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A comprehensive survey on RF energy harvesting: applications and performance determinants
Get PDFThere has been an explosion in research focused on Internet of Things (IoT) devices in recent years, with a broad range of use cases in different domains ranging from industrial automation to business analytics. Being battery-powered, these small devices are expected to last for extended periods (i.e., in some instances up to tens of years) to ensure network longevity and data streams with the required temporal and spatial granularity. It becomes even more critical when IoT devices are installed within a harsh environment where battery replacement/charging is both costly and labour intensive. Recent developments in the energy harvesting paradigm have significantly contributed towards mitigating this critical energy issue by incorporating the renewable energy potentially available within any environment in which a sensor network is deployed. Radio Frequency (RF) energy harvesting is one of the promising approaches being investigated in the research community to address this challenge, conducted by harvesting energy from the incident radio waves from both ambient and dedicated radio sources. A limited number of studies are available covering the state of the art related to specific research topics in this space, but there is a gap in the consolidation of domain knowledge associated with the factors influencing the performance of RF power harvesting systems. Moreover, a number of topics and research challenges affecting the performance of RF harvesting systems are still unreported, which deserve special attention. To this end, this article starts by providing an overview of the different application domains of RF power harvesting outlining their performance requirements and summarizing the RF power harvesting techniques with their associated power densities. It then comprehensively surveys the available literature on the horizons that affect the performance of RF energy harvesting, taking into account the evaluation metrics, power propagation models, rectenna architectures, and MAC protocols for RF energy harvesting. Finally, it summarizes the available literature associated with RF powered networks and highlights the limitations, challenges, and future research directions by synthesizing the research efforts in the field of RF energy harvesting to progress research in this area
Assessment of the immune response of clinically infected calves to Cryptosporidium parvum infection
Get PDFCryptosporidium parvum (C. parvum) infection is one of the main causes of diarrhea in calves. The current study assessed the role of blood biomarkers (acute-phase proteins (APPs), procalcitonin, neopterin, cytokines, and oxidative stress in the pathogenesis, diagnosis, and prognosis of calves naturally infected with C. parvum. Fifty-seven calves, aged from 10 to 45 days, were detected positive for C. parvum and were allotted into the diseased group; twenty healthy calves were selected as a control group. Serum amyloid A, haptoglobin, cytokines, neopterin, procalcitonin, and stress biomarkers were tested in the diseased and healthy groups. The serum levels of APPs, cytokines, neopterin, procalcitonin, and malondialdehyde increased, whereas antioxidant levels were significantly decreased in diseased calves compared to the healthy group. Moreover, all examined biomarkers were significantly altered towards normal values in infected calves following different treatment protocols. All biomarkers examined were highly effective in discriminating between C. parvum-infected calves and healthy individuals. Furthermore, the area under the curve (AUC) showed that all tested parameters had a higher degree of prognostic accuracy in predicting the treatment response of calves naturally infected with C. parvum. Our data suggest the usefulness of the examined biomarkers in the immune pathogenesis of the C. parvum infection in calves, contributing to diagnosis and treatment efficacy
Indispensable yet invisible: a qualitative study of carer roles in infection prevention in a South Indian hospital
Get PDFObjectives We investigated the roles of patient carers in infection-related care on surgical wards in a South Indian hospital, from the perspective of healthcare workers (HCW), patients, and their carers.
Methods Ethnographic study including ward-round observations (138 hours) and face-to-face interviews (44 HCW, 6 patients/carers). Data (field notes, interview transcripts) were coded in NVivo 12 and thematically analysed. Data collection and analysis were iterative, recursive and continued until thematic saturation.
Results Carers have important, unrecognised roles. In the study site, institutional expectations are formalised in policies demanding a carer to always accompany inpatients. Such intense presence embeds families in the patient care environment, as demonstrated by their high engagement in direct personal (bathing patients) and clinical care (wound care). Carers actively participate in discussions on patient progress with HCWs, including therapeutic options. There is a misalignment between how carers are positioned by the organisation (through policy mandates, institutional practices, and HCWs expectations), and the role that they play in practice, resulting in their role, though indispensable, remaining unrecognised.
