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.

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.

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/.

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/.

Radio Frequency Identification Temperature/CO2 Sensor Using Carbon Nanotubes.

In the world of digitization, different objects cooperate with the Internet of Things (IoT); these objects also amplify using sensing and data processing structures. Radio frequency identification (RFID) has been identified as a key enabler technology for IoT. RFID technology has been used in different conventional applications for security, goods storage, transportation and asset management. In this paper, a fully inkjet-printed chipless radio frequency identification (RFID) sensor tag is presented for the wireless identification of tagged objects. The dual polarized tag consists of two resonating structures functioning wirelessly. One resonator works for encoding purpose and other resonator is used as a CO2/temperature sensor. The sensing behavior of the tag relies on the integration of a meandered structure comprising of multi-wall carbon nanotubes (MWCNT). The MWCNT is highly sensitive to CO2 gas. The backscattered response of the square-shaped cascaded split ring resonators (SRR) is analyzed through a radar cross-section (RCS) curve. The overall tag dimension is 42.1 mm × 19.5 mm. The sensing performance of the tag is examined and optimized for two different flexible substrates, i.e., PET and Kapton®HN. The flexible tag structure has the capability to transmit 5-bit data in the frequency bands of 2.36-3.9 GHz and 2.37-3.89 GHz, for PET and Kapton®HN, respectively. The proposed chipless RFID sensor tag does not require any microchip or a power source, so it has a great potential for low-cost and automated temperature/CO2 sensing applications.

DHU-Pred: accurate prediction of dihydrouridine sites using position and composition variant features on diverse classifiers.

Background: Dihydrouridine (D) is a modified transfer RNA post-transcriptional modification (PTM) that occurs abundantly in bacteria, eukaryotes, and archaea. The D modification assists in the stability and conformational flexibility of tRNA. The D modification is also responsible for pulmonary carcinogenesis in humans. Objective: For the detection of D sites, mass spectrometry and site-directed mutagenesis have been developed. However, both are labor-intensive and time-consuming methods. The availability of sequence data has provided the opportunity to build computational models for enhancing the identification of D sites. Based on the sequence data, the DHU-Pred model was proposed in this study to find possible D sites. Methodology: The model was built by employing comprehensive machine learning and feature extraction approaches. It was then validated using in-demand evaluation metrics and rigorous experimentation and testing approaches. Results: The DHU-Pred revealed an accuracy score of 96.9%, which was considerably higher compared to the existing D site predictors. Availability and Implementation: A user-friendly web server for the proposed model was also developed and is freely available for the researchers.

A forced convection of water aluminum oxide nanofluid flow and heat transfer study for a three dimensional annular with inner rotated cylinder.

The article examines a water alumina nanofluid and heat transfer through the three-dimensional annular. The annular is constructed by the two concentric cylinders in which the inner cylinder can rotate along the tangential direction at a constant speed. A slip boundary condition will be imposed to vanish the viscous effect in the vicinity of the outer cylinder wall. Moreover, the rotating cylinder is kept at a hot temperature, and the outer one is at a cold temperature. A three-dimensional incompressible Navier Stokes and energy equations were carried in cylindrical coordinates. The simulation was observed using the emerging computational tool of COMSOL Multiphysics 5.6, which implements Least Square Galerkin's scheme of finite element method. The parametric study will be done by altering the speed of rotation of the inner cylinder from 1 to 4, volume fraction from 0.001 to 0.9, and the aspect ratio from 0.4 to 0.6 for a fixed Reynolds number of 35,000. The results will be displayed with graphs and tables for average values of the Nusselt number, the percentage change in the temperature, and the skin friction at the middle plan. It was found that the average Nusselt number at the middle of the annular increases before the volume fraction of 0.2 and then decreases for all values of the volume fraction for a fixed rotation of the inner cylinder. The average percentage change relative to the inner cylinder's hot temperature decreases with the volume fraction increase for the fixed rotation. Also, it was found that the quantity of nanoparticles in the domain is improving the average skin friction in the middle of the channel, and it can be reduced by improving the rotation of the inner cylinder by about 10-23% strictly depending upon the aspect ratio for a particular case.

m1A-pred: Prediction of Modified 1-methyladenosine Sites in RNA Sequences through Artificial Intelligence.

