Amr A. Sharawi

Effect of Two Methods of Reinforcement on the Fracture Strength of Interim Fixed Partial Dentures

PURPOSE This study assessed the efficiency of reinforcing provisional restorations by adding a fine gauze metallic mesh or polyethylene fibers between the abutments spanning the pontic length. MATERIALS AND METHODS Forty-five resin fixed partial dentures (FPDs) were constructed using three provisional resins. The three resin groups were further divided into three subgroups depending on their reinforcement. Specimens were loaded compressively, and the load required to fracture the specimens was recorded in Newtons. Data were presented as means and standard deviation values. A regression model with two-way ANOVA was used in testing significance. Duncans post hoc test was used for pairwise comparison (p < or = 0.05). RESULTS Duralay resin and Duralay fiber-reinforced restorations showed the highest fracture-resistance values, followed by Protemp and Snap, which showed statistically similar values. The three mesh-reinforced resin restoration materials showed no statistically significant difference between their fracture resistance values. Reinforcement did not alter the fracture resistance of Duralay and Protemp resin subgroups, but significantly increased that of Snap, equalizing it with the other resins. The three resin materials had similar moduli. Significant alterations occurred after fiber reinforcement. Results showed that fiber-reinforced Duralay resin showed the highest modulus values, while no statistical difference was found between the moduli of fiber-reinforced Protemp and Snap. Regarding the mesh-reinforced groups, Duralay had the highest modulus followed by Protemp and Snap. Reinforcements altered the modulus values of Duralay resin only. Mesh-reinforced Duralay resin showed the highest mean modulus, but no statistically significant difference was apparent between fiber-reinforced and control groups. As for Protemp and Snap resin subgroups, their moduli remained unchanged by reinforcements. CONCLUSION Initially, Duralay resin had higher fracture resistance values than Protemp II and Snap. Fiber and mesh reinforcements increased the fracture resistance of Snap. No statistically significant difference was evident among the fracture resistances of the three mesh-reinforced resin FPD restorations. The three resins had similar moduli. Fiber and mesh reinforcement increased the modulus of Duralay resin but did not change that of Protemp and Snap. Fiber and metal mesh reinforcements may alter the fracture strength and modulus of some, but not all, provisional resins.

Preventive Maintenance Prioritization Index of Medical Equipment Using Quality Function Deployment

Preventive maintenance is a core function of clinical engineering, and it is essential to guarantee the correct functioning of the equipment. The management and control of maintenance activities are equally important to perform maintenance. As the variety of medical equipment increases, accordingly the size of maintenance activities increases, the need for better management and control become essential. This paper aims to develop a new model for preventive maintenance priority of medical equipment using quality function deployment as a new concept in maintenance of medical equipment. We developed a three-domain framework model consisting of requirement, function, and concept. The requirement domain is the house of quality matrix. The second domain is the design matrix. Finally, the concept domain generates a prioritization index for preventive maintenance considering the weights of critical criteria. According to the final scores of those criteria, the prioritization action of medical equipment is carried out. Our model proposes five levels of priority for preventive maintenance. The model was tested on 200 pieces of medical equipment belonging to 17 different departments of two hospitals in Piedmont province, Italy. The dataset includes 70 different types of equipment. The results show a high correlation between risk-based criteria and the prioritization list.

High performance GPU-Based fourier volume rendering

Fourier volume rendering (FVR) is a significant visualization technique that has been used widely in digital radiography. As a result of its 𝒪(N 2log⁡N) time complexity, it provides a faster alternative to spatial domain volume rendering algorithms that are 𝒪(N 3) computationally complex. Relying on the Fourier projection-slice theorem, this technique operates on the spectral representation of a 3D volume instead of processing its spatial representation to generate attenuation-only projections that look like X-ray radiographs. Due to the rapid evolution of its underlying architecture, the graphics processing unit (GPU) became an attractive competent platform that can deliver giant computational raw power compared to the central processing unit (CPU) on a per-dollar-basis. The introduction of the compute unified device architecture (CUDA) technology enables embarrassingly-parallel algorithms to run efficiently on CUDA-capable GPU architectures. In this work, a high performance GPU-accelerated implementation of the FVR pipeline on CUDA-enabled GPUs is presented. This proposed implementation can achieve a speed-up of 117x compared to a single-threaded hybrid implementation that uses the CPU and GPU together by taking advantage of executing the rendering pipeline entirely on recent GPU architectures.

Offline large scale fourier volume rendering on low-end hardware

The resolution of medical data sets acquired by state-of-the-art imaging modalities is growing rapidly. Providing high-end workstations to visualize such data sets might not be affordable in some cases. To resolve this issue, there should be alternative convenient software solutions to handle huge data sets either by out-of-core or offline rendering applications. This presented work features an offline rendering pipeline that is capable of rendering digital x-ray radiographs of very large scale volumetric data sets, which cannot fit into the memory of the running platform relying on spatial-domain decomposition and projection-slice theorem.

MATLAB-based fourier volume rendering framework

Volume rendering plays a significant role in medical imaging. It allows exploring the internal structures of volumetric data acquired by the different imaging modalities. This exploration allows accurate diagnosis and consequently effective treatment. Various volume rendering techniques exists. However, compared to other techniques, Fourier volume rendering has gained a wide acceptance by the radiologists for several reasons. This technique generates attenuation renderings similar to x-ray radiographs that are well interpreted by the physicians. Additionally, it works with time complexity of O(N2logN), and thus, it delivers interactive frame rates for large scale medical volumes in comparison with spatial-domain rendering techniques. The complexity associated with developing a basic rendering pipeline for this technique hinders medical imaging scientists from focusing their research on investigating new algorithms for improving the reconstruction quality of the resulting digital radiographs. In this paper, we present a flexible, extensible and semi-interactive high-level MATLAB-based framework for the Fourier volume rendering pipeline.

