10 research outputs found

    Pattern of Congenital Heart Diseases in Paediatric Age Group

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    Background: To determine the pattern of differenttypes of congenital heart diseases, in paediatric agegroup.Methods: In this observational cross sectionalstudy cases of congenital heart defects (CHD) wereincluded, through simple random samplingirrespective of age and gender. Every patient’s dataon echocardiographic report clearly indicating hisCHD type along with age and gender was recorded.Variables of study i.e. type of CHDs, age, and genderwith relative frequencies were presented separatelygraphically.Results: Out of 298 diagnosed patients of CHD 156were males and 142 were females. Isolatedventricular septal defect found to be the mostcommon anomaly (32.6%). In combination atrialseptal defect and ventricular defect were found to bemost common with 5.4% burden rate. Out of 298patients Acyanotic CHDs were 67.1% while CyanoticCHDs were found to be 32.9%.Conclusion: Acyanotic CHDs were found to bedominant over Cyanotic CHDs with relativepercentages of 67.1% and 32.9% respectivel

    Alleviation of Boron Stress through Plant Derived Smoke Extracts in Sorghum bicolor

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    Boron is an essential micronutrient necessary for plant growth at optimum concentration. However, at high concentrations boron affects plant growth and is toxic to cells. Aqueous extract of plant-derived smoke has been used as a growth regulator for the last two decades to improve seed germination and seedling vigor. It has been established that plant-derived smoke possesses some compounds that act like plant growth hormones. The present research was the first comprehensive attempt to investigate the alleviation of boron stress with plant-derived smoke aqueous extract on Sorghum (Sorghum bicolor) seed. Smoke extracts of five plants, i.e. Cymbopogon jwarancusa, Eucalyptus camaldulensis, Peganum harmala, Datura alba and Melia azedarach each with six dilutions (Concentrated, 1:100, 1:200, 1:300, 1:400 and 1:500) were used. While boron solutions at concentrations of 5, 10, 15, 20 and 25 ppm were used for stress. Among the dilutions of smoke, 1:500 of E. camaldulensis significantly increased germination percentage, root and shoot length, number of secondary roots and fresh weight of root and shoot while, boron stress reduced growth of Sorghum. It was observed that combined effect of boron solution and E. camaldulensis smoke extract overcome inhibition and significantly improved plant growth. Present research work investigated that the smoke solution has the potential to alleviate boron toxicity by reducing the uptake of boron by maintaining integrity of plant cell wall. The present investigation suggested that plant derived smoke has the potential to alleviate boron stress and can be used to overcome yield losses caused by boron stress to plants

    Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

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    Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

    Enhanced Machine-Learning Techniques for Medium-Term and Short-Term Electric-Load Forecasting in Smart Grids

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    Nowadays, electric load forecasting through a data analytic approach has become one of the most active and emerging research areas. It provides future consumption patterns of electric load. Since there are large fluctuations in both electricity production and use, it is a difficult task to achieve a balance between electric load and demand. By analyzing past electric consumption records to estimate the upcoming electricity load, the issue of fluctuating behavior can be resolved. In this study, a framework for feature selection, extraction, and regression is put forward to carry out the electric load prediction. The feature selection phase uses a combination of extreme gradient boosting (XGB) and random forest (RF) to determine the significance of each feature. Redundant features in the feature extraction approach are removed by applying recursive feature elimination (RFE). We propose an enhanced support vector machine (ESVM) and an enhanced convolutional neural network (ECNN) for the regression component. Hyperparameters of both the proposed approaches are set using the random search (RS) technique. To illustrate the effectiveness of our proposed strategies, a comparison is also performed between the state-of-the-art approaches and our proposed techniques. In addition, we perform statistical analyses to prove the significance of our proposed approaches. Simulation findings illustrate that our proposed approaches ECNN and ESVM achieve higher accuracies of 98.83% and 98.7%, respectively

    Getting Smarter about Smart Cities: Improving Data Security and Privacy through Compliance

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    Smart cities assure the masses a higher quality of life through digital interconnectivity, leading to increased efficiency and accessibility in cities. In addition, a huge amount of data is being exchanged through smart devices, networks, cloud infrastructure, big data analysis and Internet of Things (IoT) applications in the various private and public sectors, such as critical infrastructures, financial sectors, healthcare, and Small and Medium Enterprises (SMEs). However, these sectors require maintaining certain security mechanisms to ensure the confidentiality and integrity of personal and critical information. However, unfortunately, organizations fail to maintain their security posture in terms of security mechanisms and controls, which leads to data breach incidents either intentionally or inadvertently due to the vulnerabilities in their information management systems that either malicious insiders or attackers exploit. In this paper, we highlight the importance of data breaches and issues related to information leakage incidents. In particular, the impact of data breaching incidents and the reasons contributing to such incidents affect the citizens’ well-being. In addition, this paper also discusses various preventive measures such as security mechanisms, laws, standards, procedures, and best practices, including follow-up mitigation strategies

    Effect of Silver Nanoparticles on Biofilm Formation and EPS Production of Multidrug-Resistant Klebsiella pneumoniae

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    Antibiotic resistance against present antibiotics is rising at an alarming rate with need for discovery of advanced methods to treat infections caused by resistant pathogens. Silver nanoparticles are known to exhibit satisfactory antibacterial and antibiofilm activity against different pathogens. In the present study, the AgNPs were synthesized chemically and characterized by UV-Visible spectroscopy, scanning electron microscopy, and X-ray diffraction. Antibacterial activity against MDR K. pneumoniae strains was evaluated by agar diffusion and broth microdilution assay. Cellular protein leakage was determined by the Bradford assay. The effect of AgNPs on production on extracellular polymeric substances was evaluated. Biofilm formation was assessed by tube method qualitatively and quantitatively by the microtiter plate assay. The cytotoxic potential of AgNPs on HeLa cell lines was also determined. AgNPs exhibited an MIC of 62.5 and 125 μg/ml, while their MBC is 250 and 500 μg/ml. The production of extracellular polymeric substance decreased after AgNP treatment while cellular protein leakage increased due to higher rates of cellular membrane disruption by AgNPs. The percentage biofilm inhibition was evaluated to be 64% for K. pneumoniae strain MF953600 and 86% for MF953599 at AgNP concentration of 100 μg/ml. AgNPs were evaluated to be minimally cytotoxic and safe at concentrations of 15-120 μg/ml. The data evaluated by this study provided evidence of AgNPs being safe antibacterial and antibiofilm compounds against MDR K. pneumoniae
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