A Comparative study between Different Treatment Modalities of Floating Knee Jnjury At Aswan University Hospital

Purpose: The study aimed at presenting a comparison between the modalities of treatment different of floating knee injury at Aswan University Hospital.  Materials and Methods:  This study is a prospective study including all of our 20 cases of floating knee injuries who were treated utilizing various treatment modalities at Aswan University Hospital between December 2018 and September 2019 with a follow-up period of 12 months  Results: Based on the data analysis,  nailing is a better modality in floating knee injury (especially with diaphyseal long bone). Moreover, plating is a good choice for distal fractures, the external fixator is considered a choice for limb saving(as in popliteal ischemia, open fractures(OG3), and compartment syndrome).  Conclusion: Management of floating knee injury is critical as floating knee injury is not like other fractures. Floating knee injuries are serious injuries with a high rate of complications. Besides being caused by high-energy trauma with extensive skeletal and soft tissue damage, they are also associated with potentially life-threatening injuries of the head, chest, and abdomen. There are multiple controversies in surgical management starting from choosing suitable fixation for each patient according to variable conditions.  Floating knee injury remains a challenging orthopedic problem in which regaining good knee function outcome is a major concern. Stable osteosynthesis to achieve rigid fixation and early mobilization should always be attempted

Adopting Scenario-Based approach to solve optimal reactive power Dispatch problem with integration of wind and solar energy using improved Marine predator algorithm

The penetration of renewable energy resources into electric power networks has been increased considerably to reduce the dependence of conventional energy resources, reducing the generation cost and greenhouse emissions. The wind and photovoltaic (PV) based systems are the most applied technologies in electrical systems compared to other technologies of renewable energy resources. However, there are some complications and challenges to incorporating these resources due to their stochastic nature, intermittency, and variability of output powers. Therefore, solving the optimal reactive power dispatch (ORPD) problem with considering the uncertainties of renewable energy resources is a challenging task. Application of the Marine Predators Algorithm (MPA) for solving complex multimodal and non-linear problems such as ORPD under system uncertainties may cause entrapment into local optima and suffer from stagnation. The aim of this paper is to solve the ORPD problem under deterministic and probabilistic states of the system using an improved marine predator algorithm (IMPA). The IMPA is based on enhancing the exploitation phase of the conventional MPA. The proposed enhancement is based on updating the locations of the populations in spiral orientation around the sorted populations in the first iteration process, while in the final stage, the locations of the populations are updated their locations in adaptive steps closed to the best population only. The scenario-based approach is utilized for uncertainties representation where a set of scenarios are generated with the combination of uncertainties the load demands and power of the renewable resources. The proposed algorithm is validated and tested on the IEEE 30-bus system as well as the captured results are compared with those outcomes from the state-of-the-art algorithms. A computational study shows the superiority of the proposed algorithm over the other reported algorithms

Solving the Optimal Reactive Power Dispatch Using Marine Predators Algorithm Considering the Uncertainties in Load and Wind-Solar Generation Systems

The optimal reactive power dispatch (ORPD) problem is an important issue to assign the most efficient and secure operating point of the electrical system. The ORPD became a strenuous task, especially with the high penetration of renewable energy resources due to the intermittent and stochastic nature of wind speed and solar irradiance. In this paper, the ORPD is solved using a new natural inspired algorithm called the marine predators’ algorithm (MPA) considering the uncertainties of the load demand and the output powers of wind and solar generation systems. The scenario-based method is applied to handle the uncertainties of the system by generating deterministic scenarios from the probability density functions of the system parameters. The proposed algorithm is applied to solve the ORPD of the IEEE-30 bus system to minimize the power loss and the system voltage devotions. The result verifies that the proposed method is an efficient method for solving the ORPD compared with the state-of-the-art techniques

Technoeconomic and Environmental Study of Multi-Objective Integration of PV/Wind-Based DGs Considering Uncertainty of System

For technological, economic, and environmental reasons, renewable distributed generators (RDGs) have been extensively used in distribution networks. This paper presents an effective approach for technoeconomic analysis of optimal allocation of REDGs considering the uncertainties of the system. The primary issue with renewable-based distributed generators, especially wind and photovoltaic systems, is their intermittent characteristic that results in fluctuating output power and, hence, increasing power system uncertainty. Thus, it is essential to consider the uncertainty of such resources while selecting their optimal allocation within the grid. The main contribution of this study is to figure out the optimal size and location for RDGs in radial distribution systems while considering the uncertainty of load demand and RDG output power. A Monte Carlo simulation approach and a backward reduction algorithm were used to generate a reasonable number of scenarios to reflect the uncertainties of loading and RDG output power. Manta ray foraging optimization (MRFO), an efficient technique, was used to estimate the ratings and placements of the RDGs for a multi-objective function that includes the minimization of the expected total cost, total emissions, and total system voltage deviation, in addition to enhancing predicted total voltage stability. An IEEE 118-bus network was used as a large interconnected network, along with a rural 51-bus distribution grid and the IEEE 15-bus model as a small distribution network to test the developed technique. Simulations demonstrate that the proposed optimization technique effectively addresses the optimal DG allocation problem. Furthermore, the results indicate that using the proposed method to optimally integrate wind turbines with solar-based DG decreases the expected costs, emissions, and voltage deviations while improving voltage stability by 40.27%, 62.6%, 29.33%, and 4.76%, respectively, for the IEEE 118-bus system and enhances the same parameters by 35.57%, 59.92%, 68.95%, and 11.88%, respectively, for the rural 51-bus system and by 37.74%, 61.46%, 58.39%, and 8.86%, respectively, for the 15-bus system

