We describe the synthesis and characterization of a novel 2D-MnOx material using a combination of HR-TEM, XAS, XRD, and reactivity measurements. The ease with which the 2D material can be made and the conditions under which it can be made implies that water oxidation catalysts previously described as “birnessite-like” (3D) may be better thought of as 2D materials with very limited layer stacking. The distinction between the materials as being “birnessite-like” and “2D” is important because it impacts on our understanding of the function of these materials in the environment and as catalysts. The 2D-MnOx material is noted to be a substantially stronger chemical oxidant than previously noted for other birnessite-like manganese oxi

The present study was conducted to estimate the incidence, clinical findings, cytological and histopathological characteristics of spontaneously occurring skin neoplasms in dogs. A total of 40 grossly suspected cases of cutaneous and subcutaneous tumors were gathered during the period from July 2016 to August 2018 from male and female dogs in Baghdad city. Dogs with skin neoplasia revealed various clinical signs, and their ages were older than 5 years to 15 years. German shepherd 30% followed by Terrier dogs 25% were more influenced than other breeds. Concerning tumor features, the majority of neoplasms had solitary lesion 70%, regular shapes 65% with black color 55%. The tumors frequently occurred on fore-limbs and abdomen, and 80% of them

A political perusal of Initiations in Declaring Middle East a District vacant of mass Destruction weapons

The research aimed to investigate the level of Organizational Cynicism and Job Engagement of Government Schools teachers in Al Zubair district. To achieve this research was conducted on a random sample of (66) items. The statistical package for social sciences (SPSS) was used to analyze and examine the hypotheses. The researcher used many statistical methods to achieve the research objectives, such as simple, multi regression and the research results showed there is a significant impact to teacher's in the schools of the research sample between Organizational cynicism and Job  Engagement             

Background: Facial disfigurement can be the result of a congenital anomaly, trauma or tumor surgery, in many cases the prosthetic rehabilitation is indicated. Maxillofacial prosthetic materials should have desirable and ideal physical, aesthetic, and biological properties and those properties should be kept for long period of time in order to reach patient acceptance. Silicone elastomer are the most commonly used material for facial restoration because of its favorable properties mechanically and physically as the biocompatibility and good elasticity. Aim of this study: This study aimed to evaluate the effect of addition of Aluminum oxide (Al2O3) Nano fillers in different concentrations on tear strength and hardness of VST 50F room tempe

It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

Tight oil reservoirs have been a concerned of the oil industry due to their substantial influence on oil production. Due to their poor permeability, numerous problems are encountered while producing from tight reservoirs. Petrophysical and geomechanical rock properties are essential for understanding and assessing the fracability of reservoirs, especially tight reservoirs, to enhance permeability. In this study, Saadi B reservoir in Halfaya Iraqi oil field is considered as the main tight reservoir. Petrophysical and geomechanical properties have been estimated using full-set well logs for a vertical well that penetrates Saadi reservoir and validated with support of diagnostic fracture injection test data employing standard equations

Background: Denture cleansing was an important step that could prevent the spread of infection and improve a patient's health, the durability of the dentures, and the overall quality of life; therefore, it was necessary to choose a suitable cleanser that, in addition to being effective, did not have an unfavorable effect on the qualities of the denture base resin itself when used for an extended period. For this purpose, this study aimed to evaluate the effect of tea tree oil (TTO) on Candida albicans adhesion and the surface roughness property of poly(methyl methacrylate) denture material after immersion in TTO. Methods: A total of 55 heat-cured acrylic resin specimens were used for C. albicans adherence and surface roughness tests. The

This work is concerned with a two stages four beds adsorption chiller utilizing activated carbon-methanol adsorption pair that operates on six separated processes. The four beds that act as thermal compressors are powered by a low grade thermal energy in the form of hot water at a temperature range of 65 to 83 °C.  As well as, the water pumps and control cycle consume insignificant electrical power. This adsorption chiller consists of three water cycles. The first water cycle is the driven hot water cycle. The second cycle is the cold water cycle to cool the carbon, which adsorbs the methanol. Finally, the chilled water cycle that is used to overcome the building load. The theoretical results showed that average cycle cooling power

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec