Nurses' Performance for Patient Undergoing Bariatric Surgery

Context: Bariatric surgery is currently considered the most effective treatment option for morbid obesity; it results in more significant improvement in weight loss outcomes and obesity-related co-morbidities when compared with non-surgical interventions. The performance of bariatric nurses is very relevant for the quality and outcome of surgery.Aim: The study aimed to assess nurses' performance for a patient undergoing bariatric surgery. Methods: A descriptive exploratory design was followed to achieve the aim of this study. The study was conducted at surgical units at Ain Shams University hospital Cairo-Egypt. A purposive sample of 30 nurses recruited in this study worked in bariatric surgery units at Ain Shams University hospital. Tools of data collection were structured self-administered knowledge assessment questionnaire and evaluation practice checklist used to collect data of this study. Results: This study showed that 73.3% of studied nurses had inadequate knowledge, and 70.0% had poor practice regarding managing the patient undergoing bariatric surgery. Furthermore, there was a statistically significant correlation between total knowledge and total practice of the studied nurses.Conclusion: The current study concluded that more than two-thirds of the studied nurses had a reduced level of knowledge and practice. The study emphasized implementing an educational training program to improve nurses' performance regarding caring for bariatric surgery patients

COMBUSTION CHARACTERISTICS AND EMISSION OF A DI DIESEL ENGINE UTILIZING NEW INDUCTION MANIFOLD DESIGNS AND RUNNING ON ALTERNATIVE FUEL BLENDS

The demands for increasing the swirl in the combustion chamber and for decreasing the exhaust emissions on diesel engines have increased rapidly over the past few years. Consequently, the researchers’ attention has been attracted significantly for innovating and testing a new design for the induction manifold that can match these demands. In this project, some possible alternative designs for the normal induction manifold are presented. The design of these new manifolds is inspired from the previous researches and studies about automobiles inlet manifolds. The test for the new manifolds involves swirl number calculations as well as a detailed performance and emission experimental test on the engine. The test also considers taking the readings for the exhaust gases (HC, CO, and ) and the smoke intensity using advanced measurement sensitive devices .Furthermore, this study aims to be more advanced by tracking out the pressure corresponding to each crank shaft angle by using a GW-Instek digital storage oscilloscope. As to make this work more beneficial, the performance of the engine is also diagnosed using alternative fuels such as GTL ( Gas to Liquid ) fuel and using biofuels ( Waste cooking oil & Corn oil ) in a blended form with diesel fuel . The results for any used alternative fuel or fuel blend in this experiment is compared with the result of diesel fuel in order to track any enhancement in engine performance or emission. It was found that the use of the 1D ( where D is the manifold inner diameter) new manifold can minimize the pressure variation with the crank angle position, the in-cylinder peak pressure and the particulate emission by a considerable amount due to the enhanced air-fuel mixing caused by the swirl motion generated when using this newly shaped manifold designs. The use of GTL fuel has significantly improved the engine performance and lower its emission due to its high cetane number and low Sulfur and Aromatics content. However, the use of the new fuel blends was found to be effective in some criteria such as lowering the PM and NO emission rate due to its high oxygen content

Effect of Positioning on Oxygenation and Hemodynamics among Patients on Mechanical Ventilation

Context: The routine practice of positioning is a vital procedure in critical care units, especially when prophylaxis is the aim. For many years, nurses have recognized that positioning prevents skin breakdown, mobilizes secretions, and provides comfort without identifying the impact of different positioning strategies on pulmonary gas exchange and ventilator weaning outcomes.Aim: The current study was conducted to assess the effect of positioning on oxygenation and hemodynamics among patients on mechanical ventilation. Methods: This study was conducted in the medical intensive care unit at El-Demerdash hospital, affiliated to Ain-Shams University. A descriptive exploratory study design was utilized in this study. A purposive sample of 93 patients was recruited in the present study. A structured interview questionnaire and patient assessment record were employed to collect data related to this study.Results: The results reveal that 39.8% of the studied patients’ age was between 45-<65, 30.1% had chronic obstructive pulmonary disease. Oxygenation significantly decreases in the supine position at p 0.003 and increases in the semi-recumbent position at p 0.020. Heart rate is significantly increased in semi-recumbent position at p<0.005. Systolic and diastolic blood pressure significantly decreased in semi-recumbent positions at p<0.010 and p=0.021, respectively, at T30, T60, and T120. Conclusion: Regarding oxygenation and hemodynamics, the results of this study concluded that the best oxygenation was in semi-recumbent position T120. Regarding hemodynamics, heart rate is significantly increased in the left lateral and semi-recumbent positions. Systolic and diastolic blood pressure were significantly affected by positioning. The time of changing position should be reviewed to be compatible with the most effective position for mechanically ventilated patients considering the patient oxygenation and hemodynamic states

EXPERIMENTAL MEASUREMENTS AND TRANSIENT 3D SIMULATIONS OF TURBULENT PREMIXED FLAMES OF GAS-TO-LIQUIDS (GTL) FUEL IN A FAN-STIRRED COMBUSTION BOMB