Solving Non-Smooth Optimal Power Flow Problems Using a Developed Grey Wolf Optimizer

The optimal power flow (OPF) problem is a non-linear and non-smooth optimization problem. OPF problem is a complicated optimization problem, especially when considering the system constraints. This paper proposes a new enhanced version for the grey wolf optimization technique called Developed Grey Wolf Optimizer (DGWO) to solve the optimal power flow (OPF) problem by an efficient way. Although the GWO is an efficient technique, it may be prone to stagnate at local optima for some cases due to the insufficient diversity of wolves, hence the DGWO algorithm is proposed for improving the search capabilities of this optimizer. The DGWO is based on enhancing the exploration process by applying a random mutation to increase the diversity of population, while an exploitation process is enhanced by updating the position of populations in spiral path around the best solution. An adaptive operator is employed in DGWO to find a balance between the exploration and exploitation phases during the iterative process. The considered objective functions are quadratic fuel cost minimization, piecewise quadratic cost minimization, and quadratic fuel cost minimization considering the valve point effect. The DGWO is validated using the standard IEEE 30-bus test system. The obtained results showed the effectiveness and superiority of DGWO for solving the OPF problem compared with the other well-known meta-heuristic techniques

Role of dynamic contrast-enhanced and diffusion weighted MRI in evaluation of hepatocellular carcinoma after chemoembolization

Purpose: To assess the role of dynamic contrast- enhanced and diffusion-weighted (DWI) MRI in the evaluation of the response of hepatocellular carcinoma (HCC) after chemoembolization. Patient & method: 30 patients having 40 HCC lesions underwent transcatheter arterial chemoembolization (TACE). Ages ranged between 41 and 76 years. All examinations were performed using Philips 1.5 Tesla MRI (Achieva). Precontrast T1, T2, Dynamic contrast enhanced and respiratory triggered DWI MR images with (b = 50, 400, 800 mm/s). DWI MRI images and Contrast-enhanced MRI images after TACE are assessed to evaluate post treatment response. DWI was used to create ADC maps and ADC values were calculated looking for a cut off value using the ROC curve. Results: Dynamic MRI had a sensitivity of 94.1%, a specificity of 95.6%, PPV value of 94.1%, NPV of 95.6% and an overall agreement of 95% compared to 82%, 73.9%, 70%, 85% and 77.5% respectively of DWI MRI. The difference between the malignant residual and well ablated groups' ADC variables was statistically significant P value 0.009. Conclusion: Dynamic and diffusion MRI complete each other in assessment of HCC response to therapy, especially in those who cannot properly hold their breath that cause degradation of the dynamic MR quality

Role of ultrasound, color doppler, elastography and micropure imaging in differentiation between benign and malignant thyroid nodules

Purpose: To evaluate the role of ultrasound elastography, Doppler and micropure imaging in the assessment of thyroid nodules, using the pathological analysis as the reference standard. Patients and methods: A prospective study was carried on all patients referred to radio-diagnosis department at Tanta Cancer Centre between November 2015 and November 2016 for evaluation of undiagnosed thyroid nodules. All patients were examined by B-mode ultrasound, color Doppler, micropure imaging and ultrasound elastography. All thyroid nodules were subjected to fine-needle aspiration biopsy. Results: 90 patients (78 women, 12 men) with 159 incompletely diagnosed thyroid nodules. 24 nodules were malignant and 135 nodules were benign, micro calcification was detected by micropure imaging in 40 nodules (29.6%) in the benign thyroid nodules and in 20 nodules (83.3%) in the malignant thyroid nodules (sensitivity 83.3%, specificity 70.4%, and accuracy 84.9%). Color flow Doppler (type III) with marked intranodular and absent or slight perinodular blood flow, was detected in 19 malignant nodules, with sensitivity 79.2%, specificity 95.6%, and the overall accuracy rate was 88.7%. The predictivity of ultrasound elastographic score measurement has high sensitivity 87.5%, and specificity 91.1%, Strain elastography cutoff value for malignant nodules was 2.7 (Sensitivity 83.3% and specificity 91.1%). Conclusion: Elastography and micropure imaging technique are useful imaging modalities to detect the nature of thyroid nodules. In combination with Doppler and B-mode sonography, they could give a better assessment for undiagnosed thyroid nodules. Keywords: Thyroid nodules, Ultrasound, Micropure, Doppler, Elastograph