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Multi-cavity molecular descriptor interconnections: Enhanced protocol for prediction of serum albumin drug binding
No full textYesThe role of human serum albumin (HSA) in the transport of molecules predicates its involvement in the determination of drug distribution and metabolism. Optimization of ADME properties are analogous to HSA binding thus this is imperative to the drug discovery process. Currently, various in silico predictive tools exist to complement the drug discovery process, however, the prediction of possible ligand-binding sites on HSA has posed several challenges. Herein, we present a strong and deeper-than-surface case for the prediction of HSA-ligand binding sites using multi-cavity molecular descriptors by exploiting all experimentally available and crystallized HSA-bound drugs. Unlike previously proposed models found in literature, we established an in-depth correlation between the physicochemical properties of available crystallized HSA-bound drugs and different HSA binding site characteristics to precisely predict the binding sites of investigational molecules. Molecular descriptors such as the number of hydrogen bond donors (nHD), number of heteroatoms (nHet), topological polar surface area (TPSA), molecular weight (MW), and distribution coefficient (LogD) were correlated against HSA binding site characteristics, including hydrophobicity, hydrophilicity, enclosure, exposure, contact, site volume, and donor/acceptor ratio. Molecular descriptors nHD, TPSA, LogD, nHet, and MW were found to possess the most inherent capacities providing baseline information for the prediction of serum albumin binding site. We believe that these associations may form the bedrock for establishing a solid correlation between the physicochemical properties and Albumin binding site architecture. Information presented in this report would serve as critical in provisions of rational drug designing as well as drug delivery, bioavailability, and pharmacokinetics
Occupational therapists' perspectives of using telehealth for youth with autism amidst the COVID-19 Pandemic in the UK: A pilot qualitative study
Get PDFYesThe COVID-19 national emergency led to a surging demand for telehealth expansion within pediatric occupational therapy. Despite the growing literature on telehealth as a response to COVID-19, few studies explore the use of telehealth for children and young people with autism spectrum disorder (ASD). This pilot study aimed to understand the experiences of occupational therapists adapting to a virtual delivery service model amidst COVID-19 to support youth with ASD. The researchers used a qualitative research design. Semi-structured, video-based interviews were used to collect data. Interviews were analyzed using thematic analysis. This study included 3 UK registered occupational therapists. Four themes emerged from the data: 1. “Telehealth is Reducing Social Anxiety” 2. “Parents End Up Becoming Your Therapy Assistants” 3. “Nothing Will Replace Face to Face for Assessments” 4. “You Definitely Have to Be More Creative.” The themes report that telehealth can reduce social anxiety, increase skill transferability, and improve family involvement. Participants indicated that shorter sessions, movement-based interventions, planning and adapting to home-based resources were strategies that overcame the limitations of virtual therapy. The findings contrast with some previous research that found that telehealth may inhibit engagement and may strain the therapeutic rapport. This study supports existing literature that telehealth can enhance engagement, family involvement and generalization of skills. Findings from this study support the use of telehealth to deliver occupational therapy services for children and young people with ASD, but it is recommended that telehealth should not be a one size fits all service delivery model. Further larger-scale research is needed to confirm the study findings and to explore the family and young person’s perspectives of using telehealth
Examining the impact of resilience strategies in mitigating medicine shortages in the United Kingdom's (UK) pharmaceutical supply chain (PSC)
Get PDFYesPurpose
Medicine shortages have a detrimental impact on stakeholders in the pharmaceutical supply chain (PSC). Existing studies suggest that building resilience strategies can mitigate the effects of these shortages. As such, this research aims to examine whether resilience strategies can reduce the impact of medicine shortages in the United Kingdom's (UK) PSC.
Design/methodology/approach
A sequential mixed-methods approach that involved qualitative and quantitative research enquiry was employed in this study. The data were collected using semi-structured interviews with 23 key UK PSC actors at the qualitative stage. During the quantitative phase, 106 respondents completed the survey questionnaires. The data were analysed using partial least square-structural equation modelling (PLS-SEM).
