Background: The prediction of changes in the mandibular third molar position and eruption is an important clinical concern because third molar retention may be beneficial for orthodontic anchorage. The aims of this study were to assess the mandibular third molar position by using medical CT scan and lateral reconstructed radiograph and evaluate gender differences. Materials and Methods: The sample of present study consisted of 39 patients (18 males and 21 females) with age range 11-15 years who were attending at Al-Suwayra General Hospital/ the Computerized Tomography department. The distance from anterior edge of ramus to distal surface of permanent mandibular second molar and mesio-distal width of developing mandibular third molar were

The current paper aims to investigate the stress distribution developed in Kennedy Class II mandibular distal extension removable partial dentures due to applying a unilateral load condition in both vertical and lateral oblique directions. 3D models of mandible bone and RPD framework were first built based on actual patient data and later exported to ANSYS software to implement the numerical analysis. For realistic analysis, the model considered the frictional contact between the RPD retainers with the teeth and mucosa with the resin denture base by applying the feature of small sliding. To ensure maximum longevity and suitability of restoration, two different metallic RPDs constructed from commercially pure titanium (CP Ti) and cob

The emergence of mixed matrix membranes (MMMs) or nanocomposite membranes embedded with inorganic nanoparticles (NPs) has opened up a possibility for developing different polymeric membranes with improved physicochemical properties, mechanical properties and performance for resolving environmental and energy-effective water purification. This paper presents an overview of the effects of different hydrophilic nanomaterials, including mineral nanomaterials (e.g., silicon dioxide (SiO2) and zeolite), metals oxide (e.g., copper oxide (CuO), zirconium dioxide (ZrO2), zinc oxide (ZnO), antimony tin oxide (ATO), iron (III) oxide (Fe2O3) and tungsten oxide (WOX)), two-dimensional transition (e.g., MXene), metal–organic framework (MOFs), c

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Mobile ad hoc network security is a new area for research that it has been faced many difficulties to implement. These difficulties are due to the absence of central authentication server, the dynamically movement of the nodes (mobility), limited capacity of the wireless medium and the various types of vulnerability attacks. All these factor combine to make mobile ad hoc a great challenge to the researcher. Mobile ad hoc has been used in different applications networks range from military operations and emergency disaster relief to community networking and interaction among meeting attendees or students during a lecture. In these and other ad hoc networking applications, security in the routing protocol is necessary to protect against malic

The clinical response to natalizumab in patients with multiple sclerosis (MS) may be significantly influenced by genetic variation. Mutations in genes related to the drug’s mechanism of action or the pathological milieu of MS can contribute substantially to interindividual differences in treatment outcomes. This review aims to provide an overview of previous studies that have examined genetic polymorphisms associated with the clinical efficacy of natalizumab. A systematic literature search was conducted across the PubMed, Google Scholar, and ResearchGate databases using targeted keywords relevant to the subject matter. Several genetic loci were found to be linked to natalizumab responsiveness, including the integrin subunit alpha 4 (ITGA4

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med