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Dietary Assessment Tools and Metabolic Syndrome: Is It Time to Change the Focus?
No full textYesMetabolic syndrome (MS) is associated with a range of chronic diseases, for which lifestyle interventions are considered the cornerstone of treatment. Dietary interventions have primarily focused on weight reduction, usually via energy restricted diets. While this strategy can improve insulin sensitivity and other health markers, weight loss alone is not always effective in addressing all risk factors associated with MS. Previous studies have identified diet quality as a key factor in reducing the risk of MS independent of weight loss. Additionally, supporting evidence for the use of novel strategies such as carbohydrate restriction and modifying the frequency and timing of meals is growing. It is well established that dietary assessment tools capable of identifying dietary patterns known to increase the risk of MS are essential for the development of personalised, targeted diet and lifestyle advice. The American Heart Association (AHA) recently evaluated the latest in a variety of assessment tools, recommending three that demonstrate the highest evidence-based and clinical relevance. However, such tools may not assess and thus identify all dietary and eating patterns associated with MS development and treatment, especially those which are new and emerging. This paper offers a review of current dietary assessment tools recommended for use by the AHA to assess dietary and eating patterns associated with MS development. We discuss how these recommendations align with recent and novel evidence on the benefits of restricting ultra-processed food and refined carbohydrates and modifying timing and frequency of meals. Finally, we provide recommendations for future redevelopment of these tools to be deployed in health care settings
Effect of solid-state shear milled natural rubber particle size on the processing and dynamic vulcanization of recycled waste into thermoplastic vulcanizate
No full textYesNatural rubber (NR) and crosslinked polyethylene (XLPE) waste streams were devulcanized by solid state shear milling (S3M), producing a fine powder that may be more easily reprocessed. Understanding devulcanization and the nature of decrosslinked thermoset materials is of utmost importance for turning these waste steams into functional products. It was found that the devulcanized powders contained significant concentrations of radicals, which may be active in the subsequent revulcanization process. The produced devulcanized powders were converted into recyclable thermoplastic vulcanizates (TPVs) by twin screw extrusion. Reprocessing of these powders into value-added products is an important step in recycling and the use of extrusion allows for high throughput and industrial viability. Herein, we demonstrate that the optimal conditions for reprocessing are dependent upon the particle size of the devulcanized powder. Furthermore, dynamic vulcanization is affected by the nature of these recyclate powders. The successfully prepared TPVs showed similar properties to virgin materials, with a high elongation to failure. Therefore, the conversion of waste rubber into the rubber phase of a TPV shows significant promise in moving towards sustainable products, providing the revulcanization step can be well controlled.EPSRC and NSFC for their funding of this work through the Joint UK-China Low Carbon Manufacturing Grant, Grant number EP/S018573/1
Development and validation of the Psychological Food Involvement Scale (PFIS)
No full textYesFood Involvement reflects the bond between consumer and food, and serves as a means of expression, identity and social recognition. Yet no existing scales are able to assess the complex psychological nature of Food Involvement. To fill this gap, this study developed and validated a Psychological Food Involvement Scale (PFIS). Data were collected by an online self-report questionnaire, involving 476 Italians aged 20-72 years (M = 48.13, SD = 13.18). The structure and psychometric properties of PFIS were examined through an exploratory and a confirmatory factor analysis, and construct validity was assessed by correlating it with Food Involvement Scale, Food Variety Seeking Scale and the General Health Interest Scale. As a behavioural indicator of validity, food and drink consumption was assessed using the Dietary Habits and Nutrition Beliefs Questionnaire. Factor analysis indicated that the PFIS comprised 19 items grouped in four stable dimensions: Emotional Balance; Self-Realization; Social Affirmation; Social Bonding. People more psychologically involved in food were more interested in healthy eating and more likely to vary their diet. The PFIS discriminated between dietary patterns. Higher PFIS scores were associated with frequent consumption of meat/fish and wholegrains/legumes. Frequent intake of meat/fish and snacks was associated with Social Bonding and meat/fish with Emotional Balance. The PFIS also explained consumption of vegetable drinks and lactose-free milk indicating the symbolic value ascribed to them related to self-expression, acceptance by others, and emotions. This implies potential for the PFIS for use in research to understand food choice and promote healthy eating.Fondazione Cariplo and Regione Lombardia within the CRAFT (Cremona Agri-Food Technologies) project ID 2018/275
Machine learning experiments with artificially generated big data from small immunotherapy datasets
No full textYesBig data and machine learning result in agile and robust healthcare by expanding raw data into useful patterns for data-enhanced decision support. The available datasets are mostly small and unbalanced, resulting in non-optimal classification when the algorithms are implemented. In this study, five novel machine learning experiments are conducted to address the challenges of small datasets by expanding these into big data and then utilising Random Forests. The experiments are based on personalised adaptable strategies for both balanced and unbalanced datasets. Multiple datasets from cryotherapy and immunotherapy are considered, however, hereby only
