373 research outputs found
Secondary prevention of heart disease - knowledge among cardiologists and Omega-3 (Omega-3) fatty acid prescribing behaviors in Karachi, Pakistan
Background: The use of omega-3 fatty acids is a currently proven strategy for secondary prevention of heart disease. The prescription practices for this important nutraceutical is not currently known. It is imperative to assess the knowledge of cardiologists regarding the benefits of omega-3 fatty acids and to determine the frequency of its prescription. The aim of the study was to determine the practices and associations of dietary fish prescribing among cardiologists of Karachi and to assess their knowledge of fish oil supplementation and attitudes toward dietary practices. Methods: A cross sectional survey was conducted during the period of January to March, 2008. A self report questionnaire was employed. All practicing cardiologists of Karachi were included in the study. Multiple logistic regression analysis was performed to determine the independent factors associated with high fish prescribers. Results: The sample comprised of a total of 163 cardiologists practicing in Karachi, Pakistan. Most (73.6%) of the cardiologists fell in the age range of 28 - 45 years and were male (90.8%). High fish prescribers only comprised 36.2% of the respondents. After adjusting for age and gender, multivariate analysis revealed that only the variable of knowledge about fish oil\u27s role in reducing sudden cardiac death was independently associated with high fish prescribers OR = 6.38 [95% CI 2.58-15.78]. Conclusion: The level of knowledge about the benefits of omega-3 fatty acids is high and the cardiologists harbor a favorable attitude towards dispensing dietary fish advice. However, the prescription practices are less than optimal and not concordant with recommendations of organisations such as the American Heart Association and National Heart Foundation of Australia. The knowledge of prevention of sudden cardiac death in CVD Patients has been identified as an important predictor of high fish prescription. This particular life-saving property of omega-3 fatty acids should be the focus of any implemented educational strategy targeted to improve secondary CVD prevention via omega-3 fatty acid supplementation
Motion estimation of an aircraft model using computer vision
Dynamic wind tunnel tests are used to investigate the flight dynamics of aircraft. Currently contact measurement systems are used which increase friction and require on-board instrumentation. A vision-based method is proposed in this paper. The method uses a sequential process of Harris corner detection, Kanade-Lucas-Tomasi tracking, and Euler angles to identify the Euler angles from a pair of cameras, one with a top-view and the other with a side-view. The method is tested by simulating a 3D CAD model for a single degree of freedom rotational motion. The results have been quantified through numerical analysis and the proposed method is analysed analytically. The developed method is effective when integrated with another method of instrumentation such as an IMU
Non-intrusive classification of gas-liquid flow regimes in an S-shaped pipeline-riser using doppler ultrasonic sensor and deep neural networks
The problem of predicting the regime of a two-phase flow is considered. An approach is proposed that classifies the flow regime using Deep Neural Networks (DNNs) operating on features extracted from Doppler ultrasonic signals of the flow using the Fast Fourier Transform (FFT) is proposed. The features extracted are categorised into one of the four flow regime classes: the annular, churn, slug, and bubbly flow regimes. The scheme was tested on signals from an experimental facility. To increase the number of samples without losing key classification information, this paper proposes a Twin-window Feature Extraction (TFE) technique. To further distinguish the performance of the proposed approach, the classifier was compared to four conventional machine learning classifiers: namely, the AdaBoost classifier, bagging classifier, extra trees classifier, and decision tree classifier. Using the TFE features, the DNNs classifier achieved a higher recognition accuracy of 99.01% and greater robustness for the overfitting challenge, thereby showing the superiority of the DNNs in flow regime classification when compared to the four conventional machine-learning classifiers, which had classification accuracies of 55.35%, 86.21%, 82.41%, and 80.03%, respectively. This approach demonstrates the application of DNNs for flow regime classification in chemical and petroleum engineering fields, using a clamp-on Doppler ultrasonic sensor. This appears to be the first known successful attempt to identify gas-liquid flow regimes in an S-shaped riser using Continuous Wave Doppler Ultrasound (CWDU) and DNN
Development of gas-liquid flow regimes identification using a noninvasive ultrasonic sensor, belt-shape features, and convolutional neural network in an S-shaped riser
