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Internet of Things and Artificial Intelligence as Enablers for Circular Economy
Get PDFThe traditional linear economy, using a take-make-dispose model is resourceintense
and comes with adverse environmental impacts. Circular economy (CE)
is regenerative and restorative by design and intention and is recommended as
the business model for efficient use of resources. Despite the push for businesses
and organisations to switch from linear to CE, there are several
barriers/challenges that need solving such as business models and the criticism
of CE projects often being small scale. Technology can be an enabler toward
scaling up CE; however, the prime challenge is to identify technologies that can
allow predicting, tracking and proactive monitoring of product's residual value,
that can potentially motivate businesses to pursue circularity decisions. In this
thesis, an Internet of Things (IoT)-enabled decision support system (DSS) for CE
business model is proposed. The aim is to effectively enable tracking, monitoring,
and analysis of products in real time with focus on residual value. The business
model is implemented using an ontological model. This model is complemented by a semantic DSS. The semantic ontological model, first of its kind, is evaluated
for technical compliance, quality of modelling and domain coverage, for final reengineering
and re-evaluations. The DSS and the ontological model is applied in
a real-world use case and demonstrate viability and applicability of the approach to businesses and sustainability via Sustainable Development Goals (SDGs)
lens. The results of the comparison of this novel model to the linear economy is
promising with the novel model proving more profitable and resource efficient.Petroleum Development Technology Fund (PTDF) Nigeri
Early diagnosis and personalised treatment focusing on synthetic data modelling: Novel visual learning approach in healthcare
Get PDFYesThe early diagnosis and personalised treatment of diseases are facilitated by machine learning. The quality of data has an impact on diagnosis because medical data are usually sparse, imbalanced, and contain irrelevant attributes, resulting in suboptimal diagnosis. To address the impacts of data challenges, improve resource allocation, and achieve better health outcomes, a novel visual learning approach is proposed. This study contributes to the visual learning approach by determining whether less or more synthetic data are required to improve the quality of a dataset, such as the number of observations and features, according to the intended personalised treatment and early diagnosis. In addition, numerous visualisation experiments are conducted, including using statistical characteristics, cumulative sums, histograms, correlation matrix, root mean square error, and principal component analysis in order to visualise both original and synthetic data to address the data challenges. Real medical datasets for cancer, heart disease, diabetes, cryotherapy and immunotherapy are selected as case studies. As a benchmark and point of classification comparison in terms of such as accuracy, sensitivity, and specificity, several models are implemented such as k-Nearest Neighbours and Random Forest. To simulate algorithm implementation and data, Generative Adversarial Network is used to create and manipulate synthetic data, whilst, Random Forest is implemented to classify the data. An amendable and adaptable system is constructed by combining Generative Adversarial Network and Random Forest models. The system model presents working steps, overview and flowchart. Experiments reveal that the majority of data-enhancement scenarios allow for the application of visual learning in the first stage of data analysis as a novel approach. To achieve meaningful adaptable synergy between appropriate quality data and optimal classification performance while maintaining statistical characteristics, visual learning provides researchers and practitioners with practical human-in-the-loop machine learning visualisation tools. Prior to implementing algorithms, the visual learning approach can be used to actualise early, and personalised diagnosis. For the immunotherapy data, the Random Forest performed best with precision, recall, f-measure, accuracy, sensitivity, and specificity of 81%, 82%, 81%, 88%, 95%, and 60%, as opposed to 91%, 96%, 93%, 93%, 96%, and 73% for synthetic data, respectively. Future studies might examine the optimal strategies to balance the quantity and quality of medical data
High pressure adsorption of hydrogen sulfide and regeneration ability of ultra-stable Y zeolite for natural gas sweetening
No full textYesAdsorbents are developing in the various separation industries; these adsorbents can use to sweeten natural gas and remove hydrogen sulfide. Many commercial adsorbents are not regenerable when exposed to hydrogen sulfide because hydrogen sulfide is highly reactive. For
removal, the main challenge when using surface adsorbent, is the dissociation adsorption of
and non-regenerability of adsorbent. In this study, ultra-stable Y (USY) zeolite, was chosen to adsorb hydrogen sulfide due to its unique physical and chemical properties. To accurately model the adsorption isotherms, experimental adsorption data were measured in high pressure up to 12 bar for hydrogen sulfide and 21 bar for carbon dioxide, methane, and nitrogen as other natural gas components. The experiments were performed at three temperatures of 283, 293 and 303 K. Toth model fitted the experimental data very well, and the capacity of hydrogen sulfide adsorption on USY at the temperature of 283 K and pressure of 12 bar is 4.47 mmol/g that is noticeable. By performing ten cycles of adsorption and regeneration of hydrogen sulfide on USY, the regenerability of the adsorbent was investigated and compared by conducting a similar test on commercial 13X adsorbent. USY is found to be completely regenerable when exposed to hydrogen sulfide. The Isosteric adsorption heat of hydrogen sulfide on the adsorbent is 18.1 kJ/mol, which indicates physical adsorption, and the order of adsorption capacity of tested compounds on USY is H2S > CO2≫CH4 > N2
