Evaluation of the Students' Learning Experience and Competency Gain with YACRS

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Evolutionary Neural Network Modeling for Energy Prediction of Cloud Data Centers

Accurate forecasts of data center energy consumptions can help eliminate risks caused by underprovisioning or waste caused by over-provisioning. However, due to nonlinearity and complexity, energy prediction remains a challenge. An added layer of complexity further comes from dynamically changing workloads. There is a lack of physical principle based clear-box models, and existing black-box based methods such neural networks are restrictive. In this paper, we develop an evolutionary neural network as a structurally optimal black-box model to forecast the energy consumption of a dynamic cloud data center. In particular, the approach to evolving an optimal network is developed from several novel mechanisms of a genetic algorithm, such as a structurally-inclusive matrix encoding and species parallelism that help maintain an overall increasing fitness to overcome slow convergence whilst preventing premature dominance. The model is trained using part of the data obtained from a set of MapReduce jobs on a 120-core Hadoop cluster and is then validated against unseen data. The results, both in terms of prediction speed and accuracy, suggest that this evolutionary neural network approach to cloud data center forecast is highly promising

Factors affecting customer intention to use online food delivery services before and during the COVID-19 pandemic

With the emerging popularity of online food delivery (OFD) services, this research examined predictors affecting customer intention to use OFD services amid the Coronavirus disease (COVID-19) pandemic. Specifically, Study 1 examined the moderating effect of the pandemic on the relationship between six predictors (perceived usefulness, perceived ease of use, price saving benefit, time saving benefit, food safety risk perception, and trust) and OFD usage intention, and Study 2 extended the model by adding customer perceptions of COVID-19 (perceived severity and vulnerability) during the pandemic. Study 1 showed that all of the predictors except food safety risk perception significantly affected OFD usage intention, but no moderation effect of COVID-19 was found. In Study 2, while perceived severity and vulnerability had no significant impact on OFD usage intention, the altered effects of socio-demographic variables during the COVID-19 pandemic were found. Theoretical and managerial implications are provided

Evolutionary Neural Network Based Energy Consumption Forecast for Cloud Computing

The success of Hadoop, an open-source framework for massively parallel and distributed computing, is expected to drive energy consumption of cloud data centers to new highs as service providers continue to add new infrastructure, services and capabilities to meet the market demands. While current research on data center airflow management, HVAC (Heating, Ventilation and Air Conditioning) system design, workload distribution and optimization, and energy efficient computing hardware and software are all contributing to improved energy efficiency, energy forecast in cloud computing remains a challenge. This paper reports an evolutionary computation based modeling and forecasting approach to this problem. In particular, an evolutionary neural network is developed and structurally optimized to forecast the energy load of a cloud data center. The results, both in terms of forecasting speed and accuracy, suggest that the evolutionary neural network approach to energy consumption forecasting for cloud computing is highly promising

A Public Health Issue: Dietary Supplements Promoted for Brain Health and Cognitive Performance

© Cindy Crawford, et al. 2020; Published by Mary Ann Liebert, Inc. 2020. Background: Dietary supplements targeting brain health have quickly emerged in the marketplace as cognitive performance becomes an important public health issue. While manufacturers are required to report the exact ingredients and formulations listed on the Supplement Facts labels of products, many reports have indicated such labels are not always truthful, and the content of some products is inconsistent with the ingredients listed on the Supplement Facts label. Objectives: To identify dietary supplement products and ingredients marketed for brain health and cognitive performance and perform analyses of select products to verify whether purported claims are truthful and product labels accurate. Design: A scoping review was performed to identify products and ingredients. Products were selected for content analysis, investigated for scientific-sounding claims made, and assessed using an educational tool for potential red flags when reading Supplement Facts labels. Results: Twelve products were selected from the 650 products being marketed for brain health and queried about by Service Members. Eight (67%) had at least one ingredient listed on the Supplement Facts label not detected through analysis. Compounds not reported on the label were detected in 10 (83%) products. Scientific-sounding claims made are not supported by science and red flags are presented. Conclusions: There are dietary supplements targeting brain health being marketed to consumers that should be considered adulterated and misbranded. Advertisements and product labels may be deceiving and could put the public at risk. Education is required so that the public can recognize red flags while the U.S. Food and Drug Administration works to modernize the current regulations for dietary supplements

Evaluation of Student and Staff Perceptions on L&T Models Across Multiple Disciplines