immunotherapy is used. In the first experiment, artificially generated data is presented by increasing the observations of the dataset, each new data is four-time larger than the previous one, resulting in better classification. In the second experiment, the effect of volume on classification is considered based on the number of attributes. The attributes of each new dataset are built based on conditional probabilities. It did not make any difference, in obtained classification, when the number of attributes is increased to more than 879. In the third simulation experiment, classes of data are classified manually by dividing the data into a two-dimensional plane. This experiment is first performed on small data and then on expanded big data: by increasing observations, an accuracy of 73.68% is attained. In the fourth experiment, the visualisation of the enlarged data did not provide better insights. In the fifth experiment, the impact of correlations among datasets' attributes on classification is observed, however, no improvements in performance are achieved. The experiments generally improved performance by comparing the classification results using the original and artificial data
Interventions for self-management of medicines for community dwelling people with dementia, mild cognitive impairment and family carers: a systematic review
No full textYesPeople with dementia or mild cognitive impairment (MCI) and their family carers face challenges in managing medicines. How medicines self-management could be supported for this population is unclear. This review identifies interventions to improve medicines self-management for people with dementia, MCI and their family carers, and which core components of medicines self-management they address. Methods A database search was conducted for studies with all research designs and ongoing citation searches from inception to December 2021. Selection criteria included community dwelling people with dementia and MCI and their family carers, and interventions with a minimum of one medicine self-management component. Exclusion criteria were wrong population, not focusing on medicines management, incorrect medicines self-management components, not in English and wrong study design. Results are presented and analysed through narrative synthesis. The review is registered [PROSPERO (CRD42020213302)]. Quality assessment was carried out independently applying the QATSDD quality assessment tool. Results Thirteen interventions were identified. Interventions primarily addressed adherence. A limited number focused on a wider range of medicine self-management components. Complex psychosocial interventions with frequent visits considered the person’s knowledge and understanding, supply management, monitoring effects and side-effects and communicating with healthcare professionals; and addressed more resilience capabilities. However, these interventions were delivered to family carers alone. None of the interventions described patient and public involvement. Conclusion Interventions, and measures to assess self-management, need to be developed which address all components of medicines self-management, to better meet the needs for people with dementia and MCI and their family carers
Analytical models of mean secondary velocities and stream functions under different bed-roughness configurations in wide open-channel turbulent flows
No full textYesTurbulence-induced secondary currents are commonly present in straight natural as well as artificial open channels without bed forms. Different structures of cellular secondary currents can be seen in open-channel flows due to various bed configurations. In our study, mathematical models of turbulence-induced secondary currents in the vertical and transverse directions within a straight open rectangular channel with alternate rough and smooth longitudinal bed strips are proposed. The proposed models are derived using appropriate theoretical and mathematical analysis. Most of the previous models of secondary currents in the literature are proposed empirically and without proper mathematical derivations. The effects of fluid viscosity and eddy diffusivity are included in the present study to make it more practical. Initially, the governing equation for vertical secondary flow velocity is derived from continuity and the Reynolds-Averaged Navier Stokes equations. Then, the proposed problem is divided into two sub-considerations, corresponding to the base flow and perturbed flow. Finally, these sub-problems are analytically solved using method of variables separation with suitable boundary conditions. Different models to consider two different types of bed-roughness configurations (i.e. equal and unequal lengths of smooth and rough longitudinal bed strips) are obtained. Apart from velocity formulations, models of the stream function are proposed for these two types of bed configurations. All proposed models are validated using existing experimental data for the various bed configurations in open-channel flows and satisfactory results have been obtained. These present models are also compared with empirical models from the literature and they are found to be more effective in representing both types of bed-roughness configurations. The effects of bed configuration on the streamlines of settling velocity are also investigated. Results show that laterally-skewed secondary cells (which occurs due to unequal smooth and rough bed strips), have significant effects on the closed ω-streamlines in terms of shape and location of the centre of these streamlines. More precisely, it is found that the area of the downflow zone proportionally increases with the length of rough-bed strips
Co-designing an intervention to improve the process of deprescribing for older people living with frailty in the United Kingdom
Get PDFYesBackground: In older people living with frailty, polypharmacy can lead to preventable harm like adverse drug reactions and hospitalisation. Deprescribing is a strategy to reduce problematic polypharmacy. All stakeholders should be actively involved in developing a person-centred deprescribing process that involves shared decision-making.
Objective: To co-design an intervention, supported by a logic model, to increase the engagement of older people living with frailty in the process of deprescribing.
