Identification of 6-methyladenosine sites using novel feature encoding methods and ensemble models.

N6-methyladenosine (6 mA) is the most common internal modification in eukaryotic mRNA. Mass spectrometry and site-directed mutagenesis, two of the most common conventional approaches, have been shown to be laborious and challenging. In recent years, there has been a rising interest in analyzing RNA sequences to systematically investigate mutated locations. Using novel methods for feature development, the current work aimed to identify 6 mA locations in RNA sequences. Following the generation of these novel features, they were used to train an ensemble of models using methods such as stacking, boosting, and bagging. The trained ensemble models were assessed using an independent test set and k-fold cross validation. When compared to baseline predictors, the suggested model performed better and showed improved ratings across the board for key measures of accuracy.

A novel probabilistic q-rung orthopair linguistic neutrosophic information-based method for rating nanoparticles in various sectors.

The idea of probabilistic q-rung orthopair linguistic neutrosophic (P-QROLN) is one of the very few reliable tools in computational intelligence. This paper explores a significant breakthrough in nanotechnology, highlighting the introduction of nanoparticles with unique properties and applications that have transformed various industries. However, the complex nature of nanomaterials makes it challenging to select the most suitable nanoparticles for specific industrial needs. In this context, this research facilitate the evaluation of different nanoparticles in industrial applications. The proposed framework harnesses the power of neutrosophic logic to handle uncertainties and imprecise information inherent in nanoparticle selection. By integrating P-QROLN with AO, a comprehensive and flexible methodology is developed for assessing and ranking nanoparticles according to their suitability for specific industrial purposes. This research contributes to the advancement of nanoparticle selection techniques, offering industries a valuable tool for enhancing their product development processes and optimizing performance while minimizing risks. The effectiveness of the proposed framework are demonstrated through a real-world case study, highlighting its potential to revolutionize nanoparticle selection in HVAC (Heating, Ventilation, and Air Conditioning) industry. Finally, this study is crucial to enhance nanoparticle selection in industries, offering a sophisticated framework probabilistic q-rung orthopair linguistic neutrosophic quantification with an aggregation operator to meet the increasing demand for precise and informed decision-making.

m1A-Ensem: accurate identification of 1-methyladenosine sites through ensemble models.

BACKGROUND: 1-methyladenosine (m1A) is a variant of methyladenosine that holds a methyl substituent in the 1st position having a prominent role in RNA stability and human metabolites. OBJECTIVE: Traditional approaches, such as mass spectrometry and site-directed mutagenesis, proved to be time-consuming and complicated. METHODOLOGY: The present research focused on the identification of m1A sites within RNA sequences using novel feature development mechanisms. The obtained features were used to train the ensemble models, including blending, boosting, and bagging. Independent testing and k-fold cross validation were then performed on the trained ensemble models. RESULTS: The proposed model outperformed the preexisting predictors and revealed optimized scores based on major accuracy metrics. CONCLUSION: For research purpose, a user-friendly webserver of the proposed model can be accessed through https://taseersuleman-m1a-ensem1.streamlit.app/ .

Electro osmotically interactive biological study of thermally stratified micropolar nanofluid flow for Copper and Silver nanoparticles in a microchannel.

A novel mathematical analysis is established that summits the key features of peristaltic propulsion for a non-Newtonian micropolar fluid with the electroosmosis and heat transfer enhancement using nanoparticles. In such physiological models, the channel have a symmetric configuration in accordance with the biological problem. Being mindful of this fact, we have disclosed an integrated analysis on symmetric channel that incorporates major physiological applications. The creeping flow inference is reviewed to model this realistic problem. Flow equations are model using cartesian coordinates and simplified using long wave length and low Reynolds number approximation. Nonlinear linear couple equations are solving numerically. We have studied the variation in the properties of nanofluid developed by two different types of nanoparticles (i.e. Cu and Ag nanoparticles). Graphical illustrations are unveiled to highlight the physical aspects of nanoparticles and flow parameters. The exploration demonstrates that the micro-rotation of the nano-liquid elements enhances the thermal conductivity of the fluid movement. The effect of micropolar fluid parameters on mean flow and pressure variables is also presented.