Findings
The results revealed that reactive and proactive elements of resilience strategies helped tackle medicine shortages. Reactive strategies increased relational issues such as behavioural uncertainty, whilst proactive strategies mitigated them.
Practical implications
The findings suggest that PSC managers and decision-makers can benefit from adopting structural flexibility and proactive strategies, which are cost-effective measures to tackle medicine shortages. Also engaging in strategic alliances as a proactive strategy mitigates relational issues that may arise in a complex supply chain (SC).
Originality/value
This study is the first to provide empirical evidence of the impact of resilience strategies in mitigating medicine shortages in the UK's PSC
Introducing a new measure of energy transition: Green quality of energy mix and its impact on CO2 emissions
Get PDFYesThis paper introduces a novel measure of the energy transition, i.e., the green quality of energy mix (GREENQ) across the Organisation for Economic Co-operation and Development (OECD) countries. Then, the paper examines the impact of the GREENQ on CO2 emissions in the panel dataset of 36 OECD countries from 1970 to 2021. The explanatory variables include per capita income, institutional quality and technology. Long-run panel data estimations indicate that per capita income, institutional quality and technology increase CO2 emissions. The novel evidence is that the GREENQ is negatively related to the level of CO2 emissions. These findings are robust to employ different panel data estimation techniques. Potential policy implications are also discussed.The project was funded by the “Foreign Cultural and Educational Experts Project of the Ministry of Science and Technology of China” (Project Number: DL2022180001L)
Resource-Induced Coping Heuristics and Organizational Ambidexterity in Context of Weak Institutions and Underdeveloped Markets
No full textThe current study contributes to the understanding of the micro foundations of organizational ambidexterity from the context of small and medium-sized enterprises (SMEs) operating in weak institutions and underdeveloped markets by focusing on three issues. First, drawing from the conservation of resources theory as a theoretical lens, this study explores the relationship between owner-managers’ resource-induced coping heuristics and organizational ambidexterity. Second, it investigates the mediating mechanism of entrepreneurial bricolage in this relationship. Third, it examines the boundary effects of financial resource capability and environmental dynamism in the first and second relationships, respectively. The quantitative study adopts a cross-sectional survey design. Data collected from 273 Nigerian owner-managers in multi-sector industries was analyzed using AMOS in structural equation modelling. The results show that resource-induced coping heuristics leads to SME ambidexterity and that entrepreneurial bricolage serves as the mechanism which transforms owner-managers’ resource-induced coping heuristics into exploration and exploitation. Surprisingly, the results reveal that environmental dynamism impedes the relationship between entrepreneurial bricolage and exploration but facilitates exploitation through bricolage. This study sets new, empirically founded information about drivers of ambidexterity in the context of weak institutions and underdeveloped markets by showing that resource-induced coping heuristic serves as a coping mechanism which fosters the simultaneous pursuit of exploration and exploitation through entrepreneurial bricolage. Additionally, by revealing that, in a more dynamic environment, SMEs are less likely to pursue exploration through entrepreneurial bricolage, this study makes a novel and significant contextual contribution on the implications of environmental dynamism for organizational outcomes in weak institutions
Fundus-DeepNet: Multi-Label Deep Learning Classification System for Enhanced Detection of Multiple Ocular Diseases through Data Fusion of Fundus Images
