Transformation Rules Research Articles

Response surface methodology in optimizing heat transfer rate for homogeneous–heterogeneous reactions with thermal radiation effect on the micropolar nanofluid

The non-Newtonian characteristic of the fluid flow phenomena has several applications in industries, engineering gadgets, biomedical sectors, etc. Based upon the aforementioned role, the present work deals with the nanofluid flow of micropolar fluid through an elongated surface is investigated. Further, the influence of radiating heat due to thermal radiation, and nanoparticle concentration is presented which are vital for the heat transfer enhancement. However, the inclusion of homogenous as well as heterogeneous chemical reactions enriches the study. Additionally, carbon nanotube (CNT) nanoparticles such as “Single-Wall Carbon Nanotube (SWCNT) and Multi-Wall Carbon Nanotube (MWCNT)” nanoparticles are used in water to perform the behavior of different nanofluids. The designed model with dimensional form is developed by converting these to dimensionless forms with the help of similarity transformation rules. The finalized transformed equations are handled numerically with the help of the shooting-based Runge-Kutta-fourth-order technique in a MATLAB environment. The proposed study became novel due to the statistical analysis for optimizing heat transfer rate for several components using “Response Surface methodology” based on the “Central Composite Design” model. Further, the ANOVA (Analysis of Variance) test is carried out for the best-fit model which is beneficial for the regression analysis. The exact solution for the velocity profile using the proposed method is validated by comparing it with a previously published numerical result in some limited cases, and an excellent agreement is established. However, the observation shows that the particle concentration of both the CNT particles augments the axial velocity and fluid temperature whereas reverse impact is rendered for the angular velocity.

Performance of carbon nanotubes (CNTs) on the development of radiating hybrid nanofluid flow through an stretching cylinder

In various industries, one of the important aspects is the cooling processes for which the material exhibits its perfect shape and size. Intending to the aforementioned property the current investigation leads to carry out the features of the materialistic property of thermal radiation and the dissipative heat by incorporating these in the water-based hybrid nanofluid. The fluid past a stretching cylinder embedded with a permeable medium and the impact of the magnetic field, and thermal radiation are depicted in momentum and energy profiles. In addition to that, the role of the Hamilton-Crosser conductivity model for the behavior of various shapes of the carbon nanotube (CNT) nanoparticles with their volume concentration is also vital. The transformation of the dimensional form of the governing equations into the non-dimensional form is obtained with the use of proper transformation rules. Further, the proposed designed model is handled by employing the traditional shooting-based Runge-Kutta fourth-order technique. The significant properties of different components are deployed graphically and the validation with earlier study shows a good correlation. Moreover, the important characteristics of the outcomes are; the surface cooling, driven by increased thermal buoyancy, promotes fluid velocity while simultaneously influencing the curvature parameter and profile to slow down the accumulation of nanoparticles.

Control of radiating heat on the heat transfer of polar hybrid nanofluid flow through a vertical permeable plate

The recent applications in industrial products and engineering need high thermal efficiency for the betterment of the shape of the products, the concept of hybrid nanofluid is significant in comparison to nanofluid and pure fluid. Therefore, this analysis focuses on the flow of a micropolar hybrid nanofluid over a vertical permeable plate. The study considers free convection of an electrically conducting fluid, incorporating metal and oxide components with a water-based hybrid nanofluid. Further, the conjunction of dissipative and radiating heat with generative/absorptive heat enhances the thermal properties. The use of standard transformation rules gives rise to converting the nondimensional form of concerned PDEs to ODEs. Moreover to get rid of the solution, for the nondimensional set of equations, a shooting-based numerical technique like Runge–Kutta (RK)-fourth-order is adopted for the standard values of several components within their range. The effectiveness of these parameters is studied and displayed through graphs. The computed result of the rate coefficients at the surface is depicted in tabular form. The comparative analysis with earlier work studied by considering the base liquid shows a good correlation in particular cases. However, the important outcomes are, the magnetized nano as well as hybrid nanoparticles produces a thicker momentum boundary layer thickness whereas it enhances the fluid temperature.

Design of a multi-target focused library for antidiabetic targets using a comprehensive set of chemical transformation rules.

