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Does physical activity level and total energy expenditure relate to food intake, appetite, and body composition in healthy older adults? A cross-sectional study
Get PDFPurpose: With ageing, older adults (≥65 years) may experience decreased appetite, contributing to declines in body weight and muscle mass, potentially affecting physical capabilities. Physical activity (PA) has been suggested as a potential strategy to enhance appetite in older adults, but evidence supporting this is insufficient. This study aimed to investigate the relationship between PA levels, total energy expenditure (TEE), body composition, energy intake (EI) and appetite in older adults.
Methods: One hundred and eight healthy older adults (age 70±4 years; BMI 24.3±2.6 kg/m2) were categorised into three groups (low, medium, high) based on accelerometer-measured PA level (AMPA) and TEE from seven-day PA diaries. Body composition was measured using bioelectrical impedance. Energy and nutrient intakes were assessed using 3-day weighed food diaries. Appetite was assessed using the visual analogue scales at 30-minute intervals throughout one day.
Results: TEE was positively correlated with EI and % muscle mass (p<0.05), with higher % muscle mass and TEE associated with higher EI. Energy and protein intake were significantly higher in the high TEE group than the low group (p=0.03, p=0.01; respectively). No significant differences in energy and macronutrient intake were observed across AMPA groups, and appetite components (hunger, fullness, desire to eat, prospective consumption) did not differ significantly in either the AMPA or TEE groups.
Conclusions: Higher TEE is associated with higher energy and protein intake, with body composition playing a crucial role. These findings highlight the importance of considering PA, TEE, and body composition in interventions aimed at improving EI in older adults
‘Trans’forming identities: migrant workers as informal interpreters
Get PDFConstruction sites are often multilingual spaces as high numbers of migrants are employed in the industry. Bilingual workers are used as informal interpreters to enable people to work together. However, little is known about who these workers are and why they take on this language work. This paper presents the stories of three informal interpreters who help facilitate communication on international construction projects. These stories, that come from a wider ethnographic research project, demonstrate how the individual’s identity is significant for why they take on this unpaid labour and how identity shapes how they perform it. This study suggests that some workers invest in their language skills, driven by their imagined communities as permanent or transnational migrants. Consequently, they are more engaged with the informal interpretation tasks than bilinguals who do not invest in their language skills and intend to return to their country of origin. This research suggests that formalising language work would help retain communication skills in the industry and may encourage investment in the informal interpreter function. This paper contributes to the theoretical discussion on investment and imagined communities by demonstrating how applying these terms generates new insights in research on migrants at work
Consumer adoption of cryptocurrencies as a precursor to a decentralized financial system: a push-pull-mooring model
Get PDFConsumer adoption of decentralized blockchain solutions, such as decentralized finance (DeFi) applications, has demonstrated considerable technological promise. However, to benefit from DeFi applications, consumers must purchase and own cryptocurrencies, which is a potential obstacle to adopting decentralized blockchain technology. This study employed a push-pull-mooring model to examine factors influencing individuals’ willingness to use cryptocurrencies. In particular, how do push (i.e. diminishing value and pricing problems), pull (i.e. relative security and perceived value) and mooring (i.e. switching cost and personal innovativeness) factors shape individuals’ switching intentions.
Design/methodology/approach
About 300 valid responses were collected via an online survey and analyzed using partial least squares structural equation modeling (PLS-SEM).
Findings
The results confirm that the factors of push (i.e. pricing problem and low perceived value of traditional fiat money), pull (i.e. relative security and perceived value of cryptocurrency) and mooring (i.e. switching cost and personal innovativeness in technology) significantly impact switching intention to cryptocurrency. These findings offer key insights and implications for consumer adoption of cryptocurrencies as a precursor to participating in decentralized blockchain ecosystems.