BACKGROUND: The process of nucleotides modification or methyl groups addition to nucleotides is known as post-transcriptional modification (PTM). 1-methyladenosine (m1A) is a type of PTM formed by adding a methyl group to the nitrogen at the 1st position of the adenosine base. Many human disorders are associated with m1A, which is widely found in ribosomal RNA and transfer RNA. OBJECTIVE: The conventional methods such as mass spectrometry and site-directed mutagenesis proved to be laborious and burdensome. Systematic identification of modified sites from RNA sequences is gaining much attention nowadays. Consequently, an extreme gradient boost predictor, m1A-Pred, is developed in this study for the prediction of modified m1A sites. METHODS: The current study involves the extraction of position and composition-based properties within nucleotide sequences. The extraction of features helps in the development of the features vector. Statistical moments were endorsed for dimensionality reduction in the obtained features. RESULTS: Through a series of experiments using different computational models and evaluation methods, it was revealed that the proposed predictor, m1A-pred, proved to be the most robust and accurate model for the identification of modified sites. AVAILABILITY AND IMPLEMENTATION: To enhance the research on m1A sites, a friendly server was also developed, which was the final phase of this research.

Mathematical modeling and thermodynamics of Prandtl-Eyring fluid with radiation effect: a numerical approach.

Main concern of current research is to develop a novel mathematical model for stagnation-point flow of magnetohydrodynamic (MHD) Prandtl-Eyring fluid over a stretchable cylinder. The thermal radiation and convective boundary condition are also incorporated. The modeled partial differential equations (PDEs) with associative boundary conditions are deduced into coupled non-linear ordinary differential equations (ODEs) by utilizing proper similarity transformations. The deduced dimensionless set of ODEs are solved numerically via shooting method. Behavior of controlling parameters on the fluid velocity, temperature fields as well as skin friction and Nusselt number are highlighted through graphs. Outcome declared that dimensionless fluid temperature boosts up for both the radiation parameter and Biot number. It is also revealed that the magnitude of both heat transfer rate and skin friction enhance for higher estimation of curvature parameter. Furthermore, comparative analysis between present and previous reports are provided for some specific cases to verify the obtained results.

A bioconvection model for viscoelastic nanofluid confined by tapered asymmetric channel: implicit finite difference simulations.

As part of the growing evolution in nanotechnology and thermal sciences, nanoparticles are considered as an alternative solution for the energy depletion due to their ultra-high thermal effectives. Nanofluids reflect inclusive and broad-spectrum significances in engineering, industrial and bio-engineering like power plants, energy source, air conditioning systems, surface coatings, evaporators, power consumptions, nano-medicine, cancer treatment, etc. The present study describes the bio-convective peristaltic flow of a third-grade nanofluid in a tapered asymmetric channel. Basic conservation laws of mass, momentum, energy, and concentration as well as the microorganism diffusion equation are utilized to model the problem. The simplified form of the modeled expressions is accounted with long wavelength assumptions. For solving the resulting coupled and nonlinear equations, a well-known numerical method implicit finite difference scheme has been utilized. The graphical results describe the velocity, temperature and concentration profiles, and the density of motile microorganisms at the nanoscale. Furthermore, microorganism concentration lines are analyzed.

Von Karman rotating nanofluid flow with modified Fourier law and variable characteristics in liquid and gas scenarios.

This investigation aims to explore the temperature-dependent variable characteristics of viscosity, and thermal conductivity with modified Fourier law in a nanofluid flow over a rotating disk. The uniqueness of the envisioned mathematical model is improved with the additional impacts of the chemical reaction, non-uniform source/sink, and convective boundaries. The salient feature of the existing problem is to discuss the whole scenario with liquid and gas thermo-physical characteristics. The graphical depiction is attained for arising pertinent parameter is attained by using Bvp4c a built-in MATLAB function. The visco-thermal conduct of the gases and liquids is examined by observing the mean flow and thermal distributions for the convectively heated disk. It is followed that liquid behaves more viscous with an increase in temperature in of the gas, but an opposing tendency can be seen for the liquid. The attained results are verified when compared with a published result.

Temperature and Concentration Stratification Effects in Mixed Convection Flow of an Oldroyd-B Fluid with Thermal Radiation and Chemical Reaction.

This research addresses the mixed convection flow of an Oldroyd-B fluid in a doubly stratified surface. Both temperature and concentration stratification effects are considered. Thermal radiation and chemical reaction effects are accounted. The governing nonlinear boundary layer equations are converted to coupled nonlinear ordinary differential equations using appropriate transformations. Resulting nonlinear systems are solved for the convergent series solutions. Graphs are plotted to examine the impacts of physical parameters on the non-dimensional temperature and concentration distributions. The local Nusselt number and the local Sherwood number are computed and analyzed numerically.