Virtual small molecule libraries are valuable resources for identifying bioactive compounds in virtual screening campaigns and improving the quality of libraries in terms of physicochemical properties, complexity, and structural diversity. In this context, the computational-aided design of libraries focused against antidiabetic targets can provide novel alternatives for treating type II diabetes mellitus (T2DM). In this work, we integrated the information generated to date on compounds with antidiabetic activity, advances in computational methods, and knowledge of chemical transformations available in the literature to design multi-target compound libraries focused on T2DM. We evaluated the novelty and diversity of the newly generated library by comparing it with antidiabetic compounds approved for clinical use, natural products, and multi-target compounds tested in vivo in experimental antidiabetic models. The designed libraries are freely available and are a valuable starting point for drug design, chemical synthesis, and biological evaluation or further computational filtering. Also, the compendium of 280 transformation rules identified in a medicinal chemistry context is made available in the linear notation SMIRKS for use in other chemical library enumeration or hit optimization approaches.

Towards Automation of the FORM/BCS Method

The software industry is facing more complex computer systems, with short development and sustainability issues. To deliver good software with these constraints, software reuse has become a central concept for minimizing design and realization costs. This study improves upon Feature-Oriented Reuse Method with Business Component Semantics (FORM/BCS), a software development method that produces adaptable architectures from reusable domain components. This is a promising method for reusable software assets and model creation. The objective of the FORM/BCS is to bring the industrial production chain to the software. This study proposes a model to automatically transform the FORM/BCS business subsystem component into a process business component. Two metamodels for business subsystems and process business components were developed. In addition, this study establishes correspondences between the source metamodel and target metamodel classes, transformation rules, and the instance of the source metamodel and generates the target metamodel instance. Detailed findings can help practitioners reduce software design costs and development time, and contribute to the advancement of knowledge in software engineering.

Sprouting Tree for Physiological Stress Assessment Using Fuzzy Petri Net

Background: Stressors have a huge impact on one’s well-being. They affect individual’s mental and physical health, if untreated. The response to these stresses is termed as a stress response. Based on the type and severity of the stimulus, stress can affect the various actions and functioning of the body. This explains how important it becomes to detect the level of stress and treat it well. The best treatment for stress is to identify the factors causing stress and eliminate them in the initial stage. Various methods have been proposed to detect the level of stress. One of the common methods is by using wearable devices to capture EEG signals and use various proposed algorithms to detect the level of stress. However, there are cases where stress cannot be captured by non-invasive technologies. Besides, these technologies cannot determine the stress-causing factors. This paper proposes a methodology to cater to such cases and identify the factors causing stress in the patient. It can also act as a front line methodology to detect if the candidate is suffering from anxiety or stress. The use of fuzzy logic in various healthcare areas has become very evident. This is because it deals with a range of values. While, Petri nets is a network where the arc runs from place to transition and not between places and transitions. It is the best model to use in dynamic and concurrent activities of the system. Thus, a combination of these two logics can provide an extremely competent basis for the implementation of computing reasoning processes and the modeling of systems with uncertainty. Thus, Fuzzy Petri Nets (FPN) have been proposed. This paper proposes the use of FPN in designing a methodology for factors responsible for causing stress and advancing the level of stress in the patient. The methodology is developed by observing the process of food transfer in plants. The authors have also discussed afferent and efferent stress paths. Method: The methodology proposed in this paper uses Fuzzy Petri Net. The algorithm designed in this paper has been named as the Sprouting tree algorithm by the authors. Designing the fault tree is the first and very important step for the correct determination of the level of the stress. The score generated using the Hamilton scale is fed as input to the AND/OR gate system to receive the value of stressor, and thus, drawing a fault tree. The transformation rules are applied to convert the fault tree into the FPN. Then, we derive production rules and reachability matrix. These rules help in normalizing the value obtained via fault tree so that they lie in the range of fuzzy logic. FPN calculates the certainty factor (CF), which represents the state of stress in an individual. Therefore, the values obtained from FPN will finally build a tree, which is named as Sprouting tree. Conclusions: The methodology proposed in this paper is absolutely new to detecting the stress. The future of this work is to observe the accuracy of the proposed algorithm by implementing it with real data, which is under process.

