Computational Aspects Research Articles

Study of Plasma-Based Vortex Generator in Supersonic Turbulent Boundary Layer

The problem of flow control under conditions of a turbulent boundary layer at transonic and supersonic free-stream velocities is considered. Such flows are integral components of the flight process and exert significant effects on the flow around both the aerodynamic object as a whole and its individual elements. The present paper describes investigations of a combined control device (“plasma wedge”), which is a wedge mounted along the flow with the energy supply at one side of the wedge owing to a spark discharge. The strategy of flow control by this device is based on increasing the momentum in the boundary layer, which enhances its resistance to the adverse pressure gradient and, as a consequence, its resistance to flow separation further downstream. The study includes experimental and computational aspects. The examined flow evolves on a rectangular flat plate with a sharp leading edge at the free-stream Mach number M = 1.45 and unit Reynolds numbers Re1 = 11.5·106 1/m. The experiments are performed to study the velocity fields and the pressure distribution in the wake behind the actuator. The results show that a streamwise vortex is formed in the wake behind the actuator when the discharge is initiated. Reasonable agreement of the experimental data with numerical simulations allows one to conclude that the Reynolds-averaged Navier–Stokes equations are suitable tools for solving the problem considered.

Artificial Intelligence and Advanced Materials.

Artificial intelligence (AI) is gaining strength, and materials science can both contribute to and profit from it. In a simultaneous progress race, new materials, systems, and processes can be devised and optimized thanks to machine learning (ML) techniques, and such progress can be turned into innovative computing platforms. Future materials scientists will profit from understanding how ML can boost the conception of advanced materials. This review covers aspects of computation from the fundamentals to directions taken and repercussions produced by computation to account for the origins, procedures, and applications of AI. ML and its methods are reviewed to provide basic knowledge of its implementation and its potential. The materials and systems used to implement AI with electric charges are finding serious competition from other information-carrying and processing agents. The impact these techniques have on the inception of new advanced materials is so deep that a new paradigm is developing where implicit knowledge is being mined to conceive materials and systems for functions instead of finding applications to found materials. How far this trend can be carried is hard to fathom, as exemplified by the power to discover unheard of materials or physical laws buried in data.

Design and characterization of a binary CT complex of imidazole-oxyresveratrol: exploring its pharmacological and computational aspects

A new binary charge transfer (CT) complex between imidazole (IMZ) and oxyresveratrol (OXA) was synthesized and characterized experimentally and theoretically. The experimental work was carried out in solution and solid state in selected solvents such as chloroform (CHL), methanol (Me-OH), ethanol (Et-OH), and acetonitrile (AN). The newly synthesized CT complex (D1) has been characterized by various techniques such as UV-visible spectroscopy, FTIR, 1H-NMR, and powder-XRD. The 1:1 composition of D1 is confirmed by Jobs’ method of continuous variation and spectrophotometric (at λmax 554 nm) methods at 298 K. The infrared spectra of D1 confirmed the existence of proton transfer hydrogen bond beside charge transfer interaction. These findings indicate that the cation and anion are joined together by the weak hydrogen bonding as N+–H–O–. Reactivity parameters strongly recommended that IMZ behaves as a good electron donor and OXA an efficient electron acceptor. Density functional theory (DFT) computations with basis set B3LYP/6-31G (d,p) was applied to support the experimental results. TD-DFT calculations gives HOMO (−5.12 eV) → LUMO (−1.14 eV) electronic energy gap ( Δ E ) to be 3.80 eV. The bioorganic chemistry of D1 was well established after antioxidant, antimicrobial, and toxicity screening in Wistar rat. The type of interactions between HSA and D1 at the molecular level was studied through fluorescence spectroscopy. Binding constant along with the type of quenching mechanism, was investigated through the Stern-Volmer equation. Molecular docking demonstrated that D1 binds perfectly with human serum albumin and EGFR (1M17) and exposes free energy of binding (FEB) values of −295.2 and −283.3 kcal/mol, respectively. The D1 fits successfully into the minor groove of HAS and 1M17, the results of molecular docking show that the D1 binds perfectly with the HAS and 1M17, the higher value of binding energy shows stronger interaction between HAS and 1M17 with D1. Our synthesized complex shows good binding results with HAS compared to 1M17. Communicated by Ramaswamy H. Sarma

