, 95.78% for precision, and 94.53% for Matthews correlation. The demonstration of image data shows the effectiveness of the developed GUI in classifying the five types of herbs.
Daily rainfall modeling using Neural Network
Authors: Permai S D , Ohyver M , Aziz M K B M
Published: August 2021

In the early 2020, Indonesia experienced flooding in several areas. This disaster caused a lot of damage and losses. One of the causes of flooding in Indonesia is due to high rainfall. This was not anticipated beforehand so there was a flood. Therefore, research on rainfall in Indonesia is very important to anticipate floods. If it is predicted that rainfall is very high and conditions do not allow it to accommodate, the government can prepare watersheds so that rainwater can flow and not be trapped. In this research, the rainfall data were obtained from Meteorological, Climatological, and Geophysical Agency (BMKG Indonesia), then the analysis of rainfall data in Indonesia was carried out. There are several statistical methods that can be used. There are ARIMA and Neural Network. In this research, the results of ARIMA model are used as input variables in the Neural Network model. Then there are several numbers of hidden layer in the Neural Network model that are compared. The results of ARIMA model and Neural Network model showed that Neural Network model is better than ARIMA model, because the mean square error (MSE) value of Neural Network model is smaller than ARIMA model.
Stock Price Prediction Using ARIMA, Neural Network and LSTM Models
Authors: Ho M K , Darman Hazlina , Musa Sarah
Published: August 2021

Since the past decades, prediction of stock price has been an important and challenging task to yield the most significant profit for a company. In the era of big data, predicting the stock price using machine learning has become popular among the financial analysts since the accuracy of the prediction can be improved using these techniques. In this paper, auto-regressive integrated moving average (ARIMA), neural network (NN) and long short-term memory network (LSTM) have been used to predict Bursa Malaysia’s closing prices data from 2/1/2020 to 19/1/2021. All the models will be evaluated using root mean square errors (RMSE) and mean absolute percentage errors (MAPE). The results showed that LSTM able to generate more than 90% of accuracy in predicting stock prices during this pandemic period.