Moving towards Education 4.0, there has been a gradual shift in learning and teaching (L&T) practices worldwide towards active and deep learning (Gardiner, 2015). With technological advancements, different models of learning and teaching utilising digital mediums have evolved, alongside with frameworks to support transitions into enhanced blended learning (Adekola, Dale, & Gardiner, 2017). It was proposed that the students’ learning needs and expectations must be considered in the L&T pedagogy. In Ithaca S+R and the Univer¬sity System of Maryland, parallel comparisons of traditional versus blended courses were conducted (Griffiths, Chingos, Mulhern, & Spies, 2014). In this study, students on the blended courses performed slightly better or as well as those on the traditional courses but enjoyed the course less. At the University of Glasgow Singapore, L&T with different modes of blended instruction was explored. Four courses in Computing Science, Nursing, Mechatronics and Civil Engineering, which were hosted on different learning management systems, FutureLearn, Moodle and xSiTe, were considered. Across these courses, varying lesson plans and proportion of digital versus Face-to-face (F2F) interactions were provided. Lesson plans ranged from supplementary learning with videos to active and blended learning. Two surveys were developed to evaluate the staffs’ and students’ experiences. These included MCQs with a Likert-scale, as well as open ended questions. In this study, quantitative data was imported into Excel for visualisation, while qualitative data was subjected to categorisation and analysis (Braun & Clarke, 2006). Results were collated from at least fifty respondents in each course. The evaluation study for the students was developed on the following areas: (1)Accessibility; (2)Acceptance Levels; (3)Learner’s Gain; (4)Learner’s Experience; (5)Learner’s Perception; (6)Viewing Duration; (7)Repeated Viewing; (8)Useful to Learning; (9)Higher Level Learning; and (10)Acceptance levels on proportion of Videos versus F2F interactions. Similar questions were posed to lecturers. Some of the key findings are as follows: (i) All four lecturers believe that the videos helped to raise the level of classroom discussion and channelled F2F consultation time to enhance the L&T gain for students. (ii) Most learners used a laptop for video viewing. This is closely followed by the smartphone, especially for Nursing. (iii) More than 93% of the learners believe that videos are helpful in their learning. (iv) Concept reinforcement was ranked to be most important approach for successful learning outcomes. Students also appreciate foundational materials and content to evoke active learning and critical thinking. (v) Over 78% of the students felt that they had to repeat the viewing of videos to grasp the concepts. (vi) Across all disciplines, more than 88% of the students felt that videos are useful to learning. Above 79% felt that they are learning at a higher level. (vii) Above 81% of the students are comfortable to engage in blended learning and felt that the optimal proportion of F2F consultation versus video time would be between 40% to 60%. In conclusion, it is evident that students are generally comfortable to engage in blended learning, if a good balance of digital and F2F interaction is provided. Students enjoy learning at their own pace and time. Many of the students felt that the digital content enabled them to review their learning and reinforce their understanding. Improvement in summative assessment scores is also demonstrated, where blended learning is offered to students. This project has provided the necessary guidance needed to develop successful courses for active and blended learning and demonstrates L&T examples with different pedagogical approaches. The results will be studied for future course development and lesson planning across all joint SIT-Glasgow degree programmes

Dosage Compensation of the X Chromosomes in Bovine Germline, Early Embryos, and Somatic Tissues

Dosage compensation of the mammalian X chromosome (X) was proposed by Susumu Ohno as a mechanism wherein the inactivation of one X in females would lead to doubling the expression of the other. This would resolve the dosage imbalance between eutherian females (XX) versus male (XY) and between a single active X versus autosome pairs (A). Expression ratio of X- and A-linked genes has been relatively well studied in humans and mice, despite controversial results over the existence of upregulation of X-linked genes. Here we report the first comprehensive test of Ohno’s hypothesis in bovine preattachment embryos, germline, and somatic tissues. Overall an incomplete dosage compensation (0.5 \u3c X:A \u3c 1) of expressed genes and an excess X dosage compensation (X:A \u3e 1) of ubiquitously expressed “dosage-sensitive” genes were seen. No significant differences in X:A ratios were observed between bovine female and male somatic tissues, further supporting Ohno’s hypothesis. Interestingly, preimplantation embryos manifested a unique pattern of X dosage compensation dynamics. Specifically, X dosage decreased after fertilization, indicating that the sperm brings in an inactive X to the matured oocyte. Subsequently, the activation of the bovine embryonic genome enhanced expression of X-linked genes and increased the X dosage. As a result, an excess compensation was exhibited from the 8-cell stage to the compact morula stage. The X dosage peaked at the 16-cell stage and stabilized after the blastocyst stage. Together, our findings confirm Ohno’s hypothesis of X dosage compensation in the bovine and extend it by showing incomplete and over-compensation for expressed and “dosage-sensitive” genes, respectively

A qualitative study of the views of patients with long-term conditions on family doctors in Hong Kong

<b>Background</b> Primary care based management of long-term conditions (LTCs) is high on the international healthcare agenda, including the Asia-Pacific region. Hong Kong has a 'mixed economy' healthcare system with both public and private sectors with a range of types of primary care doctors. Recent Hong Kong Government policy aims to enhance the management of LTCs in primary care possibly based on a 'family doctor' model. Patients' views on this are not well documented and the aim of the present study was to explore the views of patients with LTCs on family doctors in Hong Kong.<p></p> <b>Methods</b> The views of patients (with a variety of LTCs) on family doctors in Hong Kong were explored. Two groups of participants were interviewed; a) those who considered themselves as having a family doctor, b) those who considered themselves as not having a family doctor (either with a regular primary care doctor but not a family doctor or with no regular primary care doctor). In-depth individual semi-structured interviews were carried out with 28 participants (10 with a family doctor, 10 with a regular doctor, and 8 with no regular doctor) and analysed using the constant comparative method.<p></p> <b>Results</b> Participants who did not have a family doctor were familiar with the concept but regarded it as a 'luxury item' for the rich within the private healthcare system. Those with a regular family doctor (all private) regarded having one as important to their and their family's health. Participants in both groups felt that as well as the more usual family medicine specialist or general practitioner, traditional Chinese medicine practitioners also had the potential to be family doctors. However most participants attended the public healthcare system for management of their LTCs whether they had a family doctor or not. Cost, perceived need, quality, trust, and choice were all barriers to the use of family doctors for the management of their LTCs.<p></p> <b>Conclusions</b> Important barriers to the adoption of a 'family doctor' model of management of LTCs exist in Hong Kong. Effective policy implementation seems unlikely unless these complex barriers are addressed