The Integration of WoT and Edge Computing: Issues and Challenges

The Web of Things is an improvement on the Internet of Things (IoT) that incorporates smart objects into both the web architecture (application) and the internet (network). WoT applications are inescapable in residential homes and communities. The intent behind WoT applications is to increase sustainable development for reducing resource consumption. The Web of Things (WoT) aims to create a decentralized Internet of Things. Edge computing addresses IoT computing demands by reducing the escalation in resource congestion situations. In edge computing data is placed closed to the end users which diverts computation load from the centralized data centers. Furthermore, the dispersed structure balances network traffic and minimizes traffic peaks in IoT networks. Therefore, resulting in reducing transmission delays between edge servers and end users which improves response times for real-time WoT applications. Low battery supply to nodes with enough power resources can increase the lifespan of the individual nodes by moving processing and communication overhead from the nodes. This paper integrates WoT and edge computing and compares their functionalities. In addition, it demonstrates how edge computing enhances WoT performance and concentrates on transmission, storage, and computation aspects. Furthermore, for performance evaluation it categorizes edge computing based on different architectures. Moreover, the challenges of Web of Things and edge computing have been discussed in terms of bandwidth, latency, energy, and cost. Finally, advantages of the Web of Things and edge computing have been discussed.

English

The present paper is devoted to study some completeness properties of transitive binary relational set, i.e., a set together with a transitive binary relation (so called t-set). We hope that the results of our paper will be a starting point for a sufficiently general but simple theory of objects that are suitable for modelling various aspects of computation and useful in modern applications of domain theory to general topology and mathematical analysis.

A special issue on Bayesian inference: challenges, perspectives and prospects.

A special issue on Bayesian inference: challenges, perspectives and prospects.

Computational aspects of two important biochemical networks with respect to some novel molecular descriptors

Quantitative structure-activity relationship (QSAR) represents quantitative correlation of biological structural features (called as topological indices) and pharmacological activity as response endpoints. Topological index is a molecular descriptor extensively used to study QSAR of pharmaceutical to assess their molecular characteristics by numerical computation. Meanwhile, the topological indices are numerical functions which are used to predict the growth rate of microorganisms in biological networks. Theoretical assessment of microorganism, such as bacteria and viruses help to expedite the vaccine design and discovery process by rationalizing the lead identification, lead optimization and understanding their mechanism of actions. Hypertree, a network structure derived from graph theory, has a great importance in biological networks for growth of microorganisms, such as bacteria and viruses. In this article, some novel eccentric and degree based topological features of two important biological networks (hypertree and its corona product) are obtained on h-level and derived closed formulas for them. Based on the obtained topological features, the biological properties of these networks are investigated. Communicated by Ramaswamy H. Sarma

Structural requirement of RARγ agonism through computational aspects

RARγ is a therapeutic target for many skin diseases and has potential in cancer treatment. In the current study, we put forward a comprehensive structure-activity relationship study of third and fourth generations of RARγ agonists, addressing multiple crystal structures of RARγ complexes and approved drugs. Adapalene and Trifarotene, through hybrid strategies including protein contacts Atlas analysis, molecular docking, dynamics simulations, MM-GBSA, ASM, and pharmacophore modeling. Our result revealed crucial amino acids Arg267, Ser278, Phe288, Phe230, Met272, Leu271, and Leu268 within the RARγ pocket, as well as pharmacophore features such as two hydrophobic groups, two aromatic rings, and negative ionic features, which are essential for the binding of RARγ agonists. Based on this study, the binding mechanism of RARγ agonists was elucidated, which will be helpful for the rational design of new RARγ agonists for skin diseases and cancer treatment. In this study, Schrödinger suite 2021-2 with OPLS_4 force field, Discovery Studio program 3.0, LigandScout 4.3, and PyMOL are utilized in the investigation.

Machine Learning and AI Technologies for Smart Wearables

The recent progress in computational, communications, and artificial intelligence (AI) technologies, and the widespread availability of smartphones together with the growing trends in multimedia data and edge computation devices have led to new models and paradigms for wearable devices. This paper presents a comprehensive survey and classification of smart wearables and research prototypes using machine learning and AI technologies. The paper aims to survey these new paradigms for machine learning and AI for wearables from various technological perspectives which have emerged, including: (1) smart wearables empowered by machine learning and AI; (2) data collection architectures and information processing models for AI smart wearables; and (3) applications for AI smart wearables. The review covers a wide range of enabling technologies for AI and machine learning for wearables and research prototypes. The main findings of the review are that there are significant technical challenges for AI smart wearables in networking and communication aspects such as issues for routing and communication overheads, information processing and computational aspects such as issues for computational complexity and storage, and algorithmic and application-dependent aspects such as training and inference. The paper concludes with some future directions in the smart wearable market and potential research.

Cousin complexes via total fractions

With respect to the filtration provided by codimensions of points on a locally Noetherian scheme, we give a new approach to Cousin complexes of sheaves of modules using total fractions. Concrete examples are worked out to illustrate the computational aspect of Cousin complexes.