Galilean relativity and the path integral formalism in quantum mechanics

Closed systems in Newtonian mechanics obey the principle of Galilean relativity. However, the usual Lagrangian for Newtonian mechanics, formed from the difference of kinetic and potential energies, is not invariant under the full group of Galilean transformations. In quantum mechanics, Galilean boosts require a non-trivial transformation rule for the wave function and a concomitant “projective representation” of the Galilean symmetry group. Using Feynman's path integral formalism, this latter result can be shown to be equivalent to the non-invariance of the Lagrangian. Thus, using path integral methods, the representation of certain symmetry groups in quantum mechanics can be simply understood in terms of the transformation properties of the classical Lagrangian and conversely. The main results reported here should be accessible to students and teachers of physics—particularly classical mechanics, quantum mechanics, and mathematical physics—at the advanced undergraduate and beginning graduate levels, providing a useful exposition for those wanting to explore topics such as the path integral formalism for quantum mechanics, relativity principles, Lagrangian mechanics, and representations of symmetries in classical and quantum mechanics.

Optical variability in quasars: scalings with black hole mass and Eddington ratio depend on the observed time-scales

ABSTRACT Quasars emission is highly variable, and this variability gives us clues to understand the accretion process onto supermassive black holes. We can expect variability properties to correlate with the main physical properties of the accreting black hole, i.e. its mass and accretion rate. It has been established that the relative amplitude of variability anticorrelates with the accretion rate. The dependence of the variance on black hole mass has remained elusive, and contradicting results, including positive, negative, or no correlation, have been reported. In this work, we show that the key to these contradictions lies in the times-cales of variability studied (e.g. the length of the light curves available). By isolating the variance on different time-scales in well-defined mass and accretion rate bins we show that there is indeed a negative correlation between black hole mass and variance and that this anticorrelation is stronger for shorter time-scale fluctuations. The behaviour can be explained in terms of a universal variability power spectrum for all quasars, resembling a broken power law where the variance is constant at low temporal frequencies and then drops continuously for frequencies higher than a characteristic (break) frequency fb, where fb correlates with the black hole mass. Furthermore, to explain all the variance results presented here, not only the normalization of this power spectrum must anticorrelate with the accretion rate, but also the shape of the power spectra at short time-scales must depend on this parameter as well.

The photography method: Solving pentagon equation

In this paper, we consider two applications of the pentagon equation. The first deals with actions of flips on edges of triangulations labeled by rational functions in some variables. The second can be formulated as a system of linear equations with variables corresponding to triangles of a triangulation. The general method says that if there is some general data (say, edge lengths or areas) associated with states (say, triangulations) and a general data transformation rule (say, how lengths or areas are changed under flips) then after returning to the initial state we recover the initial data.

Formal Specification, Verification and Repair of Contiki’s Scheduler

This article presents an approach for model extraction, formal specification, verification, and repair of the scheduler of Contiki, which is an event-driven lightweight operating system for the Internet of Things (IoT). We first derive a state machine–based abstraction of the scheduler’s modes of operation along with the control flow abstractions of the scheduler’s most important functions. We then use a set of transformation rules to formally specify the scheduler and all its internal functions in Promela. Additional contributions with respect to the conference version of this article include (1) modeling nested function calls in the Promela model of the scheduler using a novel technique amenable to model checking in SPIN; (2) modeling protothreads in Promela; (3) specifying and formally verifying 12 critical requirements of the scheduler; (4) detecting new design flaws in Contiki’s scheduler for the first time (to the best of our knowledge); (5) repairing the model and the source code of Contiki’s scheduler towards fixing the flaws detected through verification, as well as regression verification of the entire model of the scheduler; and (6) experimentally analyzing the time and space costs of verification before and after repair. The proposed formal model of Contiki’s scheduler along with novel modeling techniques enhance our knowledge regarding the most critical components of Contiki and provide reusable methods for formal specification and verification of other event-driven operating systems used in Cyber Physical Systems (CPSs) and the IoT.