Micro-nano scale pore structure and fractal dimension of ultra-high performance cementitious composites modified with nanofillers
Get PDFYesThe development of ultra-high performance cementitious composite (UHPCC) represents a significant advancement in the field of concrete science and technology, but insufficient hydration and high autogenous shrinkage relatively increase the pores inside UHPCC, in turn, affecting the macro-performance of UHPCC. This paper, initially, optimized the pore structure of UHPCC using different types and dimensions of nanofillers. Subsequently, the pore structure characteristics of nano-modified UHPCC were investigated by the mercury intrusion porosimeter method and fractal theory. Finally, the fluid permeability of nano-modified UHPCC was estimated by applying the Katz-Thompson equation. Experimental results showed that all incorporated nanofillers can refine the pore structure of UHPCC, but nanofillers with different types and dimensions have various effects on the pore structure of UHPCC. Specifically, CNTs, especially the thin-short one, can significantly reduce the porosity of UHPCC, whereas nanoparticles, especially nano-SiO2, are more conducive to refine the pore size. Among all nanofillers, nano-SiO2 has the most obvious effect on pore structure, reducing the porosity, specific pore volume and most probable pore radius of UHPCC by 31.9%, 35.1% and 40.9%, respectively. Additionally, the pore size distribution of nano-modified UHPCC ranges from 10-1nm to 105nm, and the gel pores and fine capillary pores in the range of 3-50nm account for more than 70% of the total pore content, confirming nanofillers incorporation can effectively weaken pore connectivity and induce pore distribution to concentrate at nanoscale. Fractal results indicated the provision of nanofillers reduces the structural heterogeneity of gel pores and fine capillary pores, and induces homogenization and densification of UHPCC matrix, in turn, decreasing the UHPCC fluid permeability by 15.7%-79.2%.National Science Foundation of China (51978127, 52178188 and 51908103), the China Postdoctoral Science Foundation (2022M720648 and 2022M710973) and the Fundamental Research Funds for the Central Universities (DUT21RC(3)039)
Working together: reflections on how to make public involvement in research work
Get PDFYesThe importance of involving members of the public in the development, implementation and dissemination of research is increasingly recognised. There have been calls to share examples of how this can be done, and this paper responds by reporting how professional and lay researchers collaborated on a research study about falls prevention among older patients in English acute hospitals. It focuses on how they worked together in ways that valued all contributions, as envisaged in the UK standards for public involvement for better health and social care research.
The paper is itself an example of working together, having been written by a team of lay and professional researchers. It draws on empirical evidence from evaluations they carried out about the extent to which the study took patient and public perspectives into account, as well as reflective statements they produced as co-authors, which, in turn, contributed to the end-of-project evaluation.
Lay contributors' deep involvement in the research had a positive effect on the project and the individuals involved, but there were also difficulties. Positive impacts included lay contributors focusing the project on areas that matter most to patients and their families, improving the quality and relevance of outcomes by contributing to data analysis, and feeling they were 'honouring' their personal experience of the subject of study. Negative impacts included the potential for lay people to feel overwhelmed by the challenges involved in achieving the societal or organisational changes necessary to address research issues, which can cause them to question their rationale for public involvement.
The paper concludes with practical recommendations for working together effectively in research. These cover the need to discuss the potential emotional impacts of such work with lay candidates during recruitment and induction and to support lay people with these impacts throughout projects; finding ways to address power imbalances and practical challenges; and tips on facilitating processes within lay groups, especially relational processes like the development of mutual trust.Funded by the National Institute for Health Research (NIHR) Health and Social Care Delivery Research (HSDR) Programme (Project Number NIHR129488)
Improved learning outcomes and teacher experience: A qualitative study of team-based learning in secondary schools
Get PDFYesBased on the benefits of Team-Based Learning (TBL) in higher education, our project investigated possible benefits of TBL in secondary education. We found that, despite challenges, the benefits of using TBL in secondary schools make it worth teachers’ time and effort. We conducted a year-long qualitative study with 13 teachers from Ireland, Spain and UK. While teachers found preparation time, institutional requirements, and managing student team dynamics challenging, challenges were outweighed by benefits including improved student engagement, quality of learning, skill development, and teacher job satisfaction. We recommend further TBL training for secondary-level teachers and further research into this topicERASMUS
‘It's a job to be done’. Managing polypharmacy at home: A qualitative interview study exploring the experiences of older people living with frailty
Get PDFYesIntroduction: Many older people live with both multiple long‐term conditions and
frailty; thus, they manage complex medicines regimens and are at heightened risk of
the consequences of medicines errors. Research to enhance how people manage
medicines has focused on adherence to regimens rather than on the wider skills
necessary to safely manage medicines, and the older population living with frailty
and managing multiple medicines at home has been under‐explored. This study,
therefore, examines in depth how older people with mild to moderate frailty manage
their polypharmacy regimens at home.
