Does gum chewing affect the timing of return of intestinal motility after elective cesarean section?

Background: The aim is to evaluate the effect of gum chewing on the return of intestinal motility after elective CS.Methods: Study period was from September 2017 to March 2018 at the Assiut Women Health University Hospital. The study was registered as a prospective cohort study (Clinicaltrial.gov   NCT03355378). Women planned for elective CS according to selection criteria randomized to two groups: Group 1: included 100 patients who received intraoperative and postoperative non-sugary gum chewing as 15 minutes every 2 hours post-operatively for 6 hours with regular care and Group 2: included 100 patients who received regular care without gum chewing.Results: No statistically significant difference regarding the baseline criteria of both groups. There was a statistically significant lower systolic and diastolic blood pressure in gum chewing group. Hospital stay of gum chewing group was 7.33±0.73 hours versus in non-gum chewing group 20.28 ± 9.92 (p=0.000). Passage of flatus of gum chewing group was 8.54±0.98 hours versus in non-gum chewing group 13.22 ± 3.75 (P= 0.000).Conclusions: Gum chewing during elective CS improves gut motility in a safe way resulting in early passage of flatus, less hospital stay, and minimal pain score less cost on hospitals

Comparison of cognitive function, socioeconomic level, and the health-related quality of life between epileptic patients with attention deficit hyperactivity disorder and without

Background Epilepsy is one of the most common neurological conditions. Attention deficit hyperactivity disorder (ADHD) in children with epilepsy proves to be very common. Both epilepsy and ADHD impair quality of life. We aimed to evaluate cognitive function, socioeconomic level, and quality of life (QOL) among children with ADHD and epilepsy. A total of 100 children were divided into 5 groups (20 children/group) as (I) epilepsy, (II) ADHD with epilepsy, (III) ADHD with EEG changes, (IV) ADHD without EEG changes, and (V) control. Children aged between 6 and 11 years were recruited for this study. Early Childhood Epilepsy Severity Scale (E-Chess), Conners’ Parent Rating Scale (CPRS), Wechsler Intelligence Scale for Children-3rd edition (WISC-III), socioeconomic scale for assessment of social burden and socioeconomic classes, and PedsQL (quality of life measure) assessed. Results Children with ADHD and epilepsy had the lowest PedsQL total scores and lower scores than other groups especially in performance IQ score. The highest percentage of low socioeconomic class (25%) was observed in the group of ADHD with epilepsy and the group of epilepsy. Conclusion ADHD with epilepsy is associated with low performance IQ, poor socioeconomic level, and quality of life. Pediatric Quality of Life Inventory scores show significant correlation with total IQ score in the group of ADHD with epilepsy

Polymorphism of growth hormone gene and its association with wool traits in Egyptian sheep breeds

Growth hormone (GH) gene has been described as a candidate gene for marker-assisted selection in different farm animals. The present study was designed to identify the polymorphism in GH gene and its association with variation of wool traits in Egyptian sheep breeds. Wool and blood samples were collected from 42 animals including two breeds (Barki and Rahmani) and one crossbred (Rahmani x Awase). Measurements of wool traits were analyzed and involved staple strength (Str), staple length (STL), fiber diameter (FD) and clean fleece yield (CFW). DNA was extracted from blood samples and a 365-bp fragment from exon V was amplified by polymerase chain reaction (PCR). Single strand conformation polymorphisim (SSCP) analysis showed two conformational patterns. The pattern I was recorded to be more frequent (83.3, 92.86 and 90%) than pattern II (16.7, 7.14 and 10%) in Barki, Rahmani and crossbred, respectively. The sequence analysis showed one single nucleotide polymorphism (C/T). The pattern I (allele T) has been found to affect CFW and FD than pattern II (allele C). Whereas, C allele was more pronounced for Str and STL. These traits are the most important parameters determining commercial values of wool that are preferred for clothing or carpets industry. The nucleotide sequences of C and T alleles were submitted to GenBank and have the accession numbers: KT250511 and KT250512, respectively. In conclusion, the present results provide evidence that there is a single nucleotide polymorphism within GH gene in Egyptian sheep breeds. This mutation was found to have some effects on wool traits. Therefore our data show interesting prospects in future selection programs for improving wool industry.Key words: Sheep, wool, growth hormone (GH) gene, polymorphism, single strand conformation polymorphism (SSCP)

Solar cells: Types, Modules, and Applications–A Review

The basic operating principle of photovoltaic (PV) devices is the conversion of solar irradiation into electricity. There are various applications of this principle in many countries such as Egypt, Nigeria and Denmark. Most of the solar PV projects are designed for street lighting, water pumping and water desalination. However, we hope about wide range of using the appropriate components and best technical procedures, standard PV projects with maximum performance output. The present systems now provide 20% to 40% only of the community's heat or lightness on annual basic needs. These include innovative and alternative ways to reduce material uses and module degradation, and opportunities to reuse and recycle PV panels at the end of their lifetime because of the installations of photovoltaic solar modules which are growing extremely very fast.   Keywords: Solar cells; renewable energy; photovoltaic; free energy; solar panel cost; solar battery

Laparoscopic ovarian drilling-plus: a one-stop management approach for PCO-associated infertility

