This article will address autoclave design considerations and
manufacturing working with high pressure low temperature
supercritical drying technique to produce silica aerogel. The design
elects carbon dioxide as a supercritical fluid (31.7 oC and 72.3 bar).
Both temperature and pressure have independently controlling
facility through present design. The autoclave was light weight (4.5
kg) and factory-made from stainless steel. It contains a high pressure
window for monitoring both transfer carbon dioxide gas to liquid
carbon dioxide and watching supercritical drying via aerogel
preparation process. In this work aerogel samples were prepared and
the true apparent densities, total pore volume and pore size
distribution, BET surface area, spectroscopic refractive index,
structure and thermal properties have been systematically
investigated characteristic.
Background: Alveolar ridge expansion is proposed when the alveolar crest thickness is ≤5 mm. The screw expansion technique has been utilized for many years to expand narrow alveolar ridges. Recently, the osseodensification technique has been suggested as a reliable technique to expand narrow alveolar ridges with effective width gain and as little surgical operating time as possible. The current study aimed to compare osseodensification and screw expansion in terms of clinical width gain and operating time. Materials and methods: Forty implant osteotomies were performed in deficient horizontal alveolar ridges (3–5 mm). A total of 19 patients aged 21–59 years were randomized into two groups: the screw expansion group, which invo
... Show MoreThe faujasite type Y zeolite catalyst was prepared from locally available kaolin. For prepared faujasite type NaY zeolite X-ray, FT-IR, BET pore volume and surface area, and silica/ alumina were determined. The Xray and FT-IR show the compatibility of prepared catalyst with the general structure of standard zeolite Y. BET test shows that the surface area and pore volume of prepared catalyst were 360 m2 /g and 0.39 cm3 /g respectively.
The prepared faujasite type NaY zeolite modified by exchanging sodium ion with ammonium ion using ammonium nitrate and then ammonium ion converted to hydrogen ion. The maximum sodium ion exchange with ammonium ion was 53.6%. The catalytic activity of prepared faujasite type NaY, NaNH4Y and NaHY zeolites
The responsibility of the Central Bank through the implementation of its monetary policy to maintain the integrity and stability of the financial system and the economic system, because any shock, whether internal or external, may endanger the financial system and instability, so the research sheds light on the effectiveness of monetary policy in maintaining financial stability, The most important conclusion is that there is an increase in capital, which gives banks the possibility to face the risks to which they are exposed, as well as a rise in the total bad debts, which weakens its financial position, which constitutes a decline in the financial stability of these banks.
Reactive Powder Concrete (RPC) is one of the most advanced recent high compressive strength concrete. This work explored the effects of using glass waste as a fractional replacement for fine aggregate in reactive powder concrete at levels of 0%, 25%, 50%, and 100%. Linear and mass attenuation coefficients have been calculated as a function of the sample's thickness and bremsstrahlung energy. These coefficients were obtained using energy selective scintillation response to bremsstrahlung having an energy ranging from (0.1-1.1) MeV. In addition, the half-value thickness of the samples prepared has been investigated. It was found that there is a reversal association between the attenuation coefficient and the energy of the bremsstrahlu
... Show MoreThere are many images you need to large Khoznah space With the continued evolution of storage technology for computers, there is a need nailed required to reduce Alkhoznip space for pictures and image compression in a good way, the conversion method Alamueja
Abstract Software-Defined Networking (commonly referred to as SDN) is a newer paradigm that develops the concept of a software-driven network by separating data and control planes. It can handle the traditional network problems. However, this excellent architecture is subjected to various security threats. One of these issues is the distributed denial of service (DDoS) attack, which is difficult to contain in this kind of software-based network. Several security solutions have been proposed recently to secure SDN against DDoS attacks. This paper aims to analyze and discuss machine learning-based systems for SDN security networks from DDoS attack. The results have indicated that the algorithms for machine learning can be used to detect DDoS
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