Complexity, algorithmic, and computational aspects of a dial-a-ride type problem

In dial-a-ride systems involving autonomous vehicles circulating along a circuit, a fleet of vehicles must serve clients who request rides between stations of the circuit such that the total number of pick-up and drop-off operations is minimized. In this paper, we focus on a unitary variant where each client requests a single place in the vehicles and all the clients must be served within a single tour of the circuit. Such unitary variant induces a combinatorial optimization problem for which we introduce a nontrivial special case that is polynomially solvable when the capacity of each vehicle is at most 2 but it is NP-Hard otherwise. We also study the polytope associated with the solutions to this problem. We introduce new families of valid inequalities and give necessary and sufficient conditions under which they are facet-defining. Based on these inequalities, we devise an efficient branch-and-cut algorithm that outperforms the state-of-the-art commercial solvers.

Different Control Strategies Drive Interlimb Differences in Performance and Adaptation during Reaching Movements in Novel Dynamics.

Humans exhibit lateralization such that most individuals typically show a preference for using one arm over the other for a range of movement tasks. The computational aspects of movement control leading to these differences in skill are not yet understood. It has been hypothesized that the dominant and nondominant arms differ in terms of the use of predictive or impedance control mechanisms. However, previous studies present confounding factors that prevented clear conclusions: either the performances were compared across two different groups, or in a design in which asymmetrical transfer between limbs could take place. To address these concerns, we studied a reach adaptation task during which healthy volunteers performed movements with their right and left arms in random order. We performed two experiments. Experiment 1 (18 participants) focused on adaptation to the presence of a perturbing force field (FF) and experiment 2 (12 participants) focused on rapid adaptations in feedback responses. The randomization of the left and right arm led to simultaneous adaptation, allowing us to study lateralization in single individuals with symmetrical and minimal transfer between limbs. This design revealed that participants could adapt control of both arms, with both arms showing similar performance levels. The nondominant arm initially presented a slightly worst performance but reached similar levels of performance in late trials. We also observed that the nondominant arm showed a different control strategy compatible with robust control when adapting to the force field perturbation. EMG data showed that these differences in control were not caused by differences in co-contraction across the arms. Thus, instead of assuming differences in predictive or reactive control schemes, our data show that in the context of optimal control, both arms can adapt, and that the nondominant arm uses a more robust, model-free strategy likely to compensate for less accurate internal representations of movement dynamics.

A Passive System Technical Specification for CANDU 6 Generation II Reactor

The Fukushima accident led to concerns about enhancement of safety for the new design nuclear plants and also for the existing fleet of nuclear power plants (NPPs) by introducing passive safety systems. An important objective is to increase the grace time for a plant operator to establish an alternate heat sink in the case of a station blackout (SBO) accident. Efforts made by RATEN (https://www.raten.ro/?lang=en) in the frame of H2020 PIACE projects were to implement a passive safety system in the CANadian Deuterium Uranium 6 (CANDU 6) project. In this project, RATEN was in charge of the engineering design and computational modeling aspects, required to integrate a passive safety system in the existing CANDU 6 project. In order to design a passive safety system, a 3-day SBO accident was credited to occur at the Cernavoda Unit 2 NPP, a CANDU 6–type reactor. An isolation condenser (IC) system capable of transporting the total energy produced in the reactor core due to decay heat was designed and modeled. The engineering design solutions were made by RATEN CITON (http://www.citon.ro/english_index.html), and the thermal-hydraulic analysis was performed by RATEN ICN (https://nuclear.ro/en/) using the RELAP5 computer code (https://relap53d.inl.gov/SitePages/Home.aspx) to confirm natural circulation both in the secondary and the primary circuits during the SBO accident and heat transfer capability of the IC with and without noncondensable gases. The passive safety system design consists of four (4 × 33%) closed loop independent circuits, one for each steam generator. Each loop has an IC design to transport 0.66% of nominal thermal power of the reactor. In order to avoid a rapid transient during reactor cooldown, the system is endowed with four noncondensable gas tanks (one for each IC), connected to the outlet header of each IC, provided for reducing the IC heat flux simultaneously with reactor core residual heat decrease. The design concept was adapted to the CANDU 6 reactor power and the specific layout of the Cernavoda site, starting from the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED) patent (the demonstrator of lead fast reactor technology) passive system, to increase the plant operator grace time from 23 h (current situation) to more than 72 h.

