Bio-Inspired Computational Methods for the Polio Virus Epidemic Model

In 2021,most of the developing countries are fighting polio,and parents are concerned with the disabling of their children.Poliovirus transmits from person to person,which can infect the spinal cord,and paralyzes the parts of the body within a matter of hours.According to the World Health Organization(WHO),18 million currently healthy people could have been paralyzed by the virus during 1988–2020.Almost all countries but Pakistan,Afghanistan,and a fewmore have been declared polio-free.The mathematical modeling of poliovirus is studied in the population by categorizing it as susceptible individuals(S),exposed individuals(E),infected individuals(I),and recovered individuals(R).In this study,we study the fundamental properties such as positivity and boundedness of the model.We also rigorously study the model’s stability and equilibria with or without poliovirus.For numerical study,we design the Euler,Runge–Kutta,and nonstandard finite difference method.However,the standard techniques are time-dependent and fail to present the results for an extended period.The nonstandard finite difference method works well to study disease dynamics for a long time without any constraints.Finally,the results of different methods are compared to prove their effectiveness.

Predicting Genotype Information Related to COVID-19 for Molecular Mechanism Based on Computational Methods

Novel coronavirus disease 2019(COVID-19)is an ongoing health emergency.Several studies are related to COVID-19.However,its molecular mechanism remains unclear.The rapid publication of COVID-19 provides a new way to elucidate its mechanism through computational methods.This paper proposes a prediction method for mining genotype information related to COVID-19 from the perspective of molecular mechanisms based on machine learning.The method obtains seed genes based on prior knowledge.Candidate genes are mined from biomedical literature.The candidate genes are scored by machine learning based on the similarities measured between the seed and candidate genes.Furthermore,the results of the scores are used to perform functional enrichment analyses,including KEGG,interaction network,and Gene Ontology,for exploring the molecular mechanism of COVID-19.Experimental results show that the method is promising for mining genotype information to explore the molecular mechanism related to COVID-19.

Recent Advances in Computational Methods for Nuclear Magnetic Resonance Data Processing

Although three-dimensional protein structure determination using nuclear magnetic res- onance （NMR） spectroscopy is a computationally costly and tedious process that would benefit from advanced computational techniques, it has not garnered much research attention from special- ists in bioinformatics and computational biology. In this paper, we review recent advances in com- putational methods for NMR protein structure determination. We summarize the advantages of and bottlenecks in the existing methods and outline some open problems in the field. We also dis- cuss current trends in NMR technology development and suggest directions for research on future computational methods for NMR.

Preliminary Investigation of Copper(II) Ion Binding or Complex Coordination in Lysozeme Molecules

Hydrophobic Val derivative Schiff base copper(II) complexes and dipeptide (AlaAla, GlyGly) derivative Schiff base copper(II) complexes were introduced into egg white lysozyme. X-ray crystal structure analysis revealed amino acid derivative Schiff base copper(II) complexes were obtained. Herein we discuss primarily on the binding mode of copper(II) of the complexes obtained with egg white lysozyme. The electron density of copper(II) ions was confirmed by X-ray crystal structure analysis. The Val derivative Schiff base copper(II) complex was weakly bound at Arg114 of egg white lysozyme. In other copper(II) complexes, binding of copper(II) ions with dissociated ligands to various residues was observed. The binding sites of copper(II) ions were compared with computational scientific predictions.

Protein-protein interactions: Methods, databases, and applications in virus-host study

Almost all the cellular processes in a living system are controlled by proteins:They regulate gene expression,catalyze chemical reactions,transport small molecules across membranes,and transmit signal across membranes.Even,a viral infection is often initiated through virus-host protein interactions.Protein-protein interactions(PPIs)are the physical contacts between two or more proteins and they represent complex biological functions.Nowadays,PPIs have been used to construct PPI networks to study complex pathways for revealing the functions of unknown proteins.Scientists have used PPIs to find the molecular basis of certain diseases and also some potential drug targets.In this review,we will discuss how PPI networks are essential to understand the molecular basis of virus-host relationships and several databases which are dedicated to virus-host interaction studies.Here,we present a short but comprehensive review on PPIs,including the experimental and computational methods of finding PPIs,the databases dedicated to virus-host PPIs,and the associated various applications in protein interaction networks of some lethal viruses with their hosts.

