Objectives: To assess the feasibility and accuracy of a new prototype robotic implant system for the placement of zygomatic implants in edentulous maxillary models. Methods: The study was carried out on eight plastic models. Cone beam computed tomographs were captured for each model to plan the positions of zygomatic implants. The hand-eye calibration technique was used to register the dynamic navigation system to the robotic spaces. A total of 16 zygomatic implants were placed, equally distributed between the anterior and the posterior parts of the zygoma. The placement of the implants (ZYGAN®, Southern Implants) was carried out using an active six-jointed robotic arm (UR3e, Universal Robots) guided by the dynamic navigation coordinate transformation matrix. The accuracy of the implant placement was assessed using EvaluNav and GeoMagicDesignX® software based on pre- and post-operative CBCT superimposition. Descriptive statistics for the implant deviations and Pearson’s correlation analysis of these deviations to force feedback recorded by the robotic arm were conducted. Results: The 3D deviations at the entry and exit points were 1.80 ± 0.96 mm and 2.80 ± 0.95 mm, respectively. The angular deviation was 1.74 ± 0.92◦. The overall registration time was 23.8 ± 7.0 min for each side of the model. Operative time excluding registration was 66.8 ± 8.8 min for each trajectory. The exit point and angular deviations of the implants were positively correlated with the drilling force perpendicular to the long axis of the handpiece and negatively correlated with the drilling force parallel to the long axis of the handpiece. Conclusion: The errors of the dynamic navigation-guided robotic placement of zygomatic implants were within the clinically acceptable limits. Further refinements are required to facilitate the clinical application of the tested integrated robotic-dynamic navigation system. Clinical significance: Robotic placement of zygomatic implants has the potential to produce a highly predictable outcome irrespective of the operator’s surgical experience or fatigue. The presented study paves the way for clinical applications.
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Background/Aim: Understanding how perinatal outcome variations affect dentition eruption can lead to healthcare providers monitoring and managing dental health in infants and children. This study aimed to evaluate the influence of gestational age, mode of delivery and birth weight on the stage of primary dentition eruption in children. Methods: A sample of 304 children aged 6-24 months from Baghdad City was studied. Information about gestational age, delivery method (vaginal vs Caesarean) and birth weight were evaluated through a parent-answered sheet. The stage of dental eruption was estimated based on the criteria established by Damodar P Swami. Statistical and descriptive analyses were utilised to compare the dental eruption stag
... Show MoreThis research is considered a simple attempt and effort which is it first and last target is to point at the procedures of the taxes account that aims to reduce the taxes from the persons and give free to the person who estimates the tax to practice what comes from the competent authorities to describe the person who estimates the tax and not an accountant who practice the accountant procedures which are imposed on him by the annual terms from higher administrations , So he can not evaluate state of the person who pay the tax , and he might be dissatisfied with his job , because his role can’t be activated from the general foundation taxes.
And so , this research includes four fields:-
... Show MoreThe history of the impact of nuclear radiation on the environment, as illustrated by the Hiroshima bombing, reveals a multifaceted interplay of scientific, ecological, and ethical dimensions. From the historical context and immediate environmental consequences to long-term ecological effects and human health implications, the effects of nuclear radiation are pervasive. Comparatively analyzed with other nuclear incidents, case studies of affected ecosystems, and through education, ongoing challenges and opportunities toward nuclear technology are revealed. Moreover, it is through the echoes of past nuclear events that lessons were learned which until today guide current efforts on striking a balance between technological advancement
... Show MorePain is a sensory and emotional experience that is influenced by physiologic, sensory, affective, cognitive, socio-cultural and behavioral factors. Postoperative pain is the commonest reason for delayed discharge and unanticipated hospital admission after ambulatory surgery. Our Objective is to test the hypothesis that administration of 2 ml/kg/hr preoperative IV fluids may attenuates postoperative pain.The study was carried out in the Baghdad Teaching Hospital, Al-Yarmok Teaching Hospital and Al-Karama Teaching Hospital from 12 May till 17 June 2009. The total number of patients was 120 (35 males and 85 females) with their age ranged between 10-90 years. The patients were divided into two groups according to administration of preop
... Show MoreThe pathogenicity of S. saprophyticus was studied in mice. A group of white mice were injected transurethrally using a catheter with S. saprophyticus S67 cell suspension in a concentration reached 109 CFU/ml. concomitantly, the role of its peptidoglycan in the pathogenicity was studied by injecting another group of mice with 0.3 mg/0.2 ml of partially purified S. saprophyticus S67 peptidoglycan extract. After autopsy, kidneys and urinary bladder showed several histopathological changes both in cells and peptidoglycan injected mice, included: hydropic degeneration, glomerulus shrinkage, congestion of renal vessels, infiltration of inflammatory cells, and dekeratinization in urinary bladder.
Feed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 m
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