Background: The aim of this in vitro study was to evaluate and compare the microleakage between Vertise Flow T M composite material and other conventional (Filtek Z250, riva light cure and SDR) composite materials when restoring CII mesial box only cavity at gingival margin through die penetration test Materials and methods: Forty maxillary first premolars were prepared with class II box design only cavities. Samples were divided into four groups of ten teeth according to material used: group I (FiltekZ250 only). Group II (SDR+FiltekZ250). Group III (Vertise Flow +FiltekZ250). Group IV (Riva light cure+ FiltekZ250). After 24 hrs. immersion in 2% in methylene blue, samples were sectioned and micro leakage was estimated. Results: None of the

Background: Hair loss is a common distressing disease and challenging problem for many dermatologist. Telogen effluvium is the most common hair loss disease in which nutritional deficiencies may precipitate the disease through their effect on hair structure and growth.

Study Aim : Validating role of serum ferritin level and body mass index in Chronic Telogen Effluvium and analyzing association between these factors with socioeconomic, demographic, gynecological factors and weight loss effect. Establishing a nutritional preventive advice to improve treatment successfulness and decrease the disease occurrence.

A field experiment was conducted during winter season of 2021 at a research station of college of agricultural engineering sciences, university of Baghdad to determine the response of active fertility percentage and seed yield and its components of faba bean (Vicia faba L. cv. Aguadulce) to distance between plants and spraying of nano and traditional boron. A Randomized Complete Block Design according to split-plots arrangement was used at three replicates. The main plots were three distances between plants (25, 35 and 45 cm), while the sub plots including spraying of distilled water only (control treatment), spraying of boron at a 100 mg L^-1 and spraying of nano boron at two concentrations (1

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 "Nudge" Theory is considered one of the most recent theories, which is clear in the economic, health, and educational sectors, due to the intensity of studies on it and its applications, but it has not yet been included in crime prevention studies. The use of  Nudge theory appears to enrich the theory in the field of crime prevention, and to provide modern, effective, and implementable mechanisms.

The study deals with the "integrative review" approach, which is a distinctive form of research that generates new knowledge on a topic through reviewing, criticizing, and synthesizing representative literature on the topic in an integrated manner so that new frameworks and perspectives are created around it.

The study is bas

Acid treatment is a widely used stimulation technique in the petroleum industry. Matrix acidizing is regarded as an effective and efficient acidizing technique for carbonate formations that leads to increase the fracture propagation, repair formation damage, and increase the permeability of carbonate rocks. Generally, the injected acid dissolves into the rock minerals and generates wormholes that modify the rock structure and enhance hydrocarbon production. However, one of the key issues is the associated degradation in the mechanical properties of carbonate rocks caused by the generated wormholes, which may significantly reduce the elastic properties and hardness of rocks. There have been several experimental and simulation studies regardi

Rotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect

A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.

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