The rapid fluctuation in oil prices and the increased demand for alternative fuels to replace conventional fuels are challenging contemporary issues. One such alternative fuel that has gained significant interest recently is the Gas-to-Liquids (GTL) fuel, which is in the stage of replacing conventional diesel. However, detailed combustion characteristic investigations are required before using this alternative fuel broadly in engines. Therefore, the present dissertation is dedicated to experimentally investigate GTL (and its 50/50 by volume blend with diesel) turbulent flame speeds (St) under a wide range of thermodynamics and turbulence operating conditions using a cylindrical fan-stirred combustion bomb. Turbulent premixed GTL flame is centrally ignited in an 81.7L cylindrical combustion bomb under atmospheric pressure at an initial temperature of 463K near Homogeneous and Isotropic Turbulence (HIT) conditions. The experiments are conducted under a wide range of equivalence ratios (Ф) between 0.7 to 1.3 and turbulence intensities (u`) that vary between 0.5m/s and 3.0m/s at an integral length scale, Lt=20mm. The turbulent flame speed of the outwardly propagating GTL flame is measured using a pressure transducer, and the flame propagation is visualized by high-speed imaging. To extend and verify the experimental findings, Zimont Turbulent Flame Speed Closure (Zimont TFC) numerical model is adapted and implemented into ANSYS Fluent through a Reynolds Averaged Navier-Stokes (RANS) approach to study the influence of turbulence on GTL premixed combustion. The results showed that: (i) rich diesel and lean GTL fuels are characterized by faster flame development and pressure rise rate (dp/dt) and thus, higher turbulent flame speeds; (ii) at the same elapsed time, turbulent Reynolds numbers (ReT) and Damkohler numbers (Da) are higher for stoichiometric GTL fuel compared to diesel and 50/50 diesel-GTL blend, which indicates that the flame propagates towards the vessel’s wall at a faster rate, and the chemistry has dominated turbulence in a shorter time, and (iii) at low turbulence intensity level (u`=0.5m/s), the flame morphology is defined by a wrinkled flamelet regime in Borghi diagram. However, at moderate and high turbulence levels (u`=1.5m/s and u`=3.0m/s, respectively), the corrugated flamelets regime defines the flame structure

Provenance-enabled Packet Path Tracing in the RPL-based Internet of Things

The interconnection of resource-constrained and globally accessible things with untrusted and unreliable Internet make them vulnerable to attacks including data forging, false data injection, and packet drop that affects applications with critical decision-making processes. For data trustworthiness, reliance on provenance is considered to be an effective mechanism that tracks both data acquisition and data transmission. However, provenance management for sensor networks introduces several challenges, such as low energy, bandwidth consumption, and efficient storage. This paper attempts to identify packet drop (either maliciously or due to network disruptions) and detect faulty or misbehaving nodes in the Routing Protocol for Low-Power and Lossy Networks (RPL) by following a bi-fold provenance-enabled packed path tracing (PPPT) approach. Firstly, a system-level ordered-provenance information encapsulates the data generating nodes and the forwarding nodes in the data packet. Secondly, to closely monitor the dropped packets, a node-level provenance in the form of the packet sequence number is enclosed as a routing entry in the routing table of each participating node. Lossless in nature, both approaches conserve the provenance size satisfying processing and storage requirements of IoT devices. Finally, we evaluate the efficacy of the proposed scheme with respect to provenance size, provenance generation time, and energy consumption.Comment: 14 pages, 18 Figure

Exploring Teachers’ Perceptions of the Barriers to Teaching STEM in High Schools in Qatar

Understanding teachers’ attitudes and perceptions of STEM teaching is a key pathway to enhance effective STEM teaching. Inarguably, teachers are the cornerstone of educational quality and play a central role in students’ academic performance. Specifically, the pedagogical strategies teachers employ and their effective use in the classroom are strong determinants of students’ enrollment or retention in STEM fields of study and eventual careers. This study sought to explore the experiences of high school STEM teachers in Qatar, focusing on the pedagogical approaches they utilize and the challenges they encounter, with the aim of delving into how these approaches and barriers affect the teaching of STEM in the country’s high schools. The study’s design is observational, with data collected using a survey of 299 secondary high school STEM teachers (11th and 12th grades). To attain the goal of this study, we examined the barriers perceived to impede engagement in effective STEM teaching from high school teachers’ perspective. The study’s findings pointed to the influence of student- and school-related factors in shaping STEM teaching. Significant differences were detected based on teachers’ gender, grade level of teaching, age group, and university education. Logistic regressions revealed that teachers’ demographic attributes, including age group and university education, affect their likelihood to use STEM pedagogies in class. This likelihood was significantly affected by student-related barriers and the learning resources/materials employed in classrooms. These findings postulate critical evidence in directing the development of successful STEM learning practices within Qatar’s high schools.The project was funded by Qatar University (Reference: QUCG-SESRI-20/21-1)

A new framework for electricity price forecasting via multi-head self-attention and CNN-based techniques in the competitive electricity market

Due to recent technical improvements, the smart grid has become a feasible platform for electricity market participants to successfully regulate their bidding process based on demand-side management (DSM) perspectives. At this level, practical design, implementation, and assessment of numerous demand response mechanisms and robust short-term price forecasting development in day-ahead transactions are all critical. The accuracy and effectiveness of the day-ahead price forecasting process are crucial concerns in a deregulated market. In this market, the reason for low accuracy is the limitation of electricity generation compared to the electricity demand variations. Hence, this study proposes a suitable technique for forecasting electricity prices using a multi-head self-attention and Convolutional Neural networks (CNN) based approach. Further, this study develops a feature selection technique using mutual information (MI) and neural networks (NN) to choose suitable input variable subsets significantly affecting electricity price predictions simultaneously. The combination of MI and NN reduces the number of input features used in the model, thereby decreasing the computational complexity of the NN. The actual data sets from the Ontario electricity market in 2020 are acquired to verify the simulation results. Finally, the simulation results proved the efficiency of the proposed method by demonstrating increased accuracy by attaining the lowest average value for MAPE and RMSE with a value of 1.75% and 0.0085, respectively, and compared to results obtained by recent computational intelligence approaches. By attaining accurate electricity price results, the significance of this study can be summed up as aiding the electricity industry's operators in administering effective energy management, efficient resource allocation, and informed decision-making.© 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).fi=vertaisarvioitu|en=peerReviewed