Outcome of Dome-Shaped Proximal Tibial Osteotomy in Infantile Genu Varum

Background: The goals of the proximal tibial osteotomy are correcting the deformity, Hip-knee-ankle angle, and preventing the progress of the destruction of the medial compartment of the knee joint.Objectives: The aim of the work was to evaluate the outcome of children with genu varum after proximal tibial dome shaped osteotomy.Patients and Methods: These randomized clinical trials study included a total of 10 patients with 12 affected knees confirmed with persistent physiologic genu varum, attending at Orthopedic Department, Zagazig University Hospitals, Zagazig, Egypt. All cases were evaluated pre and post-operatively according to Modified Hospital for Special Surgery Knee Scoring System (HSSKS) as shown in appendix I. cases were assessed for functional improvement after surgery at 2, 4 months and detection of malunion or delayed union after 3 months. Results: The mean (±SD) pre-operative tibio-femoral angle was 21.7 (±5.6) versus 3.18 (±1.97) post-operatively, preoperative femoral condyle-tibial shaft angle (FTA) was 16.3 (± 2.8) versus 3.2 (±1.1) post-operatively and preoperative metaphyseal diaphyseal angle was 15.8 (±2.6) versus 3.6 (±1.2) post-operatively with a statistically significant difference in between (p < 0.05). The mean pre-operative HSSKS scores were 70.16±11.3 while the mean post-operative HSSKS scores were 91.4±2.1.Conclusion: It could be concluded that proximal tibial osteotomy using dome-shaped procedure to correct Infantile Genu varum deformity, has favorable treatment outcomes, does not involve any dangerous complications, and can be used as a safe and effective treatment method for the correction of infantile genu varum deformity. In the current study, angles significantly improved, most of legs got full correction and little complications occurred

Synthesis, characterization and catalytic activity of Cu(II), Co(II), Ni(II), Mn(II) and Fe(III) complexes of 4-((3-formyl-4-hydroxyphenyl)diazenyl)-N-(4-methyloxazol-2-yl) benzenesulfonamide

The sulfonamide derivative, 4-((3-formyl-4-hydroxyphenyl)diazenyl)-N-(4-methyloxazol-2-yl) benzenesulfonamide (FDMB), was synthesized and characterized. Additionally, its Cu(II), Co(II), Ni(II), Mn(II) and Fe(III) complexes were prepared and their structures were investigated by elemental analysis, thermal analysis and (IR, electronic and EPR) spectroscopy. The mode of binding indicates that the ligand binds to the metal ion through carbonyl oxygen and OH phenolic with displacement of its proton. The Co(II) complex was applied for the hydrolysis of nerve agent-like compound, bis-(p-nitrophenyl) phosphate (BNPP). The results showed a significant rate enhancement of 2.5 million fold with respect to the auto-hydrolysis of BNPP under the same conditions

Prevalence of Neospora caninum and Toxoplasma gondii Antibodies and DNA in Raw Milk of Various Ruminants in Egypt.

The prevalence of Neospora caninum and Toxoplasma gondii antibodies in raw milk samples was estimated in different ruminants and Egyptian governorates. Of 13 bulk milk samples tested by ELISA, five (38.5%) were positive for antibodies to N. caninum, and two samples were additionally positive for antibodies to T. gondii, resulting in a seroprevalence of 15.4% for both T. gondii and co-infection. In individual milk samples (n = 171) from the same bulks, antibodies to N. caninum were detected in 25.7%, to T. gondii in 14%, and 3.5% had antibodies to both parasites. A strong correlation between the OD values of the bulk samples and of the relevant individual milk samples was found for T. gondii (Pearson r = 0.9759) and moderately strong for N. caninum (Pearson r = 0.5801). Risk factor assessment for individual milk samples revealed that antibodies to T. gondii were significantly influenced by animal species, while no risk factors were detected for N. caninum antibodies. Additionally, DNA of N. caninum was detected in a bulk milk sample of cattle for the first time in Egypt, and DNA of T. gondii was found in bulk milk samples of cattle, sheep and goats. This is the first study in Egypt in which bulk milk samples of different ruminants were tested for the presence of N. caninum and T. gondii antibodies and DNA. Both individual and bulk milk samples are useful tools for monitoring antibody response to N. caninum and T. gondii infections in different ruminants in Egypt

Seroprevalence of Toxoplasma gondii and Neospora caninum in camels recently imported to Egypt from Sudan and a global systematic review.