A fast computational method for the landing footprints of space-to-ground vehicles

Fast computation of the landing footprint of a space-to-ground vehicle is a basic requirement for the deployment of parking orbits, as well as for enabling decision makers to develop real-time programs of transfer trajectories. In order to address the usually slow computational time for the determination of the landing footprint of a space-to-ground vehicle under finite thrust, this work proposes a method that uses polynomial equations to describe the boundaries of the landing footprint and uses back propagation(BP) neural networks to quickly determine the landing footprint of the space-to-ground vehicle. First, given orbital parameters and a manoeuvre moment, the solution model of the landing footprint of a space-to-ground vehicle under finite thrust is established. Second, given arbitrary orbital parameters and an arbitrary manoeuvre moment, a fast computational model for the landing footprint of a space-to-ground vehicle based on BP neural networks is provided.Finally, the simulation results demonstrate that under the premise of ensuring accuracy, the proposed method can quickly determine the landing footprint of a space-to-ground vehicle with arbitrary orbital parameters and arbitrary manoeuvre moments. The proposed fast computational method for determining a landing footprint lays a foundation for the parking-orbit configuration and supports the design of real-time transfer trajectories.

Review:Recent Development of High⁃Order⁃Spectral Method Combined with Computational Fluid Dynamics Method for Wave⁃Structure Interactions

The present paper reviews the recent developments of a high⁃order⁃spectral method(HOS)and the combination with computational fluid dynamics(CFD)method for wave⁃structure interactions.As the numerical simulations of wave⁃structure interaction require efficiency and accuracy,as well as the ability in calculating in open sea states,the HOS method has its strength in both generating extreme waves in open seas and fast convergence in simulations,while computational fluid dynamics(CFD)method has its advantages in simulating violent wave⁃structure interactions.This paper provides the new thoughts for fast and accurate simulations,as well as the future work on innovations in fine fluid field of numerical simulations.

Computing methods for icosahedral and symmetry-mismatch reconstruction of viruses by cryo-electron microscopy

Three-dimensional（3 D） reconstruction of icosahedral viruses has played a crucial role in the development of cryoelectron microscopy single-particle reconstruction, with many cryo-electron microscopy techniques first established for structural studies of icosahedral viruses, owing to their high symmetry and large mass. This review summarizes the computational methods for icosahedral and symmetry-mismatch reconstruction of viruses, as well as the likely challenges and bottlenecks in virus reconstruction, such as symmetry mismatch reconstruction, contrast transformation function（CTF）correction, and particle distortion.

Development of mathematically motivated hybrid soft computing models for improved predictions of ultimate bearing capacity of shallow foundations

Ultimate bearing capacity(UBC)is a key subject in geotechnical/foundation engineering as it determines the limit of loads imposed on the foundation.The most reliable means of determining UBC is through experiment,but it is costly and time-consuming which has led to the development of various models based on the simplified assumptions.The outcomes of the models are usually validated with the experimental results,but a large gap usually exists between them.Therefore,a model that can give a close prediction of the experimental results is imperative.This study proposes a grasshopper optimization algorithm(GOA)and salp swarm algorithm(SSA)to optimize artificial neural networks(ANNs)using the existing UBC experimental database.The performances of the proposed models are evaluated using various statistical indices.The obtained results are compared with the existing models.The proposed models outperformed the existing models.The proposed hybrid GOA-ANN and SSA-ANN models are then transformed into mathematical forms that can be incorporated into geotechnical/foundation engineering design codes for accurate UBC measurements.

Novel Proposal of Bio-based Sewing Timber Joint:Learning from Diatoms

The twenty-first century is one of the most complex in the history of humanity,mainly due to the ecological crisis it is going through.The construction sector generates about 40%of CO2 emissions into the environment;the foregoing should motivate this sector to seek new alternatives to develop new building practices.Taking these current needs into account,this document classifies and presents a multidisciplinary solution that integrates biology,engineering and architecture to develop a new and innovative lightweight timber structure;it divides with a main structure made of timber and an innovative joint system made of bio-polymers connecting all the panels.Through the study of diatoms,it was able to analyze the bio-morphology of the structure,joints and in particular the geometry since they were the inspiration for the design of this structure that presents an innovative and novel design of structural optimization.Through parametric design and digital fabrication,it was able to create a complex geometry that obtains excellent structural behavior.This research discusses and explores how materials,geometry led to the optimization of a structure and how new structures can arise,thanks to biology new solutions can be obtained that are completely sustainable,being a clear example of how to combat the effects of the climate change and in a precise way it highlights the advantages of the bio-design in the architectural design.