No full textYesDetecting multiple ocular diseases in fundus images is crucial in ophthalmic diagnosis. This study introduces the Fundus-DeepNet system, an automated multi-label deep learning classification system designed to identify multiple ocular diseases by integrating feature representations from pairs of fundus images (e.g., left and right eyes). The study initiates with a comprehensive image pre-processing procedure, including circular border cropping, image resizing, contrast enhancement, noise removal, and data augmentation. Subsequently, discriminative deep feature representations are extracted using multiple deep learning blocks, namely the High-Resolution Network (HRNet) and Attention Block, which serve as feature descriptors. The SENet Block is then applied to further enhance the quality and robustness of feature representations from a pair of fundus images, ultimately consolidating them into a single feature representation. Finally, a sophisticated classification model, known as a Discriminative Restricted Boltzmann Machine (DRBM), is employed. By incorporating a Softmax layer, this DRBM is adept at generating a probability distribution that specifically identifies eight different ocular diseases. Extensive experiments were conducted on the challenging Ophthalmic Image Analysis-Ocular Disease Intelligent Recognition (OIA-ODIR) dataset, comprising diverse fundus images depicting eight different ocular diseases. The Fundus-DeepNet system demonstrated F1-scores, Kappa scores, AUC, and final scores of 88.56%, 88.92%, 99.76%, and 92.41% in the off-site test set, and 89.13%, 88.98%, 99.86%, and 92.66% in the on-site test set.In summary, the Fundus-DeepNet system exhibits outstanding proficiency in accurately detecting multiple ocular diseases, offering a promising solution for early diagnosis and treatment in ophthalmology.European Union under the REFRESH - Research Excellence for Region Sustainability and High-tech Industries project number CZ.10.03.01/00/22_003/0000048 via the Operational Program Just Transition. The Ministry of Education, Youth, and Sports of the Czech Republic - Technical University of Ostrava, Czechia under Grants SP2023/039 and SP2023/042
Beyond the Echo: Exploring Usage, Anthropomorphism and User-Smart Object Relationships in the Age of Amazon Alexa
No full textCharacterised by their unique capabilities and autonomous nature, Voice-Controlled Smart Assistants (VCSAs) have rapidly gained popularity as one of the most prominent AI-based consumer technologies of this decade. However, while poised to revolutionise the customer journey, insight into the successful adoption and usage of VCSA devices, the perception and relationships that emerge as a result of usage, and the influence of such on the use of voice-shopping is limited. This study seeks to address this issue by bringing together theories on technology adoption, anthropomorphism, and user-VCSA relationships to establish a deeper understanding of VCSA usage and the associated impact on the potential use of voice-shopping capabilities, engagement, and future usage.
Using questionnaires, personal diaries, and informal interviews, data from 14 participants was collected over an 8-week period, allowing for insight into how participants used and interacted with their VCSA device over time. The findings revealed that the adoption of VCSA devices is heavily influenced by the perceived benefits received, with continued usage regularly leading to the development of habits and positive experiences. As a result of continued and habitual usage, the findings also provide insight into the participants’ likelihood to anthropomorphise the device and the development of associated user-VCSA relationships. Finally, the findings shine light on the influence of habitual usage and user-VCSA relationships on the participants’ likelihood to use VCSA voice-shopping capabilities.
The results of this study have theoretical and practical implications, contributing to a deeper understanding of factors affecting the adoption and continued usage of VCSA devices and their influence on voice-shopping, user engagement, and consumer behaviour
Field study of local scour around bridge foundations on silty seabed under irregular tidal flow
No full textYesLocal scour induced by tidal flow is a major hazard for sea-crossing bridge foundations in coastal areas. The
irregular tidal flow and silt-muddy seabed environment generates a very complicated flow turbulence and
sediment transport. This paper, for the first time, presents the field measured scour holes around the Hangzhou
Bay Sea-Crossing Bridge (HBSB) under irregular tidal flow dominated water regions. The high-resolution seabed
topography around 19 bridge foundations in the south waterway of HBSB is measured from 2015 to 2020 by
using a multi-beam sonar system. The field measured data are analyzed to investigate the local scour characteristics under irregular tidal flows. Results indicate that under irregular tidal flows with stronger flood tide, the
local scour hole around every bridge foundation is slightly asymmetric and the scour depth downstream is larger
than that upstream. The slope angles at upstream, downstream and lateral sides of local scour hole are about 13◦
～18◦, which are much smaller than the Angle of Repose (AoR = 35◦) due to bidirectional scouring generated by
tidal flows. During 2015～2020, the maximum scour depths around all bridge foundations range between 1.2