Preface: 2022 International Conference on Theoretical Physics, Computers and Electronic Engineering (TPCEE 2022)

This volume contains papers accepted by the 2022 International Conference on Theoretical Physics, Computers and Electronic Engineering (TPCEE 2022), which was held online during December 30-31, 2022 in Toronto, Canada. TPCEE 2022 brought together innovative scholars and industry experts to jointly hold a forum. The main objective of the conference is to promote the research and development activities of theoretical physics, astrophysics, quantum physics, computer engineering, information technology and electronic engineering, and the other objective is to promote the exchange of scientific information among researchers, developers, engineers, students and practitioners around the world.
 Over 200 participants from many countries attended this online conference, which included 4 keynote speeches and 48 oral presentations on different aspects of theoretical physics, computers and electronic engineering in 4 sections. The cutting-edge research works were presented by such renowned keynote speakers. The virtual format of TPCEE 2022 was a success where all the participants gathered on the online platform regardless of the time zone and location and share experiences and research findings in their respective fields.
 Organizing Committees of TPCEE 2022
 Toronto, Canada

Computational aspects of experimental designs in multiple-group mixed models

We extend the equivariance and invariance conditions for construction of optimal designs to multiple-group mixed models and, hence, derive the support of optimal designs for first- and second-order models on a symmetric square. Moreover, we provide a tool for computation of D- and L-efficient exact designs in multiple-group mixed models by adapting the algorithm of Harman et al. (Appl Stoch Models Bus Ind, 32:3–17, 2016). We show that this algorithm can be used both for size-constrained problems and also in settings that require multiple resource constraints on the design, such as cost constraints or marginal constraints.

The K-mer antibiotic resistance gene variant analyzer (KARGVA).

Characterization of antibiotic resistance genes (ARGs) from high-throughput sequencing data of metagenomics and cultured bacterial samples is a challenging task, with the need to account for both computational (e.g., string algorithms) and biological (e.g., gene transfers, rearrangements) aspects. Curated ARG databases exist together with assorted ARG classification approaches (e.g., database alignment, machine learning). Besides ARGs that naturally occur in bacterial strains or are acquired through mobile elements, there are chromosomal genes that can render a bacterium resistant to antibiotics through point mutations, i.e., ARG variants (ARGVs). While ARG repositories also collect ARGVs, there are only a few tools that are able to identify ARGVs from metagenomics and high throughput sequencing data, with a number of limitations (e.g., pre-assembly, a posteriori verification of mutations, or specification of species). In this work we present the k-mer, i.e., strings of fixed length k, ARGV analyzer - KARGVA - an open-source, multi-platform tool that provides: (i) an ad hoc, large ARGV database derived from multiple sources; (ii) input capability for various types of high-throughput sequencing data; (iii) a three-way, hash-based, k-mer search setup to process data efficiently, linking k-mers to ARGVs, k-mers to point mutations, and ARGVs to k-mers, respectively; (iv) a statistical filter on sequence classification to reduce type I and II errors. On semi-synthetic data, KARGVA provides very high accuracy even in presence of high sequencing errors or mutations (99.2 and 86.6% accuracy within 1 and 5% base change rates, respectively), and genome rearrangements (98.2% accuracy), with robust performance on ad hoc false positive sets. On data from the worldwide MetaSUB consortium, comprising 3,700+ metagenomics experiments, KARGVA identifies more ARGVs than Resistance Gene Identifier (4.8x) and PointFinder (6.8x), yet all predictions are below the expected false positive estimates. The prevalence of ARGVs is correlated to ARGs but ecological characteristics do not explain well ARGV variance. KARGVA is publicly available at https://github.com/DataIntellSystLab/KARGVA under MIT license.

On the strategy of emphasizing disruptive computer-based approaches when teaching astronomy to promote related careers

The knowledge attained in the last decades in space physics, and in particular in Astronomy, has attracted, in part due to its associated computational innovation components, the attention of young students all over the world. Thus, both teaching and the scientific dissemination of knowledge in these areas should seek to guide, based on this interdisciplinary characteristic, talented young people towards related careers. By introducing Space Physics and Astronomy as data-driven sciences, and with a high dependence on computer simulation and disruptive technologies, we make the research and development activities associated with them even more attractive. In this article we highlight the program called Decolar Astronomia (DA), an initiative carried out in the city of S˜aoJos´e dos Campos, SP, Brazil. In the DA 2022 edition, eight activities were formulated with the aim of emphasizing the relevance of computational knowledge in space sciences with an emphasis on 21st century Astronomy. In addition to describing the activities that were applied under DA-2022, we present a more general strategy that can be applied by any other program. This strategy emphasizes computational aspects (such as data-driven science and disruptive technologies) related to Astronomy, in motivating teaching programs for young students. The expected result, after applying this strategy, is that the interest in Astronomy and related careers becomes even greater.