Control of magnetic dissipation and radiation on an unsteady stagnation point nanofluid flow: A numerical approach

This study investigates two-dimensional time-dependent stagnation point nanofluid flow over a permeable stretching or sinking sheet. The electrically conducting fluid allows for the interaction of a transverse magnetic field along with magnetic dissipation and thermal radiation to enrich the flow phenomena. The use of nanofluids is becoming increasingly important in a variety of industrial applications, as well as in engineering and biomedicine. The process of peristaltic pumping, the flow of blood in the artery, the drug delivery process, and besides that, the cooling of electronic devices for the better shape of the product at the final stage of production, the use of nanofluid, are all important. The transformed dimensionless governing equations are obtained by the implementation of various transformation rules, and the model is designed by using different thermophysical properties such as viscosity, conductivity, etc. Finally, the numerical technique RK-fourth-order method is deployed to solve the set of equations and the iteration process is continued up to the desired accuracy of 10[Formula: see text]. The validation of the current result is shown with the earlier investigation in particular cases, and further, the behavior of the physical parameters is presented through graphs. It is observed that the particle concentration has a greater impact in enhancing the velocity distribution for the variation of suction/injection. The behavior of the magnetic parameter vis-à-vis the unsteadiness parameter and the thermal buoyancy presents their greater contribution in enhancing the magnitude of nanofluid velocity.

Numerics of Bianchi type II and type IX spacetimes in effective loop quantum cosmology

We numerically determine the effective loop quantum cosmology (LQC) dynamics for the vacuum Bianchi type II and type IX spacetimes, in particular studying how the Kasner exponents evolve across the LQC bounce. We find that when the spatial curvature is negligible at the bounce then the Kasner exponents transform according to the same simple equation as for a Bianchi type I spacetime in effective LQC, while there are departures from this transformation rule in cases where the spatial curvature is significant during the bounce. We also use high-precision numerics to compute the evolution of a Bianchi type IX spacetime through multiple bounces and recollapses, and find indications of chaotic behavior. Interestingly, the numerics indicate that it is during the classical recollapse, and not the LQC bounce, that nearby solutions diverge most strongly.

Effects of Brownian and thermophoresis on the nanofluid flow with zero nanoparticle mass flux and convective conditions through non-linearly expanding Riga plate

The present flow phenomena characterize the behavior of the Brownian motion and thermophoresis considering the Buongiorno model nanofluid through a non-linearly expanding Riga plate. The conjunction of thermal radiation with zero nanoparticle mass flux and convective boundary conditions enriches the thermal properties of the nanofluid. With the recent need in various industrial applications, the biomedical sector, for the design and development of the production process of various equipment, the role of nanofluid is vital. Further, the suitable variables leading to transformation rules are useful to get rid of the dimensional form of the governing equations. Traditional numerical technique with the help of shooting-based Runge–Kutta fourth-order technique is adopted for the solution of a transformed set of equations. The physical behavior of the characterizing components is presented and described briefly. Further, the important outcomes are the use of Hartmann number that overshoots the velocity profile, whereas the heat transfer retards significantly and enhanced thermophoresis attenuates the heat transfer rate.

Reusability of Legacy Software Using Microservices: An Online Exam System Example

A new design approach called microservices-based architecture is quickly emerging as one of the most efficient ways to re-architect aging enterprise systems and reengineer them into new modern systems . Microservice architecture is essential for creating high-quality, scalable, high-performance, and easy-to-maintain software. The newest method of creating new applications or reorganizing existing systems is the microservice-based architecture. It is thought to be more efficient in a number of areas than the more traditional service-oriented design, including: such as maintainability, dependability, scalability, and agility. Software Engineering developed an architecture with independent and autonomous components known as the microservice architecture in response to the requirement to enhance and evolve software architecture design. Online exams are crucial components of education. It minimizes the vast amount of material resources and is both quick and effective. However, monolithic design, which was used to create online exam systems, has more issues and is incompatible with cloud computing, distribution, or new technologies. This paper presents on evolving and reusability a legacy enterprise system (Online Exam) using a microservice architecture. the study's contributions To update a legacy enterprise system, feature-driven microservice-specific transformation rules are adopted. Performance, maintainability, scalability, and testability are prioritized when comparing a historical monolithic architecture to a microservice architecture.

