ABSTRACT— In primary teeth, root canal treatment is a time consuming and challenging procedure, particularly during the most important step in endodontic treatment which is the preparation of the canal. Pulpectomy is the treatment of choice in all the necrotic primary teeth. For better treatment protocol, advancing technology brought the rotary system to reduce the manual dexterity and improve the quality of treatment for pulpectomy. This study aimed to compare and assess the efficacy of cleaning and the time required for the instrumentation during the preparation of root canals of the primary molars using the rotary and the manual (conventional) systems. Thirty root canals of primary teeth were selected. These teeth submitted to access opening and then all the canals injected with Indian ink. Then, 48 hours later, the teeth were randomly classified into two groups: group A (n=fifteen tooth): where the manual preparation of the root canals was done by stainless steel K- files, while group B (n= fifteen tooth): consisted of the root canals that prepared with rotary two shape system. The total instrumentation time was measured using a digital stopwatch. After that, a disk bur was used to section the roots. Then, a digital camera was used to photograph the specimens to evaluate the root canal cleaning. The cleaning efficacy was compared at the coronal, middle and apical level. In the coronal third, rotary two shape system showed more removal to the ink than the K-file with statistical significant difference (p <0.05), however, for the middle third of the canal, no statistical difference was found between the two systems (p=0.05). While at the apical level, K-file showed more removal to the ink than the rotary two shape system and with statistical significant difference (p <0.05). Evaluation of the total samples revealed no statistical significant difference concerning the efficacy of cleaning between K-files and rotary two shape system files. The group that was rotary prepared took less time for the canal preparation as compared to the manual group (80.063 sec., 144.576 sec. respectively). No significant difference was found between the two systems concerning the cleaning efficacy. Instrumentation done by the rotary system took significantly less time than that of the manual. KEYWORDS: Cleaning efficacy, manual instrumentation, primary teeth, rotary instrumentation.
This study aims to encapsulate atenolol within floating alginate-ethylcellulose beads as an oral controlled-release delivery system using aqueous colloidal polymer dispersion (ACPD) method.To optimize drug entrapment efficiency and dissolution behavior of the prepared beads, different parameters of drug: polymer ratio, polymer mixture ratio, and gelling agent concentration were involved.The prepared beads were investigated with respect to their buoyancy, encapsulation efficiency, and dissolution behavior in the media: 0.1 N HCl (pH 1.2), acetate buffer (pH 4.6) and phosphate buffer (pH 6.8). The release kinetics and mechanism of the drug from the prepared beads was investigated.All prepared atenolol beads remained f
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In this paper, a microcontroller-based electronic circuit have been designed and implemented for dental curing system using 8-bit MCS-51 microcontroller. Also a new control card is designed while considering advantages of microcontroller systems the time of curing was controlled automatically by preset values which were input from a push-button switch. An ignition based on PWM technique was used to reduce the high starting current needed for the halogen lamp. This paper and through the test result will show a good performance of the proposed system.
The aim of the present study was to develop theophylline (TP) inhalable sustained delivery system by preparing solid lipid microparticles using glyceryl behenate (GB) and poloxamer 188 (PX) as a lipid carrier and a surfactant respectively. The method involves loading TP nanoparticles into the lipid using high shear homogenization – ultrasonication technique followed by lyophilization. The compositional variations and interactions were evaluated using response surface methodology, a Box – Behnken design of experiment (DOE). The DOE constructed using TP (X1), GB (X2) and PX (X3) levels as independent factors. Responses measured were the entrapment efficiency (% EE) (Y1), mass median
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To damp the low-frequency oscillations which occurred due to the disturbances in the electrical power system, the generators are equipped with Power System Stabilizer (PSS) that provide supplementary feedback stabilizing signals. The low-frequency oscillations in power system are classified as local mode oscillations, intra-area mode oscillation, and interarea mode oscillations. A suitable PSS model was selected considering the low frequencies oscillation in the inter-area mode based on conventional PSS and Fuzzy Logic Controller. Two types of (FIS) Mamdani and suggeno were considered in this paper. The software of the methods was executed using MATLAB R2015a package.
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Piroxicam (PIR) is a nonsteroidal anti-inflammatory drug of oxicam category, used in gout, arthritis, as well as other inflammatory conditions (topically and orally). PIR is practically insoluble in water, therefore the aim is prepare and evaluate piroxicam as liquid self-nanoemulsifying drug delivery system to enhance its dispersibility and stability. The Dispersibilty and Stability study have been conducted in Oil, Surfactant and Co-surfactant for choosing the best materials to dissolve piroxicam. The pseudo ternary phase diagrams have been set at 1:1, 2:1, 3:1 as well as 4:1 ratio of surfactants and co-surfactants, also there are 4 formulations were prepared by using various concentrations of transcutol HP, cremophore EL and triacetin
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
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