Application of quality function deployment and genetic algorithm for replacement of medical equipment

The management of medical equipment raises a range of complex problems including those associated with replacement processes. One of the most significant challenges is to identify a proper list of medical equipment that requires replacement and then to optimize this list. In this article, we present a new approach to solve this problem by integrating Quality Function Deployment (QFD) and Genetic Algorithm (GA) in one framework. In a previous application, QFD has proven its validity to solve the priority problem; meanwhile GA is an optimization method. Hence, the proposed model, QFD-GA, was developed to prioritize the medical equipment for replacement process taking into account a set of criteria; in addition, the prioritized list is optimized according to the available budget of the hospital to maximize the number of replaced devices. The validation of the proposed model was carried out on sixty devices that include different types of medical equipment in one public hospital. Results show that the proposed model can efficiently classify the priority into four subcategories, and simultaneously maximize the number of medical equipment to be replaced considering the budget constraint.

A New Approach for Preventive Maintenance Prioritization of Medical Equipment

Efficient maintenance of medical equipment is crucial phase in medical equipment management. Preventive maintenance is a core function of clinical engineering and it is essential to guarantee the correct functioning of the equipment. The aim of this paper is to develop a new model for preventive maintenance priority of medical equipment using the quality function deployment (QFD) as a new concept in maintenance of medical equipment. We developed a 3 domain framework consisting of requirements, function, and concepts. The requirements domain is the house of quality matrix (HOQ) or planning matrix. The second domain is the design matrix. Finally, the concept domain contains the critical criteria for preventive maintenance prioritization with its weights. According to the final scores of the criteria, the prioritization of medical equipment is performed. The data set includes 200 medical equipment belonging to 17 different departments of 2 hospitals in Piemonte; Italy. It includes 70 different types of equipment. Our model proposes 5 levels of priority for preventive maintenance. The results show a high correlation between risk - based criteria and prioritization.

Modeling of medical equipment maintenance in health care facilities to support decision making

Observation of maintenance programs in healthcare facilities is an essential requirement for almost all equipment in order to guarantee its performance, prevent sudden failures and to extend the equipments life expectancy. In this work availability, reliability and performance efficiency were used for equipment performance judgment, in order to support the clinical engineers decision making process. Time series models were the suggested technical tools used for prediction. Two models were used in this study. Raw data were processed in an excel sheet and used as input data to Autoregressive Moving Average (ARMA) and Linear Predictive Coefficient (LPC) filters. The two models produced good prediction results compared to real data. The ARMA model resulted in the minimum mean square error compared to the other model.

Sensitivity Improvement of Micro-diaphragm Deflection for Pulse Pressure Detection

Cardiovascular diseases are one of the leading causes of death. Globally, they underlie the death of one third of the world’s population. The main cause of cardiovascular diseases is atherosclerosis which makes arteries less elastic (called ‘‘hardening of the arteries” or ‘‘arterial stiffness’’). The optical Micro Electro Mechanical System (MEMS) pressure sensor has shown its potential in the diagnosis of arterial stiffness that can be conducted by detecting the pulse pressure in the radial artery. In this paper, we attempt to improve the sensitivity of micro-diaphragm deflection in optical Micro-electromechanical System (MEMS) sensors as applied to pulse pressure detection, thus aiming to determine the safety of a person’s measured pulse of cardiovascular disease. The deflection sensitivity improvement was evidenced using Finite Element Analysis ANSYS software. Corrugation for periphery-clamped silicon nitride (Si3N4) micro-diaphragm based on the variation of the diaphragm thickness (td) and some corrugation factors such as the corrugation angle (β) and the corrugation depth (hc) was implemented to reduce bending and tensile stresses which limit the micro-diaphragm deflection sensitivity. This was supported by calculating the von Mises stress. Analytic results show agreement with ANSYS software simulation with a static response of 1.27 μm maximum deflection under applied pressure of 300 mmHg in the case of the corrugated micro-diaphragm, compared to a 0.32 μm maximum deflection in the case of a flat micro-diaphragm, and for the same applied pressure, a maximum deflection sensitivity of 4.23 × 10−3 μm/mmHg for the corrugated micro-diaphragm compared to 1.07 × 10−3 μm/mmHg for the flat one, and the reduction of micro-diaphragm bending and initial tensile stresses exhibited by maximum equivalent stress (von Mises stress) of 159.99 MPa for the corrugated compared to 175.9 MPa for the flat one. Therefore, the implementation of corrugation presents the chance to control mechanical deflection sensitivity and compared to the film deposition process control it is often an easier way.

An Optimal Scheduling for Medical Equipment Preventive Maintenance Over a Finite Planning Horizon Using Ant Colony Algorithm

The importance of preventive maintenance management has been gradually recognized specially with the great attention to the role of health technology management. Finding the optimal schedule to perform preventive maintenance for medical equipment is rarely considered in the literature. This research suggests using ant colony optimization method to solve the problem of finding the optimal preventive maintenance schedule. We developed 2 versions of the algorithm, both starting from a prioritized medical equipment list and differing in the heuristic function. The experimental results indicate the effectiveness of the ant colony optimization algorithm for this kind of problems.