An integrated computational method for calculating dynamic thermal bridges of building facades in tropical countries

Identifying thermal bridges on building façades has been a great challenge for architects,especially during the conceptual design stage.This is not only due to the complexity of parameters when calculating thermal bridges,but also lack of feature integration between building energy simulation(BES)tools and the actual building conditions.For example,existing BES tools predominantly calculate thermal bridges only in steady state without considering the temperature dynamic behaviour of building outdoors.Consequently,relevant features such as thermal delay,decrement factor,and operative temperature are often neglected,and this can lead to miscalculation of energy consumption.This study then proposes an integrated method to calculate dynamic thermal bridges under transient conditions by incorporating field observations and computational simulations of thermal bridges.More specifically,the proposed method employs several measurement tools such as HOBO data logger to record the actual conditions of indoor and outdoor room temperature and thermal cameras to identify the surface temperature of selected building junctions.The actual datasets are then integrated with the simulation workflow developed in BES tools.This study ultimately enables architects not only to identify potential thermal bridges on existing building façades but also to support material and geometric exploration in early design phase.

Nonlinear Dynamic Analysis of Deepwater Drilling Risers Subjected to Random Loads

Excited by ocean currents, random wave and vessel motion, deepwater drilling risers exhibit significant dynamic response. In time domain, a method is proposed to calculate the nonlinear dynmnic response of deepwater drilling risers subjected to random wave and dynamic large displacement vessel motion boundary condition. Structural and functional loads, external and intemal pressure, free surfaee effect of irregular wave, hydrodynamic forees induced by current and wave, as well as wave and low frequency （drift） motion of the drilling vessel are all accounted for. An example is presented which illustrates the application of the proposed method. The study shows that long term drift motion of the vessel has profound effect on the envelopes of bending stress and lateral displacement, as well as the range of lower flex joint angle of the deepwater riser. It can also be concluded that vessel motion is the principal dynamic loading of nonlinear dynamic response for the deepwater risers rather than wave force.

Study on resistance coefficient in compound channels

This paper presents a further study of the Manning and Darcy-Weisbach resistance coefficients, as they play a significant role in assessing the cross-sectional mean velocity, conveyance capacity and determining the lateral distribution of depth mean velocity and local boundary shear stress in compound channels. The relationships between the local, zonal and overall resistance coefficients, and a wide range of geometries and different roughness between the main channel and the flood plain are established by analyzing a vast amount of experimental data from a British Science and Engineering Research Council Flood Channel Facility （SERC-FCF）. And the experimental results also show that the overall Darcy-Weisbach resistance coefficient for a compound channel is the function of Reynolds number, but the function relationship is different from that for a single channel. By comparing and analyzing the conventional methods with the experimental data to predict composite roughness in compound channels, it is found that these methods are not suitable for compound channels. Moreover, the reason why the conventional methods cannot assess correctly the conveyance capacity of compound channels is also analyzed in this paper.

IDSS: Designing to Extend the Cognitive Limits

The paper presents the conceptual and operational basis of the creation of IDSS based on our recent research experience. In this paper, an intelligent decision support system, IDSS is defined as: any interactive system that is specially designed to improve the decision making of its user by extending the user's cognitive decision making abilities. As a result, this view of man-machine joint cognitive system stresses the need to use computational technology to aid the user in the decision making process. And the human's role is to achieve total systems's objectives. The paper outlines the designing procedure in successive steps. First, the decision maker's cognitive needs for decision support are identified. Second, the computationally realizable support functions are defined that could be provided by IDSS. Then, the specific techniques that would best fill the decision needs are discussed. And finally, for system implementation the modern computational technology infrastructure is emphasized.

