Background: The association between facial types and dental arches forms has considerable implications in orthodontic diagnosis and treatment planning. The aim was to establish the maxillary and mandibular dental arches width and length in skeletal and dental class II division 1 and class III malocclusion groups, find out the most frequent dental arch form and facial type and the association between them and to check the gender differences. Materials and Methods: Frontal and lateral facial photographs and maxillary and mandibular occlussal photographs for 90 iraqi subjects with age 18-25 years old (45 males and 45 females) divided equally into three groups, the 1st group with class II division 1malocclusion (overjet more than 3mm but less t

background: human epidermal growth factor receptor-2 (her2/neu) is related to growth factor receptors with alkaline kinase activity and it is regarded as important prognostic and therapeutic factor that can depended on in breast cancer therapy. HER2/neu expression by immunohistochemistry (IHC) is submitted to a great in terob server inconsistency. Subsequently additional confirmatory tests for assessment of gene alterations and amplification status are needed for patients with early or metastatic breast cancer. In situ hybridization techniques and specifically Chromogenic in situ hybridization (CISH) was arise as a practical, cost-effective, and alternative to fluorescent in situ hybridization in testing for gene alterationAims of the study

The study aims to identify the degree of implementation of the coronavirus prevention standards (covid-19) in the kingdom of Saudi Arabia and compare it with the families of intellectual disabilities. The study population consisted of all families residing in the Kingdom of Saudi Arabia. To achieve the objectives of the research, the analytical descriptive approach was employed. The study sample consisted of (372) families, among them (84) families with intellectual disabilities, and (288) families without intellectual disabilities. They were chosen from the Saudi community according to what is available for collection in a simple random way, using the standard criteria for the prevention of coronavirus (Covid- 19) Prepared by the resear

The research includes the synthesis and identification of the mixed ligands complexes of M+2ions in general composition[M(Asn)2(SMX)] Where L- Aspargine (C4H8N2O3)symbolized (AsnH) as a primary ligand and Sulfamethoxazole(C10H11N3O3S) symbolized (SMX) as a secondary ligand. The ligands and the metal chlorides were brought in to reaction at room temperature in(v/v) ethanol /water as solvent containing NaOH. The reaction required the following [(metal: 2(Na+Asn-): (SMX)] molar ratios with M(II) ions, Where: M(II)=Mn(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II). The UV–Vis and magnetic moment data revealed an octahedral geometry around M(II), The conductivity data show a non-electrolytic nature of the complexes. The antimicrobial a

Infectious diseases pose a global challenge, necessitating an exploration of novel methodologies for diagnostics and treatments. Since the onset of the most recent pandemic, COVID-19, which was initially identified as a worldwide health crisis, numerous countries experienced profound disruptions in their healthcare systems. To combat the spread of the COVID-19 pandemic, governments across the globe have mobilized significant efforts and resources to develop treatments and vaccines. Researchers have put forth a multitude of approaches for COVID-19 detection, treatment protocols, and vaccine development, including groundbreaking mRNA technology, among others.

This matter represents not only a scientific endeavor but also an essenti

Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed.  A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing

Deep learning techniques are used across a wide range of fields for several applications. In recent years, deep learning-based object detection from aerial or terrestrial photos has gained popularity as a study topic. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles andclassification probabilities for an image. In layman's terms, it is a technique for instantly identifying and rec