Comparation Review between of Titania (TiO<sub>2</sub>) Synthesis Using CTAC and Fe-TiO<sub>2</sub> Synthesis Using Pluronic P123 as Surfactant

This study reviewed the synthesis of Titania with different shapes in the presence of cetyltrimethylammonium chloride (CTAC) as the famous stabilizer for directly altering the morphology and dimensions. These CTAC stabilizers usually provide the synthesis of Titania with a narrow size distribution and mostly single-crystalline structures in high yields. Many papers on the synthesis of Titania are available. However, only a few articles focus on the synthesis of Titania using CTAC as the stabilizer. The general rule for the shape transformation of Titania by CTAC stabilizer can be easily summarized based on the literature during the last ten year from https://www.sciencedirect.com/ as the data source.

Analysis of the main provisions of the theory of parallel-hierarchical transformations

The article presents an analysis of the main principles of parallel-hierarchical transformations theory. The continuous movement of society towards the automation of everyday life requires the creation of fundamentally new software and hardware solutions. Considering the current physical limitations of integrated circuits, it is evident that improving software processing is the way to go. The main problem lies in the increasing complexity of architecture and supporting such code. The ideas of parallel-hierarchical networks allow for a significant increase in processing speed through process parallelization while maintaining the relative simplicity of the software solution's architecture. The proposed structure of the parallel-hierarchical network allows for modelling the operation principle of a distributed neural network and forms a deterministic network using spatial-temporal division. The general rules of direct and inverse parallel-hierarchical transformation and their application to image recognition tasks are discussed. A block diagram of the algorithm for the basic model of nonlinear direct network transformation is shown. A mathematical model of direct parallel-hierarchical transformation is presented using an example. Compared to known numerical transformation methods involving simple operations like addition, the model enables complex functional signal processing in real-time scale, as well as unambiguity and reversibility with good convergence of the computational process.

Yeast cell detection using fuzzy automatic contrast enhancement (FACE) and you only look once (YOLO)

In contemporary biomedical research, the accurate automatic detection of cells within intricate microscopic imagery stands as a cornerstone for scientific advancement. Leveraging state-of-the-art deep learning techniques, this study introduces a novel amalgamation of Fuzzy Automatic Contrast Enhancement (FACE) and the You Only Look Once (YOLO) framework to address this critical challenge of automatic cell detection. Yeast cells, representing a vital component of the fungi family, hold profound significance in elucidating the intricacies of eukaryotic cells and human biology. The proposed methodology introduces a paradigm shift in cell detection by optimizing image contrast through optimal fuzzy clustering within the FACE approach. This advancement mitigates the shortcomings of conventional contrast enhancement techniques, minimizing artifacts and suboptimal outcomes. Further enhancing contrast, a universal contrast enhancement variable is ingeniously introduced, enriching image clarity with automatic precision. Experimental validation encompasses a diverse range of yeast cell images subjected to rigorous quantitative assessment via Root-Mean-Square Contrast and Root-Mean-Square Deviation (RMSD). Comparative analyses against conventional enhancement methods showcase the superior performance of the FACE-enhanced images. Notably, the integration of the innovative You Only Look Once (YOLOv5) facilitates automatic cell detection within a finely partitioned grid system. This leads to the development of two models—one operating on pristine raw images, the other harnessing the enriched landscape of FACE-enhanced imagery. Strikingly, the FACE enhancement achieves exceptional accuracy in automatic yeast cell detection by YOLOv5 across both raw and enhanced images. Comprehensive performance evaluations encompassing tenfold accuracy assessments and confidence scoring substantiate the robustness of the FACE-YOLO model. Notably, the integration of FACE-enhanced images serves as a catalyst, significantly elevating the performance of YOLOv5 detection. Complementing these efforts, OpenCV lends computational acumen to delineate precise yeast cell contours and coordinates, augmenting the precision of cell detection.