De～2.5De (where De being the effective diameter of bridge foundation). The maximum scour depths vary
frequently with a fluctuation within 0.6De. Comparison between the field measured and predicted scour depth
using three available scour depth predication equations show that all prediction equations overestimate the scour
depth. As such, considering the discount effect of the varied tidal flow compared with steady current, an
improved maximum scour depth prediction equation is proposed to estimate the scour depth under tidal flow on
a silty seabed. Results show that the predicted scour depth using the proposed equation has a relative error of ±30%.The article includes a Corrigendum published in 2024
Advancing Indoor Air Pollution Research: A Novel Integration of AI, IoT, and Behavioural Science for Enhanced Indoor Air Quality Monitoring and Behaviour Change
No full textThis thesis addresses global concerns over air quality, focusing on Indoor Air Quality (IAQ). It presents an interdisciplinary exploration into the integration of Artificial Intelligence (AI), the Internet of Things (IoT), and Low-Cost Sensors (LCS) for air quality monitoring. The research evaluates LCS, augmented by AI and IoT, as an alternative to expensive monitoring systems, tackling challenges like sensor selection and calibration. Various AI techniques, including Random Forest and Neural Networks, are employed for calibration. The study also delves into the impact of human behaviour on IAQ, utilising the COM-B model to design digital interventions. Case studies with IoT-based devices in volunteer households showed significant IAQ improvement and increased awareness due to these interventions. The thesis further examines a digital visualisation platform's effectiveness in raising IAQ awareness, applying the Technology Acceptance Model (TAM) to understand technology adoption factors. The research underscores the potential of digital interventions in promoting better IAQ practices. It emphasises leveraging LCS-based IoT technologies, digital platforms, and citizen engagement to address IAQ challenges. The findings provide insights into AQ monitoring and improvement's technical, behavioural, and digital dimensions. This comprehensive exploration showcases how behavioural models, combined with IoT and AI, can drive behavioural change, offering valuable guidance for researchers, policymakers, and public health officials on IAQ
Biodegradation and Properties of Phosphated Polyurethanes
No full textVast quantities of plastics are produced annually, to meet the expanding global demand. The use and misuse of plastic, followed by the subsequent mismanagement of waste, has raised great environmental concerns. Despite the recognition of the problems faced the production of plastic continues to increase. This along with the resistance of most polymers to degradation highlights the requirement of further investigation into effective methods of biodegradation, as well as into the synthesis of biodegradable polymers.
Three standard polyurethanes with varying soft:hard segment ratios were synthesised and characterized via FTIR, 1H NMR and GPC. Phosphate-functionalised polyurethanes (GP-PU) with equivalent soft:hard segment ratios were also synthesised and characterised. The degradation properties of each PU and GP-PU were studied and compared, under various controlled conditions. Bacteria and fungi contributing towards the degradation of these material, were also identified, via DNA sequencing of the 16S and ITS1 rRNA regions, respectively.
The thermal and mechanical properties of PUs and their equivalent GP-PUs were also studied and compared, at each composition to determine how the addition of phosphate affected the materials final properties. Various techniques were used including, thermogravimetric analysis, differential scanning calorimetry and tensile testing. It was demonstrated how the incorporation of phosphate functional groups to polyurethanes resulted in materials with enhanced thermal and mechanical properties.
In this thesis it is demonstrated how the addition of phosphate to polyurethane, results in materials which are significantly more amenable to biodegradation whilst also enhancing their mechanical properties, when compared to their non-phosphated equivalents. Species of both bacteria and fungi were found to be greatly amplified on the film surfaces, contributing towards this enhanced biodegradation.
From 16S analysis, the two predominant species of bacteria on the film surfaces were Melioribacter roseus and Ignavibacterium album. From ITS1 analysis, the two species of fungi amplified on the film surfaces were Talaromyces rugulosus and Saccharomyces cerevisiae