A cellular automata model for simulating grain structures with straight and hyperbolic interfaces

A description of a mathematical algorithm for simulating grain structures with straight and hyperbolic interfaces is shown. The presence of straight and hyperbolic interfaces in many grain structures of metallic materials is due to different solidification conditions, in- eluding different solidification speeds, growth directions, and delaying on the nucleation times of each nucleated node. Grain growth is a complex problem to be simulated; therefore, computational methods based on the chaos theory have been developed for this purpose. Straight and hyperbolic interfaces are between columnar and equiaxed grain structures or in transition zones. The algorithm developed in this work involves random distributions of temperature to assign preferential probabilities to each node of the simulated sample for nucleation according to previously defined boundary conditions. Moreover, more than one single nucleation process can be established in order to gen- erate hyperbolic interfaces between the grains. The appearance of new nucleated nodes is declared in sequences with a particular number of nucleated nodes and a number of steps for execution. This input information influences directly on the final grain structure （grain size and dislribution）. Preferential growth directions are also established to obtain equiaxed and columnar grains. The simulation is done using rou- tines for nucleation and growth nested inside the main function. Here, random numbers are generated to place the coordinates of each new nucleated node at each nucleation sequence according to a solidification probability. Nucleation and growth routines are executed as a func- tion of nodal availability in order to know if a node will be part of a grain. Finally, this information is saved in a two-dimensional computa- tional array and displayed on the computer screen placing color pixels on the corresponding position forming an image as is done in cellular automaton.

Structures and Vibrational Spectra of C2 and LaC2+ Clusters

C 2 and LaC + 2 were studied using Hartree Fock(HF), B3LYP (Becke 3 paremeter Lee Yang Parr) density functional method, second order Mφller Plesset perturbation(MP2) and coupled cluster singles and doubles with non iterative triples(CCSD(T)) methods. The basis set employed was LANL1DZ. Geometries, vibrational frequencies and other quantities were reported. The results showed that for C 2, all the methods performed well for low spin state(singlet), while only HF and B3LYP remained so for high spin state(triplet). For LaC + 2, four isomers were presented and fully optimized. The results suggested that linear isomers with C ∞v and D ∞h symmetries were predicted to be saddle points on the energy surface for all the methods, while for isomers with C 2v and C s symmetries, they were local minima except C 2v at B3LYP level, and were isoenergetic at HF, MP2 and CCSD(T) levels, near isoenergetic at B3LYP level. From the differences between HOMO and LUMO, it is also known that the isomers with C 2v and C s symmetries offer the largest values and therefore correspond to the most stable structure. For La—C bond lengths, B3LYP gives the shortest, the order is B3LYP<HF<MP2<CCSD(T) for all the methods.

CORBA-Based Discrete Event Simulation System

The CORBA technique is an integration of the object-oriented conception and distributed computing technique. It can make the application within distributed heterogeneous environments reusable, portable and interoperable. The architecture of CORBA-based discrete event simulation systems is presented and the interface of distributed simulation objects (DSO) is defined in this paper after the DSO is identified and the synchronization mechanism among DSO is discussed.

On the Solutions of the Matrix Equations in Optimal Stochastic Control

In this paper, the matrix algebraic equations involved in the optimal control problem of time-invariant linear Ito stochastic systems, named Riccati- Ito equations in the paper, are investigated. The necessary and sufficient condition for the existence of positive definite solutions of the Riccati- Ito equations is obtained and an iterative solution to the Riccati- Ito equations is also given in the paper thus a complete solution to the basic problem of optimal control of time-invariant linear Ito stochastic systems is then obtained. An example is given at the end of the paper to illustrate the application of the result of the paper.

Study on the System Design of Multiple Expert Systems Integrated Decision Support System

There has been an increasing interest in integrating decision support systems (DSS) and expert systems (ES) to provide decision makers a more accessible, productive and domain-independent information and computing environment. This paper is aimed at designing a multiple expert systems integrated decision support system (MESIDSS) to enhance decision makers' ability in more complex cases. The basic framework, management system of multiple ESs, and functions of MESIDSS are presented. The applications of MESIDSS in large-scale decision making processes are discussed from the following aspects of problem decomposing, dynamic combination of multiple ESs, link of multiple bases and decision coordinating. Finally, a summary and some ideas for the future are presented.

Algorithm for Computation of Unstructured Real Stability Radius and Its Applications

An algorithm for the computation of the unstructured real stability radius of high dimensional linearsystem is presented. Using the accurate formula of the real stability radius of 2-dimensional system linear systemchecks the algorithm. The result shows that the algorithm is reliable and efficient. As applications, the unstructuredreal stability radii of 2-dimensional Chua's circuit and 3-dimensional piecewise-linear system are calculated, thedynamical orbits of the corresponding perturbed systems are simulated.