Numerical Analysis of Bacterial Meningitis Stochastic Delayed Epidemic Model through Computational Methods

Based on theWorld Health Organization(WHO),Meningitis is a severe infection of the meninges,the membranes covering the brain and spinal cord.It is a devastating disease and remains a significant public health challenge.This study investigates a bacterial meningitis model through deterministic and stochastic versions.Four-compartment population dynamics explain the concept,particularly the susceptible population,carrier,infected,and recovered.The model predicts the nonnegative equilibrium points and reproduction number,i.e.,the Meningitis-Free Equilibrium(MFE),and Meningitis-Existing Equilibrium(MEE).For the stochastic version of the existing deterministicmodel,the twomethodologies studied are transition probabilities and non-parametric perturbations.Also,positivity,boundedness,extinction,and disease persistence are studiedrigorouslywiththe helpofwell-known theorems.Standard and nonstandard techniques such as EulerMaruyama,stochastic Euler,stochastic Runge Kutta,and stochastic nonstandard finite difference in the sense of delay have been presented for computational analysis of the stochastic model.Unfortunately,standard methods fail to restore the biological properties of the model,so the stochastic nonstandard finite difference approximation is offered as an efficient,low-cost,and independent of time step size.In addition,the convergence,local,and global stability around the equilibria of the nonstandard computational method is studied by assuming the perturbation effect is zero.The simulations and comparison of the methods are presented to support the theoretical results and for the best visualization of results.

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.

Numerical Study on the Aerodynamic and Fluid−Structure Interaction of An NREL-5MW Wind Turbine

A 5-MW wind turbine has been modeled and analyzed for fluid-structure interaction and aerodynamic performance.In this study, a full-scale model of a 5-MW wind turbine is first developed based on a computational fluid dynamics(CFD) approach, in which the unsteady, noncompressible Reynolds Averaged Navier-Stokes(RANS) method is used. The main focus of the study is to analyze the tower shadow effect on the aerodynamic performance of the wind turbine under different inlet flow conditions. Subsequently, the finite element model is established by considering fluid/structure interactions to study the structural stress, displacement, strain distributions and flow field information of the structure under the uniform wind speed. Finally, the fluid-structure interaction model is established by considering turbulent wind and the tower shadow effect. The variation rules of the dynamic response of the one-way and two-way fluid-structure interaction(FSI) models under different wind speeds are analyzed, and the numerical calculation results are compared with those of the centralized mass model. The results show that the tower shadow effect and structural deformation are the main factors affecting the aerodynamic load fluctuation of the wind turbine, which in turn affects the aerodynamic performance and structural stability of the blades. The structural dynamic response of the coupled model shows significant similarity, while the structural displacement response of the former exhibits less fluctuation compared with the conventional centralized mass model. The one-way fluid-structure interaction(FSI)model shows a higher frequency of stress-strain and displacement oscillations on the blade compared with the two-way FSI model.

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.

Applications of Soft Computing Methods in Backbreak Assessment in Surface Mines: A Comprehensive Review

Geo-engineering problems are known for their complexity and high uncertainty levels,requiring precise defini-tions,past experiences,logical reasoning,mathematical analysis,and practical insight to address them effectively.Soft Computing(SC)methods have gained popularity in engineering disciplines such as mining and civil engineering due to computer hardware and machine learning advancements.Unlike traditional hard computing approaches,SC models use soft values and fuzzy sets to navigate uncertain environments.This study focuses on the application of SC methods to predict backbreak,a common issue in blasting operations within mining and civil projects.Backbreak,which refers to the unintended fracturing of rock beyond the desired blast perimeter,can significantly impact project timelines and costs.This study aims to explore how SC methods can be effectively employed to anticipate and mitigate the undesirable consequences of blasting operations,specifically focusing on backbreak prediction.The research explores the complexities of backbreak prediction and highlights the potential benefits of utilizing SC methods to address this challenging issue in geo-engineering projects.

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.

抓持接触力的空间分解及计算(英文)

Robotic hands grasp and manipulate objects through the contact forces between the fingers and the objects. The determination of contact forces in grasping is discussed in this paper. To systematically investigate the characteristics of different grasps, the vector space of contact forces is decomposed into four subspaces and their basis is found by an efficient computational method. The vector of contact forces is then formulated into four components: active and passive grasping forces, controllable and uncontrollable internal forces. The dimensions of the subspaces identify uncontrollable internal forces. The contact force is further expressed into an explicit function of the external wrench and the joint torques. The resulting formulation simplifies the computation in the optimization of contact forces and makes the optimal variables controllable. Two numerical cases are given to show the simplicity and validity of the method.

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.

EXPERIMENTAL INVESTIGATION OF AERODYNAMICINTERACTION EFFECT OF ROTOR WAKE ONFUSELAGE OF HELICOPTER

The interaction effect of rotor wake on fuselage of helicopter was investigated with experimental method. The results from experiment have proved that for the drag of fuselage the effect of rotor airflow is closely in connection with both the flight speed and the collective pitch of blades, while for the thrust and pitch moment of fuselage the collective pitch angle of blades plays more important role. A simple and effective computing method about aerodynamic interaction can be derived from the measured data. In order to implement the experiment, a fuselage model, a special sensor, the measurement and data acquisition and processing system were designed and manufactured according to the special requirements of this research project, thereby a good base was built up for carrying out experiments successfully with high quality.

Theoretical and Comparative Study of the Complex[RuCl_(3)(H_(2)O)_(2)(Gly)]by Density Functional Theory

In this work, the use of computational methods was essential to distinguish the three possible isomeric structures of the [RuCl3(H2O)2(Gly)] molecule. The characterization of these molecules was performed using IR, NMR and UV-VIS simulations. Some calculations related to the optimization of structures and properties such as chemical hardness and dipole moment were also conducted. The fac-cis isomer presented promising data when compared to the experimental data, indicating that this is the likely experimentally synthesized isomer. This study demonstrates the technical utility of the computational calculations by virtue of situations that prevent the realization of X-ray diffraction.