Microbic flow analysis of nano fluid with chemical reaction in microchannel with flexural walls under the effects of thermophoretic diffusion.

The current investigation examines the peristaltic flow, in curved conduit, having complaint boundaries for nanofluid. The effects of curvature are taken into account when developing the governing equations for the nano fluid model for curved channels. Nonlinear & coupled differential equations are then simplified by incorporating the long wavelength assumption along with smaller Reynolds number. The homotopy perturbation approach is used to analytically solve the reduced coupled differential equations. The entropy generation can be estimated through examining the contributions of heat and fluid viscosities. The results of velocity, temperature, concentration, entropy number, and stream functions have been plotted graphically in order to discuss the physical attributes of the essential quantities. Increase in fluid velocity within the curved conduit is noticed for higher values of thermophoresis parameter and Brownian motion parameter further entropy generation number is boosted by increasing values of Grashof number.

Biological structural study of emerging shaped nanoparticles for the blood flow in diverging tapered stenosed arteries to see their application in drug delivery.

The magnetic force effects and differently shaped nano-particles in diverging tapering arteries having stenoses are being studied in current research via blood flow model. There hasn't been any research done on using metallic nanoparticles of different shapes with water as the base fluid. A radially symmetric but axially non-symmetric stenosis is used to depict the blood flow. Another significant aspect of our research is the study of symmetrical distribution of wall shearing stresses in connection with resistive impedance, as well as the rise of these quantities with the progression of stenosis. Shaping nanoparticles in accordance with the understanding of blood flow in arteries offers numerous possibilities for improving drug delivery, targeted therapies, and diagnostic imaging in the context of cardiovascular and other vascular-related diseases. Exact solutions for different flow quantities namely velocity, temperature, resistance impedance, boundary shear stress, and shearing stress at the stenosis throat, have been assessed. For various parameters of relevance for Cu-water, the graphical results of several types of tapered arteries (i.e. diverging tapering) have been explored.

Thermal characteristics of magnetized hybrid Casson nanofluid flow in a converging-diverging channel with radiative heat transfer: a computational analysis.

In the present article we consider the physical model of two-dimensional Casson hybrid nanofluids flow, which is magnetized and thermally radiative, laminar, incompressible inside the channel. Flow equations have been modelled for two dimensional axial and radial velocity components [Formula: see text] along [Formula: see text] and [Formula: see text] along the [Formula: see text]. There exists temperature [Formula: see text] which is constant for upper and lower walls. The Casson nanofluids model with nano type particles includes heat transfer effect between two stretched and shrinking walls of the channel was constructed. The continuity, momentum and energy equations are modelled in cartesian coordinates system. The finite element technique is used to evaluate numerical solutions for velocity, temperature, Skin friction and Nusselt number. It is evident that the hybrid Casson nanofluids exhibit opposite behaviors in the stretching and shrinking cases near the upper and lower walls of the channel. It is also observed that in the stretching case, increasing the values of the Casson parameter leads to a rise in both shear stress and heat transfer rate for both plates of the channel. However, the results contradict this trend in the shrinking case. Understanding the thermal characteristics of magnetized hybrid fluids can be applied to the design of advanced cooling systems in engineering applications, biomedical fluid dynamic, in energy system this study can be applied to improve the efficiency of energy systems where fluid flow and heat transfer play crucial roles. Further use of nanofluids suggests a connection to nanotechnology, and the study may have implications for the development of advanced nanomaterial-based heat transfer fluids.

Melting heat transfer analysis in magnetized bioconvection flow of sutterby nanoliquid conveying gyrotactic microorganisms.