Background: The current study aims to estimate additional values of laparoscopic intervention for diagnosis and treatment of concomitant pelvic pathologies among infertile women with clomiphene-resistant polycystic ovarian syndrome (PCOS) subjected to laparoscopic ovarian drilling (LOD) in comparison to non-PCOS infertile women subjected to diagnostic/therapeutic laparoscopy.Methods: A prospective cross sectional observational study was carried out in the Endoscopic unit of a tertiary care university hospital.  The study included 232 infertile women planned for laparoscopy were divided into a study group A (116 cases) with clomiphene-resistant PCOS and a control group B (116 cases) without PCOS. Each group was further subdivided into two subgroups according to the presence and absence of risk factors (RF) for adhesion formation. Diagnostic/operative laparoscopy was done. The main study outcome was the prevalence of any pelvic abnormalities seen during laparoscopy.Results: Both groups showed insignificant difference regarding socio-demographic history and basic data. Laparoscopy detected pelvic pathologies in 44 cases (37.9%) and 86 cases (74.1%) in both groups respectively. In group A, we diagnosed pelvic pathologies in 29 (32.6%) and 15 (55.6%) cases with and without RF respectively while in group B they were diagnosed in 76 (84.4%) and 10 (38.5%) cases with and without RF respectively. If compared to women with unexplained infertility, PCO patients without risk factors have an insignificant but higher prevalence of pelvic abnormalities. All concomitant pelvic pathologies in both groups were treated on a one-stop (see and treat) basis.Conclusions: Detection and proper management of associated pelvic pathologies at laparoscopy is a valuable additional advantage of LOD particularly in women with positive risk factors. LOD plus see and treat associated pathologies is a time saving and prompt management approach for women with PCO–associated infertility

Novel microwell-based spectrophotometric assay for determination of atorvastatin calcium in its pharmaceutical formulations

The formation of a colored charge-transfer (CT) complex between atorvastatin calcium (ATR-Ca) as a n-electron donor and 2, 3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) as a π-electron acceptor was investigated, for the first time. The spectral characteristics of the CT complex have been described, and the reaction mechanism has been proved by computational molecular modeling. The reaction was employed in the development of a novel microwell-based spectrophotometric assay for determination of ATR-Ca in its pharmaceutical formulations. The proposed assay was carried out in 96-microwell plates. The absorbance of the colored-CT complex was measured at 460 nm by microwell-plate absorbance reader. The optimum conditions of the reaction and the analytical procedures of the assay were established. Under the optimum conditions, linear relationship with good correlation coefficient (0.9995) was found between the absorbance and the concentration of ATR-Ca in the range of 10-150 μg/well. The limits of detection and quantitation were 5.3 and 15.8 μg/well, respectively. No interference was observed from the additives that are present in the pharmaceutical formulation or from the drugs that are co-formulated with ATR-Ca in its combined formulations. The assay was successfully applied to the analysis of ATR-Ca in its pharmaceutical dosage forms with good accuracy and precision. The assay described herein has great practical value in the routine analysis of ATR-Ca in quality control laboratories, as it has high throughput property, consumes minimum volume of organic solvent thus it offers the reduction in the exposures of the analysts to the toxic effects of organic solvents, and reduction in the analysis cost by 50-fold. Although the proposed assay was validated for ATR-Ca, however, the same methodology could be used for any electron-donating analyte for which a CT reaction can be performed

Intelligent Fault Diagnosis Framework for Modular Multilevel Converters in HVDC Transmission

Copyright: © 2022 by the authors. Open circuit failure mode in insulated‐gate bipolar transistors (IGBT) is one of the most common faults in modular multilevel converters (MMCs). Several techniques for MMC fault diagnosis based on threshold parameters have been proposed, but very few studies have considered artificial intelligence (AI) techniques. Using thresholds has the difficulty of selecting suitable threshold values for different operating conditions. In addition, very little attention has been paid to the importance of developing fast and accurate techniques for the real‐life application of open‐circuit failures of IGBT fault diagnosis. To achieve high classification accuracy and reduced computation time, a fault diagnosis framework with a combination of the AC‐side three‐phase current, and the upper and lower bridges’ currents of the MMCs to automatically classify health conditions of MMCs is proposed. In this framework, the principal component analysis (PCA) is used for feature extrac-tion. Then, two classification algorithms—multiclass support vector machine (SVM) based on error-correcting output codes (ECOC) and multinomial logistic regression (MLR)—are used for classifi-cation. The effectiveness of the proposed framework is validated by a two‐terminal simulation model of the MMC‐high‐voltage direct current (HVDC) transmission power system using PSCAD/EMTDC software. The simulation results demonstrate that the proposed framework is highly effective in diagnosing the health conditions of MMCs compared to recently published re-sults.National Natural Science Foundation of China, grant no. 51105291; by the Shaanxi Provincial Science and Technology Agency, nos. 2020GY124, 2019GY-125, and 2018JQ5127; Key Laboratory Project of the Department of Education of Shaanxi Province, nos. 19JS034 and 18JS045

Open-circuit Fault Detection and Classification of Modular Multilevel Converters in High Voltage Direct Current Systems (MMC-HVDC) with Long Short-Term Memory (LSTM) method

Copyright: © 2021 by the authors. Fault detection and classification are two of the challenging tasks in Modular Multilevel Converters in High Voltage Direct Current (MMC-HVDC) systems. To classify directly the raw sensor data without certain feature extraction and classifier design, a long short-term memory (LSTM) neural network is proposed and used for seven states of the MMC-HVDC transmission power system simulated by Power Systems Computer Aided Design/ Electromagnetic Transients including DC (PSCAD/EMTDC). It is observed that the LSTM method can detect faults with 100% accuracy and classify different faults as well as provide promising fault classification performance. Compared with a bidirectional LSTM (BiLSTM), the LSTM can get similar classification accuracy, requiring less training time and testing time. Compared with Convolutional Neural Networks (CNN) and AutoEncoder-based deep neural networks (AE-based DNN), the LSTM method can get better classification accuracy around the middle of the testing data proportion but it needs more training time.National Natural Science Foundation of China; Shaanxi Provincial Science and Technology Agency; Key Laboratory Project of Department of Education of Shaanxi Provinc