Uncertainty quantification in inerter-based quasiperiodic lattices

Inerter-based periodic structures have attracted significant interest among the research community due to their wide range of applications. However, existing studies on quasiperiodic structures, especially with inerters, are limited. Therefore, this timely work investigates the dynamics of novel one-dimensional inerter-based quasiperiodic lattices with and without local resonators. The quasiperiodicity is introduced through the modulation of both spring and inerter properties resulting in the well-known Hofstadter-like butterfly spectrum having a fractal structure. Moreover, by considering the appropriate boundary conditions and many mass–spring-inerter subsystems, the bulk spectrum of the system is investigated demonstrating the existence of multiple edge states in lower and higher frequency ranges. The deterministic study showed that the effect of inertia amplification is to reduce the frequencies of the Hofstadter-like butterfly and to widen the low frequency band gaps. The second contribution of this work involves investigating the effect of parametric uncertainty for the acoustic-metamaterial-like chain based on Monte Carlo simulations. Moreover, to address the computational aspect of the problem, grey-box modeling using machine learning was performed. A Gaussian process model was trained on a limited dataset and was found to capture the stochastic responses of the lattices adequately. The statistical variation of parameters with different levels of uncertainty demonstrated significant effects on the Hofstadter-like butterfly, band gaps, corresponding edge states and frequency responses. The sensitivity of the dynamic behavior in quasiperiodic lattices to variabilities reveal the need to account for system uncertainties for their targeted performance as future vibration absorbers and energy harvesters. The study also paves the way to utilize the results as useful prior information for robust design optimization of real inerter-based quasiperiodic lattice devices.

EEG-Based BCIs on Motor Imagery Paradigm Using Wearable Technologies: A Systematic Review.

In recent decades, the automatic recognition and interpretation of brain waves acquired by electroencephalographic (EEG) technologies have undergone remarkable growth, leading to a consequent rapid development of brain-computer interfaces (BCIs). EEG-based BCIs are non-invasive systems that allow communication between a human being and an external device interpreting brain activity directly. Thanks to the advances in neurotechnologies, and especially in the field of wearable devices, BCIs are now also employed outside medical and clinical applications. Within this context, this paper proposes a systematic review of EEG-based BCIs, focusing on one of the most promising paradigms based on motor imagery (MI) and limiting the analysis to applications that adopt wearable devices. This review aims to evaluate the maturity levels of these systems, both from the technological and computational points of view. The selection of papers has been performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), leading to 84 publications considered in the last ten years (from 2012 to 2022). Besides technological and computational aspects, this review also aims to systematically list experimental paradigms and available datasets in order to identify benchmarks and guidelines for the development of new applications and computational models.

Preface

1st International Conference on Fluid Dynamics and Computational Science (FDCS 2022) included original and peer-reviewed research papers and held on November 12-13, 2022, in Chengdu, China. This conference was co-organized by Southwest Jiaotong University, Huazhong University of Science and Technology, Tiangong University, sponsored by CCCC Second Harbour Engineering Company Ltd., Asian Union of Information Technology.FDCS is an annual international conference devoted to the discussion of original work on theoretical, computational, and experimental aspects of the mechanics of fluids, with special regards to the Navier-Stokes equations. FDCS conference covers the field of CFD; heat transfer and thermodynamics; multi-phase flows; fluid-structure interaction; combustion; turbulence; shock waves and explosions; plasma flow.FDCS aims to provide a knowledge exchange and sharing platform of physical and computational sciences for the aviation industry, automobile industry, shipbuilding industry, etc. We welcome experts in fields related to fluid dynamics and computational science to join us.This conference was organized in technical association with the Asian Union of Information Technology and included invited keynote talks and oral paper presentations from both academia and industry. The topics covered in this FDCS 2022 are: 1. Computational Fluid Dynamics; 2. Heat Transfer and Thermodynamics; 3. Physical and Computational Sciences; 4. Other Topics in Fluid Dynamics. Each keynote speakers lasted for 30 minutes, including 5 minutes for Q&A. and for other sessions, there was 20 minutes for each presentation, including 5 minutes for Q&A. The book is useful to professionals and scientists involved or interested in fluid mechanics and industrial applications. Hopefully, all participants and other interested readers would benefit scientifically from the proceedings and also find it stimulating in the process.We would like to thank all the author submitted papers to this FDCS 2022 and thank all the reviewers for their time and effort in reviewing articles. Especially we would like to thank the organizing committee for their valuable advices in the organization and helpful peer review of the papers.Conference Organizing Committee,Wuhan, ChinaList of Committees, Chairmen, Members are available in this pdf.