Conclusion Current models of patient and carer involvement in infection prevention and control (IPC) are poorly aligned with socio-cultural and contextual aspects of care. Culture- sensitive IPC policies which embrace the roles that carers play are urgently needed
Black is the night: masking and unmasking, social science research, and what a song might bring
Get PDFAn important aspect of commissioned research is how we negotiate the distance that remains unbridged between a researcher and her participants. Arthur Frank, referencing Emmanuel Levinas asks, “Do I recognise what the other is having to hold together, to carry on at all, and his or her fear of life coming apart.” He then asks us to consider what role, or what part “the other” casts us in, in the unfolding drama of their life. I like the language Frank and Levinas use as they move into the realm of performance, where we can be cast in a role, and perhaps adopt a mask to work through these types of issues
The Cuban Music Room
No full textThe Cuban Music Room is a thought-provoking documentary film in which a series of educators and practitioners innovate audiovisually in order to find a faithful way of capturing sound in a way that is comparable to the live production and listening experience. The film is a highly collaborative piece motivated by the challenges faced to show and teach music in context, featuring musicians and educators from Cuba and the UK who are interested in Cuban and related music. It takes us to a recording space in Matanzas, where the performance and recording process are embedded within the socio-cultural context. We see musicians and academics getting ready, performing, recording and reflecting about the process, as well as audience members interacting with the film, through multiple screens that emerge from the flat split screen of this streamed version of the video. The Cuban Music Room does not only offer insight into Cuban music, it also suggests creative ways of addressing how the static dimensions of music, both written and visual text, can showcase and critically analyse sound and music
An efficient information retrieval system using evolutionary algorithms
Get PDFWhen it comes to web search, information retrieval (IR) represents a critical technique as web pages have been increasingly growing. However, web users face major problems; unrelated user query retrieved documents (i.e., low precision), a lack of relevant document retrieval (i.e., low recall), acceptable retrieval time, and minimum storage space. This paper proposed a novel advanced document-indexing method (ADIM) with an integrated evolutionary algorithm. The proposed IRS includes three main stages; the first stage (i.e., the advanced documents indexing method) is preprocessing, which consists of two steps: dataset documents reading and advanced documents indexing method (ADIM), resulting in a set of two tables. The second stage is the query searching algorithm to produce a set of words or keywords and the related documents retrieving. The third stage (i.e., the searching algorithm) consists of two steps. The modified genetic algorithm (MGA) proposed new fitness functions using a cross-point operator with dynamic length chromosomes with the adaptive function of the culture algorithm (CA). The proposed system ranks the most relevant documents to the user query by adding a simple parameter (∝) to the fitness function to guarantee the convergence solution, retrieving the most relevant user’s document by integrating MGA with the CA algorithm to achieve the best accuracy. This system was simulated using a free dataset called WebKb containing Worldwide Webpages of computer science departments at multiple universities. The dataset is composed of 8280 HTML-programed semi-structured documents. Experimental results and evaluation measurements showed 100% average precision with 98.5236% average recall for 50 test queries, while the average response time was 00.46.74.78 milliseconds with 18.8 MB memory space for document indexing. The proposed work outperforms all the literature, comparatively, representing a remarkable leap in the studied field
Applying a new systematic fuzzy FMEA technique for risk management in light steel frame systems
Get PDFLight Steel Frame (LSF) system is mainly used for construction of short and intermediate-height buildings in developed countries whereas considerable heed is not given to it in developing countries. Unfamiliarity to LSF risks is one of the main reasons for this averseness so risk management can remedy this challenge and develop application of the LSF. Hence, this paper investigates the risk management of LSF system considering design, construction and operation phase. Three main steps entailing risk identification, assessment and responding using fuzzy Failure Mode and Effect Analysis (FMEA) technique are suggested for risk management implementation and for validation of responses, a novel index with respect to weighted combination of project quality, time and cost are calculated. The methodology is demonstrated on a pilot study in a developing country. By using interview, 29 significant risks are extracted in design, construction and operation and then evaluated by proposed fuzzy method. Results showed that the share of the risks in these steps are 21%, 31% and 48% respectively. The results revealed that the risks in the construction and operation phases are higher than those in the design phase. The results also show that involving safety as a project object in the risk management process could eventuate acceptable results
Teaching Here and There; Episode 14, 'Hyflex' with Dr. Brian Beatty
No full textThis is episode 14, featuring our renowned and distinguished guest, Dr. Brian Beatty. He is Associate Professor of Instructional Technologies in the Department of Equity, Leadership Studies and Instructional Technologies at San Francisco State University. At SFSU, Brian pioneered the development and evaluation of the HyFlex course design model for blended learning environments, implementing a “student-directed-hybrid” approach to better support student learning.
In this in-depth conversation, Dom Pates, James Rutherford and Dr. Ivan Sikora, heard from Brian about his early experiences and development of hybrid teaching as well as his views on the future of teaching in a live hybrid or Hyflex mode.
We do hope you enjoy listening to this episode
Sound-Based Cough Detection System using Convolutional Neural Network.
Get PDFSound recording and processing techniques can be used in designing diagnostic solutions for a variety of medical conditions related to the respiratory system. In this spectrum, cough monitoring for chronic or seasonal conditions is a significant medical practice. In this paper, a precise cough identification and monitoring system is presented. The system is
utilising a convolutional neural network as a feature extraction
algorithm and classification system. Including several functions of
loading the audio data into the system and converting it into a set
of spectrograms, as well as the pre-segmentation stage function,
the model retains its relatively low-complexity, which allows
accelerating the learning process, also enhanced using dropout.
Due to limited audio data available, the dataset dimension was
established at 600 samples, split into two equal-numbered groups
– 300 samples of “cough” samples, and 300 of “non-cough”
samples. The validation accuracy (thus the percentage of samples
labelled correctly by the system during the validation process)
yielded over 84%, suggesting that this can be a successful cough
detection method for future medical applications and devices, such
as potential respiratory system condition diagnostic tool
Equipping students to identify misinformation: science, health and epistemic insight
Get PDFFocusing on health education as its context, this article considers the question of how to equip students with strategies to identify and resist misinformation. In doing so, it confronts a key problem for health services nationally and globally, which is the problem of entrenched compartmentalisation. The relationship between these two key issues is explored with reference to a workshop on health misinformation. The workshop was designed through co-creation with researchers in education and was trialled with foundation-level students studying biomedical science and pharmacology. Feedback from participating students included that the workshop provided valuable aspects of interdisciplinary learning that they felt were ‘missing’ from their education to date. The article concludes by discussing the opportunity for science education in schools and colleges to address and potentially head off problems that persist beyond school and that are recognised to need urgent attention in health discourse