Sequencing technologies have reshaped the study of the subgingival microbiome, but selecting the appropriate method remains challenging because of differences in resolution, cost, host DNA contamination, and computational complexity. This review compares 16S rRNA sequencing, full-length 16S, shotgun metagenomics, and metatranscriptomics with respect to taxonomic resolution, functional output, sample requirements, and analytical limitations. Key practical issues, including low microbial biomass, contamination control, and the choice of appropriate bioinformatic tools, are emphasized to help researchers avoid common pitfalls. A decision-making framework is provided to link study goals to suitable sequencing methods while outlining rea

This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l

The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l

We prepared polythiophene (PTH) with single wall carbon nanotube (SWCNT) nanocomposite thin films for Nitrogen dioxide (NO2) gas sensing applications. Thin films were synthesized via electrochemical polymerization method onto (Indium tin oxide) ITO coated glass substrate of thiophene monomer with magnesium perchlorate and different concentration from SWCNT (0.012 and 0.016) % in the presence130mL of Acetonitrile used. X-ray diffraction (XRD), Field Emission Scanning Electron microscopy (FE-SEM), Atomic Force Microscope (AFM) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to characterized these nanocomposite thin films. The response of these nanocomposite for NO₂ gas was evaluated via monitoring the change

Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t