Design: Experience-based co-design is an approach to service improvement, which uses service users and providers to identify problems and design solutions. This was used to create a person-centred intervention with the potential to improve the quality and outcomes of the deprescribing process. A ‘trigger film’ showing older people talking about their healthcare experiences was created and facilitated discussions about current problems in the deprescribing process. Problems were then prioritised and appropriate solutions were developed. Review located the solutions in the context of current processes and procedures. An ideal care pathway and a complex intervention to deliver better care were developed.
Setting and participants: Older people living with frailty, their informal carers and professionals living and/or working in West Yorkshire, England, UK. Deprescribing was considered in the context of primary care.
Results: The current deprescribing process differed from an ideal pathway. A complex intervention containing seven elements was required to move towards the ideal pathway. Three of these elements were prototyped and four still need development. The complex intervention responded to priorities about (a) clarity for older people about what was happening at all stages in the deprescribing process and (b) the quality of one-to-one consultations.
Conclusions: Priorities for improving the current deprescribing process were successfully identified. Solutions were developed and structured as a complex intervention. Further work is underway to (a) complete the prototyping of the intervention and (b) conduct feasibility testing.National Institute for Health and Care Research (NIHR) Yorkshire and Humber Patient Safety Translational Research Centre (NIHR Yorkshire and Humber PSTRC
Unpacking physically active learning in education: a movement didaktikk approach in teaching?
Get PDFYesThis paper explores teachers’ educational values and how they shape their judgements about physically active learning (PAL). Twenty one teachers from four primary schools in Norway participated in focus groups. By conceptualising PAL as a didaktikk approach, the findings indicated that teachers engaged with PAL in a way that reflected their professional identity and previous experiences with the curriculum. Teachers valued PAL as a way of getting to know pupils in educational situations that were different from those when sedentary. These insights illustrate how PAL, as a didaktikk approach to teaching, can shift teachers’ perceptions of pupils’ knowledge, learning, and identity formation in ways that reflect the wider purposes of education. The paper gives support to a classroom discourse that moves beyond the traditional, sedentary one-way transfer of knowledge towards a more collaborative effort for pupils’ development.This work was supported by Norwegian Directorate for Higher Education and Skills: [Grant Number 2019-1-NO01-KA203-060324]. The authors of this manuscript were supported and funded by the European Union ERASMUS+Strategic Partnership Fund as part of the Activating Classroom Teachers (ACTivate) project
Modular reconfiguration of flexible production systems using machine learning and performance estimates
Get PDFYesThis paper presents an agent-based framework for reconfiguring modular assembly
systems using machine learning and system performance estimates based on previous
reconfigurations. During a reconfiguration, system integrators and engineers make changes to
the machine to meet new production requirements by increasing capacity or manufacturing
new product variants. The framework provides a method for automatically evaluating these
changes in terms of impact on the performance of the production system, and building a
knowledge base. Such knowledge is used to support future reconfigurations by recommending
changes that are likely to improve the performance based on previous reconfigurations. The
agent architecture of the framework has two levels, one for individual assembly stations and
one for the entire production line. Knowledge bases of changes are built and utilised at both
levels using machine learning and performance estimates. A prototype implementation of the
proposed framework has been evaluated on an assembly production system in an industrial
scenario. Preliminary results show that framework helps to reduce the time and resources
required to complete a system reconfiguration and reach the desired production objectives.This work was supported by the SURE Research Projects Fund of the University of Bradford and the European Commission [grant agreement n. 314762]
Blockchain technology for supply chains operating in emerging markets: an empirical examination of technology organization-environment (TOE) framework
Get PDFYesOrganizations adopt blockchain technologies to provide solutions that deliver transparency, traceability, trust, and security to their stakeholders. In a novel contribution to the literature, this study adopts the technology-organization-environment (TOE) framework to examine the technological, organizational, and environmental dimensions for adopting blockchain technology in supply chains. This represents a departure from prior studies which have adopted the technology acceptance model (TAM), technology readiness index (TRI), theory of planned behavior (TPB), united theory of acceptance and use of technology (UTAUT) models. Data was collected through a survey of 525 supply chain management professionals in India. The research model was tested using structural equation modeling. The results show that all the eleven TOE constructs, including relative advantage, trust, compatibility, security, firm’s IT resources, higher authority support, firm size, monetary resources, rivalry pressure, business partner pressure, and regulatory pressure, had a significant influence on the decision of blockchain technology adoption in Indian supply chains. The findings of this study reveal that the role of blockchain technology adoption in supply chains may significantly improve firm performance improving transparency, trust and security for stakeholders within the supply chain. Further, this research framework contributes to the theoretical advancement of the existing body of knowledge in blockchain technology adoption studies