In biotechnology and biosensors bioconvection along with microorganisms play a important role. This article communicates a theoretic numerical analysis concerning the bioconvective Sutterby nanofluid flow over a stretchable wedge surface. Bioconvection is a remarkable occurrence of undercurrents fluid that is produced owing to the turning of microbes. It is considered for hydrodynamics unsteadiness and forms classified in interruption of inclined swimming microbes. Bioconvection is perceived practically in many uses for example pharmaceutical products, bio sensing applications, biomedical, bio-micro systems, biotechnology advancements and refining of mathematical models. Additionally, unsteady parameter influences are taken into account. Furthermore, no mass flux as well as heat sink/source consequences are measured in existing analysis. The similarity transformation are established for the non-linear PDEs of microorganism's field, nanofluid concentration, energy, momentum and mass for bioconvection flow of Sutterby nanofluid. Then, altered non-linear ODEs are resolved by utilizing the bvp4c technique. Moreover, nanofluids are declining in thermal and concentration fields and the greater number of Peclet number declines the field of microorganisms. Acquired numerical data displays that temperature field of nanofluid increases for more thermophoretic and unsteady parameters.

Entropy generation in a ciliary flow of an Eyring-Powell ternary hybrid nanofluid through a channel with electroosmosis and mixed convection.

Drug delivery systems, where the nanofluid flow with electroosmosis and mixed convection can help in efficient and targeted drug delivery to specific cells or organs, could benefit from understanding the behavior of nanofluids in biological systems. In current work, authors have studied the theoretical model of two-dimensional ciliary flow of blood-based (Eyring-Powell) nanofluid model with the insertion of ternary hybrid nanoparticles along with the effects of electroosmosis, magnetohydrodynamics, thermal radiations, and mixed convection. Moreover, the features of entropy generation are also taken into consideration. The system is modeled in a wave frame with the approximations of large wave number and neglecting turbulence effects. The problem is solved numerically by using the shooting method with the assistance of computational software "Mathematica" for solving the governing equation. According to the temperature curves, the temperature will increase as the Hartman number, fluid factor, ohmic heating, and cilia length increase. It is also disclosed that ternary hybrid nanoparticles result in a change in flow rate when other problem parameters are varied, and the same is true for temperature graphs. Engineers and scientists can make better use of nanofluid-based cooling systems in electronics, automobiles, and industrial processes with the aid of the study's findings.

Interaction of gyrotactic moment of microorganisms and nanoparticles for magnetized and chemically reactive shear-thinning fluid with stratification phenomenon.

Nanotechnology has gained substantial attention on account of its vast applications in food manufacturing, heat exchanges, electronic cooling systems, medical treatment, coolant processes, energy production, biotechnology, transportation, biochemistry, nuclear reactors, and metrology. Currently, the phenomenon of bioconvection using nanomaterials has found wide industrial and technical implementations. Contemporary nanofluids are a dynamic source for illuminating heat transport systems related to engineering as well as industrial phenomena. Bioconvection has numerous applications in bio-micro-systems, owing to the augmentation in mass renovation besides collaborating, which are vital complications in diverse micro-systems. This study intended to model and examine an incompressible, unsteady 3D Casson fluid nanofluid with bioconvection on a stretching surface. A model by means of these characteristics is beneficial in applications, such as in nuclear reactors, coolants in automobiles, metallurgical procedures, energy construction, micro-manufacturing, industrial engineering, and geophysical fluid mechanics along with dynamics. The performance of the Brownian motion along with thermophoresis diffusion is assumed through an extraordinary effect of thermal radiation in the temperature equation of the fluid movement. This model was created by using PDE, which was then converted into an ODE system. The somatic behavior of substantial parameters was investigated graphically. Similarly, tables were interpreted to display the effect of the control of physical quantities on the local Nusselt number, local Sherwood number, and motile density. Consequently, it was determined that the temperature of Casson fluid grew exponentially with higher estimates of the magnetic parameter and the thermal Biot number. At the same time, we detected that augmented estimation of the Lewis number decreases the Casson fluid concentration. For growing values of the parameters, Biot number and the stretching parameter, there is a direct reaction for the microorganism profile.

Modulated complexed stenosed region consequences under the electroosmotic stimulation.