Originality/value
Cryptocurrencies have been associated with numerous risk and security concerns, potentially holding back consumer adoption of DeFi financial solutions. Accordingly, this paper contributes to extending the knowledge of consumer adoption of cryptocurrency, switching from traditional money to using cryptocurrencies based on the push-pull-mooring theory (PPM). This allows for a detailed analysis of the critical factors that hinder or promote consumers' adoption of decentralized blockchain solutions
Artificial Intelligence in documentary filmmaking: the ethics of deepfakes
No full textGenerative AI enables filmmakers to manipulate video and audio through machine learning techniques. Documentary makers have been at the forefront of the adoption of this technology, in particular the ‘deepfake’ process of altering the face or voice of an interviewee, despite an apparent conflict with the documentary principle of the authentic portrayal of a film’s subject. This chapter explores how documentary filmmakers are using deepfakes in their practice. It uses production case study and interview methodologies to understand the creative intentions and technological processes undertaken by key innovators in this field of documentary production. Key ethical concerns raised by filmmakers themselves and their audiences are elaborated. A feature of this discussion is the centrality of ethical debate at multiple levels: within the technology itself, within the process of documentary production, and in the reception of those documentary films that have integrated Generative AI into their creative process
Whey protein based colloidal gas aphrons combined with solid–liquid extraction as an integrated green separation of phenolics from fruit based by-products
Get PDFColloidal gas aphrons (CGA) are microbubbles created by the intense stirring of a surfactant solution that can be used as a separation method for biomolecules. The main objective of this work was to investigate for the first time the use of whey protein as a natural surfactant for CGA generation. Furthermore, their application for separating phenolic compounds from hydroalcoholic extracts obtained from fruit based by-products (grape marc and red goji berry). Additionally, to investigate if this surfactant-rich fraction could confer an advantage in stabilising anthocyanins during storage. First, a hydroalcoholic extract was obtained from each feedstock; then whey protein isolate (WPI) generated CGA were applied and compared with Tween 20 generated CGA. Recovery performance was assessed based on total phenolics, flavonoids, and antioxidant capacity. CGA generated with a 1.5 % (WPI) displayed comparable characteristics (gas hold-up and stability) to those generated with Tween 20 (10 mM). The CGA separation process with WPI led to a recovery of up to 97 % of phenolic compounds but a loss of antioxidant capacity under the tested conditions. Hydrophobic interactions as well as hydrogen bonding between phenolics and WPI could be responsible for the successful separation that could also hinder the radical scavenging activity. In contrast, these interactions could be responsible for the stabilising effect on anthocyanins observed during storage. Overall, CGA generated with WPI have resulted in an integrated separation method that by combining it with hydroalcoholic extraction leads to the effective separation of phenolics and their pre-formulation in a whey protein rich solution with stabilisation effect
Data supporting the North Atlantic Climate System Integrated Study (ACSIS) programme, including atmospheric composition; oceanographic and sea-ice observations (2016–2022); and output from ocean, atmosphere, land, and sea-ice models (1950–2050)
Get PDFThe North Atlantic Climate System Integrated Study (ACSIS) was a large multidisciplinary research
programme funded by the UK’s Natural Environment Research Council (NERC). ACSIS ran from 2016 to 2022 and brought together around 80 scientists from seven leading UK-based environmental research institutes to
deliver major advances in the understanding of North Atlantic climate variability and extremes. Here, we present
an overview of the data generated by the ACSIS programme. The datasets described cover the North Atlantic
Ocean, the atmosphere above it (including its composition), and Arctic sea ice.
Atmospheric composition datasets include measurements from seven aircraft campaigns (45 flights in total,
0–10 km altitude range) in the northeastern Atlantic (∼ 15–55° N, ∼ 40° W–5° E) made at intervals of 6 months
to 2 years between February 2017 and May 2022. The flights measured chemical species (including greenhouse
gases; ozone precursors; and volatile organic compounds – VOCs) and aerosols (organic aerosol – OA; SO4;
NH4; NO3; and non-sea salt chloride – nss-Cl) (https://doi.org/10.5285/6285564c34a246fc9ba5ce053d85e5e7,
FAAM et al., 2024). Ground-based stations at the Cape Verde Atmospheric Observatory (CVAO), Penlee Point
Atmospheric Observatory (PPAO), and Plymouth Marine Laboratory (PML) recorded ozone, ozone precursors,
halocarbons, greenhouse gases (CO2 and methane), SO2, and photolysis rates (CVAO; http://catalogue.ceda.ac.
uk/uuid/81693aad69409100b1b9a247b9ae75d5, National Centre for Atmospheric Science et al., 2010); O3 and
CH4 (PPAO, https://catalogue.ceda.ac.uk/uuid/8f1ff8ea77534e08b03983685990a9b0 (Plymouth Marine Laboratory and Yang, 2017); and aerosols (PML, https://doi.org/10.5285/e74491c96ef24df29a9342a3d57b5939,
Smyth, 2024), respectively.
Complementary model simulations of atmospheric composition were performed with the UK Earth System
Model (UKESM1) for the period from 1982 to 2020 using Coupled Model Intercomparison Project Phase 6
(CMIP6) historical forcing up to 2014 and Shared Socioeconomic Pathways (SSP) scenario SSP3-7.0 from 2015
to 2020. Model temperature and winds were relaxed towards ERA reanalysis. Monthly mean model data for
ozone, NO, NO2, CO, methane, stratospheric ozone tracers, and 30 regionally emitted tracers are available for
download (https://data.ceda.ac.uk/badc/acsis/UKESM1-hindcasts, Abraham, 2024).