A Modeling and Verification Method of Cyber-Physical Systems Based on AADL and Process Algebra

Cyber-Physical Systems (CPS) are the next generation of intelligent systems that integrate information control devices with physical resources. With increasingly close connections between CPS components and frequent interactions, potential defects grow exponentially, rendering the operating environment of CPS unreliable. Therefore, research on methods and theories to ensure the correctness, safety and reliability of CPS is not only an important research topic but also an inevitable challenge. In this paper, we propose a CPS modeling and verification method based on Architecture Analysis & Design Language (AADL) and process algebra to address this challenge. Due to the continuous, time-constrained, stochastic, uncertain and concurrent characteristics of CPS, this paper considers both flexibility and rigor in the modeling process. We first extend the ability of AADL to describe the multiple characteristics of CPS and propose Hybrid Probability-AADL (HP-AADL). Second, this paper introduces conditional execution, conditional interruption and probability operators into Temporal Calculus of Communication Systems (TCCS) and designs a new formal modeling language Hybrid Probability-Temporal Calculus of Communication Systems (HP-TCCS). However, HP-AADL is a semi-formal modeling language that cannot be directly used for formal verification, it cannot strictly guarantee the quality of the established CPS models, including its functional correctness and safety. Therefore, this paper proposes transformation rules from HP-AADL to HP-TCCS, which enables model checking of CPS models described in HP-AADL within HP-TCCS. Additionally, this paper designs a new formal specification language HPAT-Spatial Temporal Logic (HPAT-STL) based on Probabilistic Computation Tree Logic (PCTL) and Spatial Logic, which characterizes the temporal, probabilistic and spatial properties of CPS model. To achieve formal verification of HP-TCCS model and HPAT-STL formulas, this paper proposes a model checking algorithm HPAT-Model Checking Algorithm (HPAT-MCA). Finally, we discuss a typical CPS example to demonstrate the effectiveness of our proposed method in ensuring correct, safe and reliable CPS.

A Study of Essential Computational Software in Medicinal Chemistry

Today, it is common practice to employ computational software tools for investigating the structure, dynamics, surface characteristics, and thermodynamics of inorganic, biological, and polymeric systems. Computational software tools are a vital part of the guide for drug discovery. It is frequently employed in approaches for rational drug design and structure-based drug design. The process of drug design and discovery is essential in the invention of a new chemical entity. For this process, plenty of computational tools are available globally, Those computational software tools are fast, free, open online excess paid. Pharmaceutical software decreases human efforts, error, and time utilization in a particular task without compromising the quality of work with great accuracy and efficiency. This software is utilized by various institutes globally related to science and medicine. A computer program that transforms an input structure according toa library of medicinal chemical transformation rules before allowing evaluation of the output structures. High throughput screening is now widely accepted as a viable option that CADD supports. The development of top-notch datasets and design libraries that may be optimized for molecular diversity or similarity has resulted from the quest for novel molecular entities. On the other hand, breakthroughs in computing infrastructure and molecular docking methods are allowing screening throughput to increase quickly.

The Oblate Lambert Problem: Geometric Formulation and Solution of an Unperturbed, Generalized Lambert Problem Governed by Vinti’s Potential

Numerous methods exist for solving the Lambert problem, the two-point boundary value problem (BVP) governed by two-body dynamics. Many applications would benefit from a solution to a perturbed Lambert problem; a few studies have attempted to solve one. Establishing a larger pool of alternative solution methods gives practitioners greater latitude in choosing the solution that best suits their needs. To that end, a novel Lambert-type BVP is constructed in this work that includes oblateness by way of Vinti’s potential, rendering the problem mathematically unperturbed. This BVP is first defined and then converted to a system of equations that is amenable to an iterative solution. The formulation, which is valid for both the zero- and multiple-revolution problems, couples oblate spheroidal (OS) universal variables and OS equinoctial orbital elements together to sow robustness across all orbital regimes, only excepting orbits that are sufficiently rectilinear. For the first time, the solution space is broadly explored, exposing multiple new insights of significant practical use. Initial guess and root-solve techniques are offered to solve the system of equations. When assessed at Earth for robustness, accuracy, and computational efficiency, the zero-revolution algorithm excels across all three performance metrics, with runtimes averaging only about 15 times slower than a typical two-body Lambert solver. The multiple-revolution algorithm, while not yet evaluated as extensively, also exhibits high levels of performance, the formulation generally characterizing the existence of solutions around oblate bodies more accurately than its Keplerian counterpart.