The problem of classifying gas-liquid two-phase flow regimes from ultrasonic signals is considered. A new method, belt-shaped features (BSFs), is proposed for performing feature extraction on the preprocessed data. A convolutional neural network (CNN/ConvNet)-based classifier is then applied to categorize into one of the four flow regimes: 1) annular; 2) churn; 3) slug; or 4) bubbly. The proposed ConvNet classifier includes multiple stages of convolution and pooling layers, which both decrease the dimension and learn the classification features. Using experimental data collected from an industrial-scale multiphase flow facility, the proposed ConvNet classifier achieved 97.40%, 94.57%, and 94.94% accuracy, respectively, for the training set, testing set, and validation set. These results demonstrate the applicability of the BSF features and the ConvNet classifier for flow regime classification in industrial applications
Systematic analysis of Plasmodium myosins reveals differential expression, localisation, and function in invasive and proliferative parasite stages
The myosin superfamily comprises of actin‐dependent eukaryotic molecular motors important in a variety of cellular functions. Although well studied in many systems, knowledge of their functions in Plasmodium, the causative agent of malaria, is restricted. Previously, six myosins were identified in this genus, including three Class XIV myosins found only in Apicomplexa and some Ciliates. The well characterized MyoA is a Class XIV myosin essential for gliding motility and invasion. Here, we characterize all other Plasmodium myosins throughout the parasite life cycle and show that they have very diverse patterns of expression and cellular location. MyoB and MyoE, the other two Class XIV myosins, are expressed in all invasive stages, with apical and basal locations, respectively. Gene deletion revealed that MyoE is involved in sporozoite traversal, MyoF and MyoK are likely essential in the asexual blood stages, and MyoJ and MyoB are not essential. Both MyoB and its essential light chain (MCL‐B) are localised at the apical end of ookinetes but expressed at completely different time points. This work provides a better understanding of the role of actomyosin motors in Apicomplexan parasites, particularly in the motile and invasive stages of Plasmodium during sexual and asexual development within the mosquito
Gas-liquid flow regimes identification using non-intrusive Doppler ultrasonic sensor and convolutional recurrent neural networks in an S-shaped riser
The problem of gas-liquid (two-phase) flow regime identification in an S-shaped riser using an ultrasonic sensor and convolutional recurrent neural networks (CRNN) is addressed. This research systematically evaluates three different schemes with four CRNN-based classifiers over fourteen experiments. Four metrics are used as the evaluation criteria: categorical accuracy, categorical cross-entropy, mean square error (MSE), and computation graph complexity. Compared with existing results, a compatible performance is achieved while considerably reducing the model complexity. The testing and validation accuracies were 98.13% and 98.06%, while the complexity decreased by 98.4% (only 117,702 parameters). The proposed approach is i) accurate, low complexity, and non-intrusive and hence suitable for industry, and ii) could provide a benchmark for flow regime identification
Systematic review and meta-analysis of clinical outcomes after management of posterior cruciate ligament tibial avulsion fractures
BACKGROUND: There is no consensus regarding the management of posterior cruciate ligament (PCL) avulsion fractures and the expected outcomes after treatment.
PURPOSE: To systematically review clinical outcomes and complications after management of tibial-sided avulsion fractures of the PCL.
STUDY DESIGN: Systematic review; Level of evidence, 4.
METHODS: A literature search of Scopus, PubMed, Medline, and the Cochrane Central Register for Controlled Trials was performed in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Included were studies with evidence levels 1 to 4 that reported clinical outcomes after treatment of PCL tibial-sided avulsion fractures in humans. The quality of the included studies was performed using the Methodological Index for Non-Randomized Studies (MINORS) criteria. A meta-analysis was performed for patient-reported outcome measures using random-effects modeling with 95% CIs.
RESULTS: A total of 58 studies published between 1999 and 2022 were identified. The mean MINORS score was 9.90 ± 4.12, indicating overall low-quality evidence with high risk of bias. The studies comprised 1440 patients (mean age, 32.59 ± 5.69 years; 75.2% males) with a mean follow-up of 26.9 ± 19.6 months (range, 5.3-126 months). Most patients were treated with open surgery (63.6%), followed by arthroscopic surgery (29.7%) and nonoperative treatment (6.7%). All patients reported significant posttreatment improvement in both subjective and objective outcomes (
CONCLUSION: Although nonoperative and surgical management of PCL tibial avulsion fractures resulted in high rates of fracture union and improvement in functional outcome scores and a low incidence of complications, nonoperative treatment yielded a high side-to-side posterior displacement (\u3e4 mm) with a lower rate of fracture union compared to surgical treatment
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