In this study, thin film of pure zinc oxide (ZnO) and ZnO doped with Ga2O3 films with different concentrations (0, 0.03, 0.05, 0.07 and 0.09)wt% were prepared by pulsed laser deposition. The powder mixture was then sintered in a furnace at 1273 K for 5 h. The resulting powders were thoroughly ground and then pressed using a special press to form discs with a diameter of 1 cm and a thickness of 0.5 cm. The deposition was carried out under a vacuum of 2.5×10−2 mbar on various substrates, including glass for AFM measurements and n-type crystalline silicon wafers for the gas sensor. AFM results revealed a progressive increase in both grain size and roughness with moderate doping and irregularity at high doping levels. Gas-sensing meas

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to

Nuclear structure of 20,22Ne isotopes has been studied via the shell model with Skyrme-Hartree-Fock calculations. In particular, the transitions to the low-lying positive and negative parity excited states have been investigated within three shell model spaces; sd for positive parity states, spsdpf large-basis (no-core), and zbme model spaces for negative parity states. Excitation energies, reduced transition probabilities, and elastic and inelastic form factors were estimated and compared to the available experimental data. Skyrme interaction was used to generate a one-body potential in the Hartree-Fock calculations for each selected excited states, which is then used to calculate the single-particle matrix elements. Skyrme interac

This investigation provides a comprehensive anatomical, histological, and endocrine profile of the thyroid gland in adult guinea fowls (Numida meleagris), a species for which detailed morphological data remain scarce in avian literature. A total of ten clinically healthy specimens, representing both sexes, were subjected to morphometric analysis of their thyroid glands, including lobar dimensions and weight. Anatomical dissection revealed that the glands are bilaterally positioned at the thoracic inlet, symmetrically located near the carotid arteries. Histological examinations—conducted using Hematoxylin and Eosin and Masson\'s trichrome stains—demonstrated the presence of structurally uniform follicles surrounded by a highly vasculariz

     The oral cavity has the second major and most diverse microflora after the gut. Since it is the starting point of digestion; the oral microbiota is essential for maintaining oral and systemic health.  Thus, this study aimed to find the bacterial isolates which act as a causative agent of periodontal diseases in Iraqi patients and their relation with some immune oral parameters. Saliva specimens and oral swabs of 91 patients (51) and control individuals (40) were collected in this study. The specimens of patients were collected from Al-Amirya and Almaamon Specialized Dental Centers in Baghdad for a period from November/2021 to February/2022. The microbiological results revealed, that the most prevalent bacterial isolates we

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Water-based drilling fluids (WBDFs) are the industry-preferred medium for drilling reactive shale formations, yet they remain susceptible to shale swelling, fluid invasion, and cuttings dispersion—all of which compromise wellbore stability. Although oil-based fluids (OBFs) provide effective shale inhibition, their high cost and adverse environmental profile limit their use. Nanoparticles (NPs) derived from waste feedstocks offer a low-cost, environmentally responsible alternative for enhancing WBDF performance, but no prior study has simultaneously evaluated both waste-derived SiO2 and Al2O2 NPs within a single WBDF system. This study synthesised SiO2 NPs from Halfaya bentonite clay waste and Al2O2 NPs from recycled aluminium scrap, char