ACSIS also generated new ocean heat content diagnostics (https://doi.org/10/g6wm, https://doi.org/10/g8g2,
Moat et al., 2021a–b) and gridded temperature and salinity based on objectively mapped Argo measurements
(https://doi.org/10.5285/fe8e524d-7f04-41f3-e053-6c86abc04d51 King, 2023).
An ensemble of atmosphere-forced global-ocean sea-ice simulations using the NEMO-CICE model was
performed with horizontal resolutions of 1/4 and 1/12° covering the period from 1958 to 2020 using several different atmosphere-reanalysis-based surface forcing datasets, supplemented by additional global simulations and stand-alone sea-ice model simulations with advanced sea-ice physics using the CICE model
(http://catalogue.ceda.ac.uk/uuid/770a885a8bc34d51ad71e87ef346d6a8, Megann et al., 2021e). Output is stored
as monthly averages and includes 3D potential temperature, salinity, zonal velocity, meridional velocity, and vertical velocity; 2D sea-surface height, mixed-layer depth, surface heat, and freshwater fluxes; ice concentration
and thickness; and a wide variety of other variables.
In addition to the data presented here, we provide a very brief overview of several other datasets that were
generated during ACSIS and have been described previously in the literature
Automated construction contract analysis for risk and responsibility assessment using natural language processing and machine learning
Get PDFConstruction contracts contain critical risk-related information that requires in-depth examination, yet tight schedules for bidding limit the possibility of comprehensive review of extensive documents manually. This research aims to develop models for automating the review of construction contracts to extract information on risk and responsibility that will provide inputs for risk management plans. Models were trained on 2268 sentences from International Federation of Consulting Engineers templates and tested on an actual construction project contract containing 1217 sentences. A taxonomy classified sentences into Heading, Definition, Obligation, Risk, and Right categories with related parties of Contractor, Employer, and Shared. Twelve models employing diverse Natural Language Processing vectorization techniques and Machine Learning algorithms were implemented and benchmarked based on accuracy and F1 score. Binary classification of sentence types and an ensemble method integrating top models were further applied to improve performance. The best model achieved 89% accuracy for sentence types and 83% for related parties, demonstrating the capabilities of automated contract review for identification of risk and responsibilities. Adopting the proposed approach can significantly expedite contract reviews to support risk management activities, bid preparation processes and prevent disputes caused by overlooking risks and responsibilities
Book review: protecting genetic privacy in biobanking through data protection law by Dara Hallinan
No full text'The Most Civilized Book': Luigi Meneghello e Raleigh Trevelyan
Get PDFThis study explores the backroom issues surrounding the English translation of Luigi Meneghello’s 1964 volume I piccoli maestri, published with the title The Outlaws by the London-based firm Michael Joseph in 1967. The contribution focuses on the relationship between the author and the translator, writer and editor Raleigh Trevelyan (1923-2014). By examining the publishing correspondence surrounding the translation, preserved at the Biblioteca civica Bertoliana in Vicenza, this study puts forward an hypothesis regarding the reasons why Meneghello decided not to mention this translation in his writings about I piccoli maestri
In search of the origins of distance hunting – the use and misuse of tip cross-sectional geometry of wooden spears
Get PDFThe origins of weapons, and subsequent innovations, constitute a significant focus of archaeological research, particularly for the Pleistocene period. Due to preservation challenges, inorganic components of early weapons, such as lithic points, are often the only artefacts to survive. As a result, archaeologists rely on proxies for understanding performance and function of these lasting components including experimental research and ethnographic comparison. Within these analogical frameworks, and alongside use-wear and fracture analysis, morphometrics constitute a key method in assessing whether a point is a weapon component. Early attempts to use the cross-sectional geometries of weapon points (or tips), making use of complete archaeological specimens and ethnographic weapons as reference datasets, suggested clear demarcations between different delivery modes. Yet, subsequent studies have shown that there are considerable overlaps. Recently, it was proposed that on the basis of tip geometries the earliest complete weapons, Pleistocene wooden spears, are best matched to thrusting spear use. Here we demonstrate that there are measurement errors involved in this classification, and that furthermore there are overlaps between thrusting spears and javelins (throwing spears) that undermine the use of tip geometries to define spear delivery mode. If the correct methods are applied, archaeological wooden spear tip geometries would fit within both thrusting and javelin categories, meaning this is not methodologically useful at this time. We overview the available archaeological, experimental and ethnographic evidence and propose that these currently support a hypothesis that the technological capacity for use of distance hunting weapons was in place from at least 300,000 years ago