Two-dimensional (2-D) spectra of the streamwise velocity component, measured at friction Reynolds numbers ranging from 2400 to 26000, are used to refine a model for the logarithmic region of turbulent boundary layers. Here, we focus on the attached eddy model (AEM). The conventional AEM assumes the boundary layer to be populated with hierarchies of self-similar wall-attached ($Type\,A$) eddies alone. While $Type\,A$ eddies represent the dominant energetic large-scale motions at high Reynolds numbers, the scales that are not represented by such eddies are observed to carry a significant proportion of the total kinetic energy. Therefore, in the present study, we propose an extended AEM that incorporates two additional representative eddies. These eddies, named $Type\,C_A$ and $Type\,SS$, represent the self-similar but wall-incoherent low-Reynolds number features, and the non-self-similar wall-coherent superstructures, respectively. The extended AEM is shown to better predict a greater range of energetic length scales and capture the low- and high-Reynolds number scaling trends in the 2-D spectra of all three velocity components. A discussion on spectral self-similarity and the associated $k^{-1}$ scaling law is also presented., Comment: 19 pages, 12 figures
Chandran D. Ravi, Kumar M. Muthu, Muruganantham S., Thiyagarajan V., Ashoksri S., and Sibindharan S.
Subjects
energy management, model predictive control, optimization, electrical vehicle, photovoltaic, Environmental sciences, GE1-350
Abstract
Battery energy storage systems (BESS) with an energy management system (EMS) were suggested in this research that consists of a grid-connected photovoltaic (PV) charging station (CS) equipped with battery energy storage. The primary aim of this energy management system was to regulate the amount of energy sent to the electric vehicle (EV) while taking into account the cost and carbon dioxide emissions caused in grid connection. Consequently, our research offered a two-stage optimization process with multiple objectives to lessen the financial and ecological footprint of the charging station. An energy schedule was generated in the first optimization stage by considering factor of grid CO2 emissions on an hourly basis, the PV forecast, the power cost with the BESS initial state of charge (SoC). The maximum power that the grid was allowed to deliver the EV was the same as the output from this first stage. The second optimization step employed, model predictive control (MPC) to regulate the flow of energy among BESS, the PV, and the grid. An operational Photo Voltaic/BESS charging station used to validate the proposed EMS. The new EMS was then used to evaluate the charging station’s efficiency in this research for one month of data, taking three main aspects into consideration: environmental, economic, and energy. The optimization results suggest that the new energy profile ensures a 36% drop in emissions and a 33% drop in energy cost.
Chandran, D., primary, Zampiron, A., additional, Rouhi, A., additional, Fu, M.K., additional, Wine, D., additional, Holloway, B., additional, Smits, A.J., additional, and Marusic, I., additional
Chandran, D., Inada, N., Hather, G., Kleindt, C. K, and Wildermuth, M. C
Subjects
BRII recipient: Wildermuth (hybrid)
Abstract
To elucidate host processes and components required for the sustained growth and reproduction of the obligate biotrophic fungus Golovinomyces orontii on Arabidopsis thaliana, laser microdissection was used to isolate cells at the site of infection at 5 days postinfection for downstream global Arabidopsis expression profiling. Site-specific profiling increased sensitivity dramatically, allowing us to identify specific host processes, process components, and their putative regulators hidden in previous whole-leaf global expression analyses. For example, 67 transcription factors exhibited altered expression at the powdery mildew (PM) infection site, with subsets of these playing known or inferred roles in photosynthesis, cold/dehydration responses, defense, auxin signaling, and the cell cycle. Using integrated informatics analyses, we constructed putative regulatory networks for a subset of these processes and provided strong support for host cell cycle modulation at the PM infection site. Further experimentation revealed induced host endoreduplication occurred exclusively at the infection site and led us to identify MYB3R4 as a transcriptional regulator of this process. Induced endoreduplication was abrogated in myb3r4 mutants, and G. orontii growth and reproduction were reduced. This suggests that, by increasing gene copy number, localized endoreduplication serves as a mechanism to meet the enhanced metabolic demands imposed by the fungus, which acquires all its nutrients from the plant host.