The present study analyzes the theoretical consequences of slip effects in a complex stenosed region. The flow of blood in a stenosed region is incorporated with hybrid nanofluid features which are being prepared with copper and copper oxide nanoparticles. The flow is also intensified by applying an electric field in the axial direction. The governing equations for the proposed paradigm are solved and the corresponding closed-form solutions are obtained for the cases of mild stenosis. Parameters such as Electro-osmotic, velocity slip and Helmholtz-Smoluchowski are specially focused in this study. The heat transfer, hemodynamic velocity, wall shear stress and resistance impedance for the flow are precisely determined. The various parameters that influence the physical characteristics of flow are plotted, and their effects are discussed in detail. The present model has the potential application in medical pumps for drug delivery systems.

Thermal performance of Fe3O4, SWCNT, MWCNT and H2O based on magnetohydrodynamic nanofluid flow across a wedge with significant impacts of Soret and Dufour.

The Soret and Dufour effects have significant importance in several practical scenarios, especially in the domain of fluidic mass and temperature transfer. Nanofluidics, biological systems, and combustion processes are all areas where these consequences are crucial. Because of its distinct geometry, a wedge-shaped structure has aerodynamics, production, and engineering applications. Wedge shapes are used in aerodynamics for analyzing and improving airflow across various objects. Nanofluids increase thermal conductivity over traditional fluids making them ideal for cooling high-power electronics, boosting temperature transfer efficiencies, and boosting the solar energy system output. This work is of critical importance since it examines the consequences of a heat source/sink, the Soret impact and the Dufour impact, on the movement of a ternary nanofluid over a wedge. This work uses appropriate similarity constraints to reduce the complexity of the underlying governing equations, allowing for fast computational solutions with the Runge-Kutta-Fehlberg 4-5th order method (RKF-45). Analysis of these phenomena helps determine their possible real-world applications across various engineering fields, by presenting numerical results through plots. The results reveal that adjusting the moving wedge factor lessens the temperature profile, improving the magnetic constraint increases the velocity, and modifying the heat source/sink, Dufour, and Soret factors increases the temperature and concentration profiles. Dufour and heat source/sink constraints speed-up the heat transmission rate. In all cases, ternary nano liquids show significant performance over hybrid nano liquids.

Physical aspects of electro osmotically interactive Cilia propulsion on symmetric plus asymmetric conduit flow of couple stress fluid with thermal radiation and heat transfer.

A novel mathematical analysis is established that summits the key features of Cilia propulsion for a non-Newtonian Couple Stress fluid with the electroosmosis and heat transfer. In such physiological models, the conduit may have a symmetric or asymmetric configuration in accordance with the biological problem. Being mindful of this fact, we have disclosed an integrated analysis on symmetric in addition to asymmetric conduits that incorporates major physiological applications. The creeping flow inference is reviewed to model this realistic problem and exact solutions are computed for both the conduit cases. Graphical illustrations are unveiled to highlight the physical aspects of cilia propulsion on symmetric in addition to asymmetric conduit and an inclusive comparison study is conveyed. The flow profile attains higher values for an asymmetric conduit in relation to the symmetric. Likewise, the pressure rise and pressure gradient also score high for asymmetric conduit in relation to the symmetric conduit. A visual representation of flow inside symmetric as well as asymmetric conduit is provided by streamline graphs and temperature profile as well.

Entropy generation optimization of cilia regulated MHD ternary hybrid Jeffery nanofluid with Arrhenius activation energy and induced magnetic field.