Methods: Between June 2021 and February 2022, 32 patients aged 65 years or
older with mild or moderate frailty and taking five or more medicines were recruited
from 10 medical practices in the North of England, United Kingdom, and the CARE
75+ research cohort. Semi‐structured interviews were conducted face to face, by
telephone or online. The interviews were recorded, transcribed verbatim and
analysed using reflexive thematic analysis.
Findings: Five themes were developed: (1) Managing many medicines is a skilled job I
didn't apply for; (2) Medicines keep me going, but what happened to my life?; (3)
Managing medicines in an unclear system; (4) Support with medicines that makes my
work easier; and (5) My medicines are familiar to me—there is nothing else I need (or
want) to know.
While navigating fragmented care, patients were expected to fit new medicines
routines into their lives and keep on top of their medicines supply. Sometimes, they felt let down by a system that created new obstacles instead of supporting their
complex daily work.
Conclusion: Frail older patients, who are at heightened risk of the impact of
medicines errors, are expected to perform complex work to safely self‐manage
multiple medicines at home. Such a workload needs to be acknowledged, and more
needs to be done to prepare people in order to avoid harm from medicines.
Patient and Public Involvement: An older person managing multiple medicines at
home was a core member of the research team. An advisory group of older patients
and family members advised the study and was involved in the first stages of data
analysis. This influenced how data were coded and themes shaped.National Institute for Health and Care Research (NIHR). Grant Number: NIHR201056. National Institute for Health and Care Research (NIHR) Yorkshire and Humber Patient Safety Translational Research Centre
Biodegradable polymer‐metal‐organic framework (MOF) composites for controlled and sustainable pesticide delivery
Get PDFYesDue to high surface area, loading capacity, and selectivity, Metal-Organic Frameworks (MOFs) have shown much promise recently for potential applications in extraction and delivery of agrochemicals for environmental remediation and sustainable release, respectively. However, application of MOFs for pesticide delivery in wider agricultural context can be restricted by their granular form. Herein, an alternative approach is studied using biodegradable polymer-MOF composites to address this limitation. The loading and release of a widely used pesticide, 2,4-dichloropheoxycetic acid (2,4-D), is studied using two MOFs, UiO-66 and UiO-66-NH2, and the 2,4-D-loaded MOFs are incorporated into biodegradable polycaprolactone composites for convenient handling and minimizing runoff. The MOFs are loaded by in-situ, and post-synthetic methods, and characterised thoroughly to ensure successful synthesis and loading of 2,4-D. The pesticide release studies are performed on the MOFs and composites in distilled water, and analysed using UV-Vis spectroscopy, demonstrating sustained-release of 2,4-D over 16 days. The loaded MOF samples show high loading capacity, with up to 45 wt% for the in-situ loaded UiO-66. Release kinetics show more sustained release of 2,4-D from UiO-66-NH2 compared to UiO-66, which can be due to supramolecular interactions between the NH2 group of UiO-66-NH2 and 2,4-D. This is further supported by computational studies.Engineering and Physical Sciences Research Council. Grant Numbers: EP/T022213, EP/W033747/1, EP/R02943
Experimental assessment of using Phase Change Lightweight Aggregates to enhance the thermal storage of geo-energy structures
No full textYesGeo-energy structures (GES) are mainly structural foundations that are used as heat exchangers to extract or dissipate heat from/to the ground, and they are progressively being adopted for providing more sustainable energy strategies in new buildings. Despite the fact that over one-third of a century has passed since the first installation of geo-energy structures in northern Europe, enhancing the thermal energy storage of those structures has not been thoroughly studied. This paper aimed to increase the thermal energy-storage of geo energy structures by incorporating phase change material–impregnated light-weight aggregates (PCM LWA'S) at the soil-structure interface. The results showed that the inclusion of 35 % PCM LWA's at the GES/soil interface extensively increased the temperature difference (inlet-outlet) for cooling and heating. It is also illustrated that the effect of PCM inclusion to enhance the thermal performance is more significant during the heating mode (PCM is cooled down) than during the cooling mode (PCM is heated up). Furthermore, the findings indicated that the use of PCM LWA's has reduced the thermal deformation of GES and has a positive impact on soil temperature and interference radius