INTRODUCTION Toxoplasma gondii and Neospora caninum are closely related intracellular protozoan parasites of medical and veterinary concern by causing abortions and systemic illness. Limited or ambiguous data on the prevalence of T. gondii and N. caninum in camels triggered us to conduct this study. METHODS Camels (n = 460) recently imported from Sudan and destined mainly for human consumption, were tested for specific antibodies against these protozoans using commercially available ELISAs. From the two only quarantine stations for camels from Sudan, 368 camels were sampled between November 2015 and March 2016 in Shalateen, Red Sea governorate, and 92 samples were collected between September 2018 and March 2021 from Abu Simbel, Aswan governorate. RESULTS & DISCUSSION Overall, seropositive rates in camels were 25.7%, 3.9% and 0.8% for T. gondii, N. caninum and mixed infection, respectively. However, marked differences were found between the two study sites and/or the two sampling periods: For T. gondii, a higher rate of infection was recorded in the Red Sea samples (31.5%, 116/368; odds ratio 20.7, 5.0-85.6; P<0.0001) than in those collected in Aswan (2.2%, 2/92). The opposite was found for N. caninum with a lower rate of infection in the Red Sea samples (0.82%, 3/368; odds ratio 23.7, 6.7-83.9; P<0.0001) than in the samples from Aswan (16.3%, 15/92). Additionally, our systematic review revealed that the overall published seroprevalence of T. gondii and N. caninum was 28.6% and 14.3% in camels worldwide, respectively. To the best of our knowledge, this study provides the first record of seroprevalence of both T. gondii and N. caninum in recently imported camels kept under quarantine conditions before delivery to other Egyptian cities and regions. In addition, our review provides inclusive data on the prevalence of T. gondii and N. caninum in camel globally. This knowledge provides basic data for the implementation of strategies and control measures against neosporosis and toxoplasmosis

Contextual Sequence-to-Point Deep Learning for Household Energy Disaggregation

This paper examines a contextual paradigm for energy disaggregation using Non-Intrusive Load Monitoring (NILM). Due to numerous issues including low sampling rates, missing data, misaligned readings, and diverse combinations of nonlinear and multi-state appliances, this problem is challenging and complex. We proposed two different deep learning models for household energy disaggregation with shared parameter learning based on Convolutional Neural Networks (CNNs) and Gated Recurrent Units (GRUs). The proposed models utilize a sliding window of the main aggregate power readings to predict the per-appliance consumption at the end point of the sequence; using the entire input sequence gives more contextual information and reduces the prediction complexity in other problem settings. We evaluated the performance using two benchmark datasets, ENERTALK and UK-DALE, under different scenarios including sampling rates, imputation methods, cross-dataset generalization, and single and multi-target settings. The results demonstrate that the proposed models show better robustness and generalization capability than the other sequence-to-point models when no consumption information is discarded in the alignment process, especially for cross-domain disaggregation

Detecting Cyber-Attacks on Wireless Mobile Networks Using Multicriterion Fuzzy Classifier with Genetic Attribute Selection

With the proliferation of wireless and mobile network infrastructures and capabilities, a wide range of exploitable vulnerabilities emerges due to the use of multivendor and multidomain cross-network services for signaling and transport of Internet- and wireless-based data. Consequently, the rates and types of cyber-attacks have grown considerably and current security countermeasures for protecting information and communication may be no longer sufficient. In this paper, we investigate a novel methodology based on multicriterion decision making and fuzzy classification that can provide a viable second-line of defense for mitigating cyber-attacks. The proposed approach has the advantage of dealing with various types and sizes of attributes related to network traffic such as basic packet headers, content, and time. To increase the effectiveness and construct optimal models, we augmented the proposed approach with a genetic attribute selection strategy. This allows efficient and simpler models which can be replicated at various network components to cooperatively detect and report malicious behaviors. Using three datasets covering a variety of network attacks, the performance enhancements due to the proposed approach are manifested in terms of detection errors and model construction times

A novel approach for face recognition using fused GMDH-based networks

This paper explores a novel approach for automatic human recognition from multi-view frontal facial images taken at different poses. The proposed computational model is based on fusion of the Group Method of Data Handling (GMDH) neural networks trained on different subsets of facial features and with different complexities. To demonstrate the effectiveness of this approach, the performance is evaluated and compared using eigen-decomposition for feature extraction and reduction with a variety of GMDH-based models. The experimental results show that high recognition rates, close to 98%, can be achieved with very low average false acceptance rates, less than 0.12%. Performance is further investigated on different feature set sizes and it is found that with smaller feature sets (as few as 8 features), the proposed GMDH-based models outperform other classifiers including those using radial-basis functions and support-vector machines. Additionally, the capability of the group method of data handling algorithm to select the most relevant features during the model construction makes it more attractive to build much simplified models of polynomial units. © 2018, Zarka Private University. All rights reserved

2nd International Symposium on Intelligent Systems Technologies and Applications

This book constitutes the thoroughly refereed proceedings of the second International Symposium on Intelligent Systems Technologies and Applications (ISTA’16), held on September 21–24, 2016 in Jaipur, India. The 80 revised papers presented were carefully reviewed and selected from 210 initial submissions and are organized in topical sections on image processing and artificial vision, computer networks and distributed systems, intelligent tools and techniques and applications using intelligent techniques