This study deals with the entropy generation analysis of synthetic cilia using a ternary hybrid nanofluid (Al-Cu-Fe2O3/Blood) flow through an inclined channel. The objective of the current study is to investigate the effects of entropy generation optimization, heat, and mass transfer on ternary hybrid nanofluid passing through an inclined channel in the proximity of the induced magnetic field. The novelty of the current study is present in studying the combined effect of viscous dissipation, thermophoresis, Brownian motion, exponential heat sink/source, porous medium, endothermic-exothermic chemical reactions, and activation energy in the proximity of induced magnetic field is examined. The governing partial differential equations (PDEs) are transformed into the ordinary differential equations (ODEs) using appropriate transformations. Applying the low Reynolds number and the long-wavelength approximation, resultant ODEs are numerically solved using shooting technique via BVP5C in MATLAB. The velocity, temperature, concentration, and induced magnetism profiles are visually discussed and graphically analyzed for various fluid flow parameters. Graphical analysis of physical interest quantities like mass transfer rate, heat transfer rate, entropy generation optimization, and skin friction coefficient are also graphically discussed. The entropy generation improves for enhancing values of Reynolds number, solutal Grashof number, heat sink/source parameter, Brinkman number, magnetic Prandtl number, and endothermic-exothermic reaction parameter while the reverse effect is noticed for chemical reaction and induced magnetic field parameter. The findings of this study can be applied to enhance heat transfer efficiency in biomedical devices, optimizing cooling systems, designing efficient energy conversion processes, and spanning from renewable energy technologies to aerospace propulsion systems.

Heat and mass transport in an electrically conducting nanofluid flow over two-dimensional geometries.

Engineering equipment in medicine, chemical and power engineering, electronics, and other human endeavours use nanofluids. The ability to improve mass and heat transport because of the low concentration of nanoparticles is the primary driver behind the vast array of nanofluid applications. Thus, the famous problems of viscous, incompressible, Newtonian, and 2-D laminar flow are revisited to investigate the mass and heat transmission rates for water-based carbon nanotubes (CNTs) with variable magnetic fields and external pressure gradients. Flow cases considered with varying pressure gradients are the flows upon a flat plate, flow in a planar diverging and converging channel, flow over a wedge, and plane stagnation flows, which are investigated. The impressions of thermophoresis and Brownian motion parameters are examined through the Buongiorno model. Using the Görtler transformation, the leading boundary layer (BL) equations are converted into dimensionless forms of ordinary differential equations (ODEs). Runge-Kutta Fehlberg Method (RKF45) is operated to tackle the ensuing ODEs to find the mass, heat, and skin friction rates. It has been found that the rates of shear stress, mass, and heat transport slow down with an escalating magnetic field. Although mass transport rates are decreased, shear stress and heat transport (HT) rates escalate due to the solid volume portion of carbon nanotubes. Furthermore, the pressure gradient parameter facilitates faster heat and shear stress transmission rates.

PseU-Pred: An ensemble model for accurate identification of pseudouridine sites.

Pseudouridine (ψ) is reported to occur frequently in all types of RNA. This uridine modification has been shown to be essential for processes such as RNA stability and stress response. Also, it is linked to a few human diseases, such as prostate cancer, anemia, etc. A few laboratory techniques, such as Pseudo-seq and N3-CMC-enriched Pseudouridine sequencing (CeU-Seq) are used for detecting ψ sites. However, these are laborious and drawn-out methods. The convenience of sequencing data has enabled the development of computationally intelligent models for improving ψ site identification methods. The proposed work provides a prediction model for the identification of ψ sites through popular ensemble methods such as stacking, bagging, and boosting. Features were obtained through a novel feature extraction mechanism with the assimilation of statistical moments, which were used to train ensemble models. The cross-validation test and independent set test were used to evaluate the precision of the trained models. The proposed model outperformed the preexisting predictors and revealed 87% accuracy, 0.90 specificity, 0.85 sensitivity, and a 0.75 Matthews correlation coefficient. A web server has been built and is available publicly for the researchers at https://taseersuleman-y-test-pseu-pred-c2wmtj.streamlit.app/.

Numerical investigation of MHD flow of hyperbolic tangent nanofluid over a non-linear stretching sheet.

This research investigates two-dimensional MHD incompressible boundary layer Hyperbolic Tangent nanofluid flow across a non-linear stretching plate. Similarity transformations are employed to convert the governing non-linear partial differential equations (PDEs) into coupled non-linear ordinary differential equations (ODEs). The MATLAB built-in routine bvp4c has been used for finding the numerical solutions of the dimensionless velocity, temperature, and concentration profiles. The current findings are validated with already published results. The influence of some important parameters on the velocity, temperature, and concentration profiles are displayed through graphs and tables. It is observed that for increasing values of magnetic parameter M and hyperbolic Tangent parameter We, the boundary layer thickness of the velocity profile decreases while it increases for the temperature profile.