Lakshmanan, B., primary, Chandran, D., additional, Thampi, D. S. T. S., additional, Karunakaran, S., additional, Abraham, D., additional, Lathikakumari, A. N. M., additional, Santhosh, K., additional, and Joseph, J., additional
Knowledge sharing is a significant component of success in knowledge management. In Saudi Arabia, knowledge management is often lacking when it comes to knowledge sharing adoption, especially between academic staff. This research aims to investigate various factors of knowledge sharing adoption for eLearning communities in Saudi Arabia and to examine the effect of culture as a moderating role on the relationships between these factors and academics’ attitude. Therefore, a framework is aimed at sharing knowledge within the eLearning communities is developed. Data has been collected from public universities in Saudi Arabia. Partial Least Square approach has been applied to analyse the data. The results show individual factors (such as openness in communication, interpersonal trust) and technology acceptance factors (perceived usefulness and perceived ease of use) significantly influence knowledge sharing attitude, while the relationship between people self-motivation and knowledge sharing attitude is insignificant. Subjective norm and attitude significantly impact behavioral intention toward knowledge sharing adoption in Saudi universities’ eLearning communities.
Phung, VD, Hawryszkiewycz, I, Chandran, D, and Ha, BM
Abstract
This study aims to examine the influence of environmental and personal factors on knowledge-sharing behaviour (KSB) and whether more leads to superior innovative work behaviour (IWB) at tertiary level in Vietnam. Our case is Hanoi University (HANU), one of the Leading Public Universities in Vietnam. This study applies the structural equation modelling (SEM) to investigate the research model based on social cognitive theory. Based on a survey of 320 academic staff at HANU, the results show that two environmental factors (subjective norm, trust) and three personal factors (knowledge self-efficacy, enjoyment in helping others, and reciprocity) significantly influence KSB. The results also indicate that employee willingness to share knowledge enable the organisation to promote IWB. It is hoped that academic staff and university leaders from other countries may find the case study useful for deeper understanding of the effects of social influences, personal perceptions and KSB on IBW in the future.
The article describes the case of a 65-year-old female with bleeding superficial lower limb varicosities and was referred to a vascular unit for definitive treatment. Topics discussed include finding on clinical examination, the patient's diagnosis of varicosities secondary to severe tricuspid regurgitation (TR), and effectiveness of sclerotherapy to chemically ablate a relatively short segment of the vein to manage the local symptoms/complications.
Technology revolution in recent years has increased the demand for the provision of e-learning. However, academic staff lack the knowledge-sharing attitude in e-learning communities. The aim of this research is to investigate the various factors of knowledge-sharing adoption for e-learning communities in Saudi Arabia. Therefore, a framework aimed at sharing knowledge within the e-learning communities is developed. Data has been collected from public universities in Saudi Arabia. Partial Least Square approach has been applied to analyse the data. The results shows knowledge-sharing individual factors (such as openness in communication, interpersonal trust), technology acceptance factors (perceived usefulness and perceived ease of use) significantly influence knowledge-sharing attitude while the relationship between people self-motivation and knowledge-sharing attitude is insignificant. Among other factors, subjective norm and attitude significantly impact behavioural intention toward knowledgesharing adoption in Saudi universities' e-learning communities.
The importance of entrepreneurship has been increasingly acknowledged as a source of growth, and national economic development. Recently, women entrepreneurship has been a topic of concern and interest for scholars and researchers. Also, it has been a considerable matter for public policies and government strategies. There are many entrepreneurship initiatives that have been made by the government of Saudi Arabia to enhance contributions of women to the workforce and economic sector, as their role has been non-existent for a long period of time. However, women involvement in these initiatives is nascent with a limited entrepreneurship rate. This study focuses on identifying social factors that have influenced women entrepreneurship. Saudi women to become entrepreneurs from within the context of technology in the literature of entrepreneurship have not existed. Therefore, the present study aims to fill that gap of knowledge and contribute substantially to understand technology-based entrepreneurship within the context of Saudi women.
Knowledge sharing is a significant component of success in knowledge management. In most organisations, knowledge management is often lacking when it comes to knowledge sharing adoption, especially between academic staffs who work in Saudi universities. This paper investigates factors affecting knowledge-sharing adoption among academics in Saudi e-learning communities. A model that will affect the process of knowledge sharing within the e-learning community is proposed. Hypotheses have been developed. Data has been collected in Saudi public universities. Partial Least Square approach has been applied to analyse the data. The findings provide key factors affecting knowledge-sharing adoption among academic staff.