19684 research outputs found
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Response to comment on “Efficacy and safety of GLP-1 receptor agonists in the management of obstructive sleep apnea in individuals without diabetes:A systematic review and meta-analysis of randomized, placebo-controlled trials”
No full textPrescriber knowledge, behaviour and attitudes regarding antibiotic use and antibiotic resistance in Oman
No full textBackground: Antimicrobial resistance threatens patients, healthcare systems, and the world’s economy. Antimicrobial stewardship programs use evidence-based strategies to monitor and assess antibiotic use. This study aimed to identify prescribers’ knowledge, attitudes, and behavior regarding antibiotic use and antibiotic resistance in Oman. Research design and methods: A cross-sectional study was conducted using a questionnaire that was adapted from the European Centre for Disease Prevention and Control instruments. The survey was distributed among prescribers in Oman’s Ministry of Health. Results: The survey included a total of 371 prescribers. Most respondents were specialists, and 73% worked in hospitals. Antibiotics’ effectiveness against viruses, needless use, and adverse effects were accurately answered by over 95% of prescribers. Eighty-four percent of prescribers realized the connection between their prescribing of antibiotics and the spread of antibiotic-resistant bacteria. Approximately 80% agreed that they address antibiotic resistance and consider it when treating patients. Around 70% of prescribers knew of the Oman national action plan to combat antibiotic resistance. Sixty-six percent of prescribers wanted information regarding antibiotic resistance, 49% about antibiotic use, and 40% about antibiotic prescriptions and medical problems. Conclusion: The findings highlight the need for interventions to inform prescriber knowledge and behavior, improve antibiotic prescribing practices, and combat the spread of antimicrobial resistance.</p
Overview of intelligent CMM guidance technology
No full textWith the development of machinery industry and the increasing level of manufacturing intelligence, the quantity of measured parts is more and more, and the precision requirement is higher and higher, the three-coordinate measuring machine (CMM) has a higher level of intelligence requirements. Firstly, this paper introduces the measuring principle of the intelligent CMM and its guiding technology, which can determine the position of the parts to be measured on the CMM workbench and save the labor cost, then, the research progress of guidance technology is summarized from the aspects of the types, advantages and disadvantages of guidance technology. Finally, the future research focus and development direction of guidance technology are prospected. This technology has high research space and value in the research of part measurement scheme, and it is also the development direction in the future.</p
An Efficient Method for Complex Digitally Coded Antenna Design Based on Evolutionary Computation and Machine Learning Techniques
No full textDigitally coded antennas, also called pixelized or fragmented antennas, show high potential for improving performance and size via unconventional structures. However, the bottleneck is the resolution that can be handled. When the resolution is more than a few hundred pixels, optimization quality and efficiency become severe challenges. Therefore, a new method, called digitally coded antenna-oriented surrogate model-assisted evolutionary algorithm (DC-SADEA), is presented in this paper. The key innovations include: (1) the introduction of an ensemble learning-based surrogate modeling method for mapping the digitally coded antenna design variables to performances, and (2) a bespoke surrogate model-assisted global optimization framework and genetic algorithm operators for digitally coded antennas. An ultra-wideband antenna (about 1900 pixels) and the feeding part of a 5G outdoor base station antenna (about 1500 pixels) are used to demonstrate DC-SADEA. Measurement results demonstrate the effectiveness and efficiency of DC-SADEA
A Four-Port Separated Transceiver Antenna with Ultra-Small Frequency Ratio Based on Collocation of Magnetic and Electric Dipoles
No full textIn this communication, a novel four-port separated transceiver antenna with ultra-small frequency ratio for base stations is proposed. The antenna is realized by collocating two orthogonally crossed slots and two dipole arrays. We first discuss the operating mechanism of the collocated antenna, i.e., a collocated couple of an electric dipole and a magnetic dipole has inherent property of isolation. Then, a prototype with an ultra-small frequency ratio is designed to verify this concept and illustrate the design method. Artificial magnetic conductors (AMC) reflector and electromagnetic band gap (EBG) structure is combined with crossed slots to realize the magnetic dipoles with broadside radiation patterns and suppression of surface wave. AMC reflector is also integrated with the electric dipole arrays to reduce the profile and enhance the broadside gains. The proposed antenna operates in 1.71-1.78 GHz frequency band by the crossed slots and in 2.11-2.18 GHz frequency band by the dipoles, representing AWS (Advanced Wireless Service) band. The frequency ratio is only 1.23, and the couplings are lower than -15 dB in the operating band without any decoupling network. The proposed design concept and method give a competitive design solution for separated transceiver antennas in base stations
A Comprehensive Framework for Empowering Women in Disaster Risk Governance in Sri Lanka