Significance of melting heat in bioconvection flow of micropolar nanofluid over an oscillating surface.

Pharmaceuticals, biological polymer synthesis, eco-friendly uses, sustainable fuel cell innovations, microbial-enhanced extraction of petroleum, biological sensors, biological technology, and continual mathematical modeling refinement are all examples of how bioconvection is applied. This study examines the bio convectional viscoelastic-micropolar nano liquid flow with non-uniform heat sink/source, motile microorganisms that move across a stretched sheet. Thermal radiation and thermal conductivity are also explored. Brownian and thermophoresis diffusion effects are taken into account. The system of a higher partial differential equation is transformed to ODEs by using the appropriate similarity functions. Such reported equations are implemented with the computational tool MATLAB shooting approach using a bvp4c solver. The variations of numerous flow parameters comprise velocity, temperature, concentration, and motile microorganism profile. Various important, interesting transport numbers are numerically and graphically demonstrated with physical justifications. The bouncy ratio parameter reduces the fluid's velocity profile whereas the material parameter increases it. For increased melting parameters, the micro rotation profile improves, but it deteriorated. For the Prandtl number and temperature ratio parameters, the temperature profile is negative. The melting parameter influences the concentration profile. The microorganism's profile is decreased bioconvective Lewis numbers and is higher for the magnetic parameter. The current model has many features in the manufacturing industries, engineering works, physics, and applied mathematics.

Entropy generation and flow characteristics of Powell Eyring fluid under effects of time sale and viscosities parameters.

Shear thinning fluids are widely used in the food and polymer industries due to their unique flow characteristics. The flow behavior of these fluids has been commonly studied using the Powell Eyring model under a small shear rate assumption. However, this assumption is not always valid. In this study, we explore the transport characteristics of a Powell Eyring fluid over a variable thicker sheet, not only at small shear rates but also at medium and high shear rates. Furthermore, we calculate the rate of entropy generation based on the assumptions. Generalized Powell-Eyring model of viscosity is used for the fluid, representing the re-arrangements of molecules in the forward and backward directions through the theory of potential energy. The model concludes the sensitivity of the viscosity from zero to infinite shear rate along time sale and exponent parameters. The model is used in the transport phenomena equations. The solution of the equation is obtained by using the numerical method and used to calculate the rate of entropy generation. The results are presented in the form of velocity and temperature profiles, the average rate of entropy generation, skin friction coefficient and Nusselt number under the influence of various viscosity parameters. It is found that velocity and temperature profiles are decreased and increased respectively against the time scale parameter.

iDHU-Ensem: Identification of dihydrouridine sites through ensemble learning models.

Background: Dihydrouridine (D) is one of the most significant uridine modifications that have a prominent occurrence in eukaryotes. The folding and conformational flexibility of transfer RNA (tRNA) can be attained through this modification. Objective: The modification also triggers lung cancer in humans. The identification of D sites was carried out through conventional laboratory methods; however, those were costly and time-consuming. The readiness of RNA sequences helps in the identification of D sites through computationally intelligent models. However, the most challenging part is turning these biological sequences into distinct vectors. Methods: The current research proposed novel feature extraction mechanisms and the identification of D sites in tRNA sequences using ensemble models. The ensemble models were then subjected to evaluation using k-fold cross-validation and independent testing. Results: The results revealed that the stacking ensemble model outperformed all the ensemble models by revealing 0.98 accuracy, 0.98 specificity, 0.97 sensitivity, and 0.92 Matthews Correlation Coefficient. The proposed model, iDHU-Ensem, was also compared with pre-existing predictors using an independent test. The accuracy scores have shown that the proposed model in this research study performed better than the available predictors. Conclusion: The current research contributed towards the enhancement of D site identification capabilities through computationally intelligent methods. A web-based server, iDHU-Ensem, was also made available for the researchers at https://taseersuleman-idhu-ensem-idhu-ensem.streamlit.app/.