No full textThis study was conducted to develop a comprehensive framework for empowering women who work in disaster risk governance in Sri Lanka. Women’s empowerment in disaster risk governance has been identified as a strategy to reduce women’s vulnerability to disasters and strengthen the disaster risk governance system towards building a resilient society. The study was conducted within the Sri Lankan disaster preparedness system because of the high disaster profile and the lower level of women’s empowerment in the decision-making system. A case study strategy was employed for data collection. Three highly disaster-prone districts were selected and we conducted 26 semi-structured case study interviews. In addition, 14 expert interviews were conducted for better triangulating the results. Thematic analysis and cognitive mapping were adopted for data analysis and identifying strategies. Based on the study findings, a comprehensive framework was developed with four intervention mechanisms: individual, community, organizational, and legislative. Each group of interventions was divided into primary and secondary actions based on their priorities. The validated framework will guide policymakers and practitioners in supporting women’s empowerment in governance with the ultimate objective of enhancing societal resilience
Robotic arm operated automatic area scanning phase measuring deflectometry calibration method
Get PDFPhase measuring deflectometry (PMD) is a key measurement technology for specular surfaces form measurement. With the rapid advancements in the processing and manufacturing of specular workpieces, increasing demands are being placed on the compactness, portability, and flexibility of PMD systems. In most industrial applications, the target surface often exceeds the single field of view of the measurement setup, necessitating multi-view measurements or stitching strategies to obtain complete surface data. Robotic positioning-assisted offers an efficient alternative to traditional fiducial marker-based methods by aligning multiple sub-surfaces within a unified coordinate system. In this letter, a calibration method for a robotic arm operated automatic area scanning PMD technology is proposed. The accuracy of the proposed method is verified through experiments by measuring a ring calibration mirror target. Results demonstrate that the proposed calibration approach enables effective calibration of a robotic arm near optical coaxial PMD. This calibration method lays a certain foundation for expanding the measurement range and flexibility of in-situ measurement of PMD systems.</p
Does the entrepreneurship learning approach influence self-efficacy? The role of students’ entrepreneurial competence and satisfaction
No full textThis study examined the influence of an entrepreneurship education learning approach on students’ self-efficacy, with a specific focus on the mediating roles played by entrepreneurial competence and satisfaction. Informed by a conceptual framework drawn from pertinent literature, data were collected through purposive sampling from a diverse cohort of students within technical universities. Employing the AMOS structural equation modelling (SEM) method, the analysis revealed a statistically significant positive relationship between the entrepreneurship learning approach and self-efficacy without mediating variables. However, the study observed no significant direct relationship in the presence of these mediating factors. This suggests that entrepreneurial competence and satisfaction fully mediated the impact of the learning approach on self-efficacy. It is important to note that the study’s findings are contextually bound to technical universities within a less developed economy, cautioning against generalising them to traditional universities. Nonetheless, the study underscored the pivotal role of entrepreneurship education, self-competence, and student satisfaction in bolstering students’ self-efficacy, serving as a potent catalyst for fostering entrepreneurial intentions. Consequently, the study advocated for integrating entrepreneurship learning approaches in Technical and Vocational Education and Training (TVET) institutions.</p
Hybrid computational fluid dynamics-machine learning optimization of Darrieus wind turbines:Aerodynamic improvement and noise reduction through wake and vortex interactions
No full textThis research uniquely explores the effects of wake interactions between adjacent Darrieus wind turbines on their aerodynamic performance and noise emissions, a critical consideration for optimizing wind farm design and operation in proximity to populated areas. Additionally, it examines the vortex interactions between rotor blades and analyzes the dynamic stall phenomenon, offering valuable insights into the unsteady aerodynamic behavior. By utilizing Large-Eddy Simulation, the study analyzes complex turbulence patterns and rotor interactions, thereby deepening the understanding of their aerodynamic and aeroacoustic effects. A multiobjective evolutionary algorithm integrates machine learning with computational fluid dynamics (CFD) to improve rotor designs for maximum power efficiency and reduced noise, considering wake interactions. The study assesses the impact of physical and geometric parameters on rotor performance, creating a database via Design of Experiments to replace time-intensive CFD model with an Artificial Neural Network for performance predictions. The nondominated Sorting Genetic Algorithm II refines aerodynamic and aeroacoustic attributes, with optimal design parameters identified using the linear programing technique for multidimensional analysis of preference (LINMAP). The LINMAP-optimized rotor outperforms the Point O rotor in aerodynamic and aeroacoustic performance. Its wider blade spacing enhances airflow and torque coefficient (C T), while the Point O rotor suffers from increased vortex interactions. In the downwind region, the LINMAP rotor maintains positive C T values, whereas the Point O experiences negative torque. Furthermore, the LINMAP design produces stronger low-frequency noise, while the Point O rotor exhibits higher sound pressure levels above 100 Hz.</p
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