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Impact of ocean heat transport on sea ice captured by a simple energy balance model
Get PDFFuture projections of Arctic and Antarctic sea ice suffer from uncertainties largely associated with inter-model spread. Ocean heat transport has been hypothesised as a source of this uncertainty, based on correlations with sea ice extent across climate models. However, a physical explanation of what sets the sea ice sensitivity to ocean heat transport remains to be uncovered. Here, we derive a simple equation using an idealised energy-balance model that captures the emergent relationship between ocean heat transport and sea ice in climate models. Inter-model spread of Arctic sea ice loss depends strongly on the spread in ocean heat transport, with a sensitivity set by compensation of atmospheric heat transport and radiative feedbacks. Southern Ocean heat transport exhibits a comparatively weak relationship with Antarctic sea ice and plays a passive role secondary to atmospheric heat transport. Our results suggest that addressing ocean model biases will substantially reduce uncertainty in projections of Arctic sea ice
Exploring Intolerance of Uncertainty: behavioural, cognitive and emotional responses to uncertainty, and developmental associations with mental health
Get PDFAnxiety disorders are the most common mental health issues experienced in society,
and can occur earlier in the lifespan than other mental health disorders. Untreated anxiety in
young people can lead to challenges at school and home, and can increase the probability of
long-term mental health problems. Intolerance of Uncertainty (IU) has been linked to higher
levels of anxiety and worry in both adults and children but a number of limitations exist. There
is limited research examining IU and worry in young children, a lack of longitudinal research
examining associations between IU and worry across childhood, and almost no understanding
of how high IU relates to behavioural, cognitive and emotional responses under uncertainty,
particularly in children.
In Study 1, IU and generalised anxiety were assessed across childhood. The results
revealed associations between generalised anxiety and IU at each time point; those with
higher IU had higher symptoms than those with lower IU. Contrary to expectations,
longitudinal analysis showed that higher IU predicted downward trends in generalised anxiety
over time. This suggests that IU is associated with generalised anxiety across childhood but is
unlikely to play a causal role in the onset of generalised anxiety. Following this, Study 2
explored the relationship between IU and children’s behaviour and affect under uncertainty.
This study also examined the role of curiosity to tease apart effects of IU from curiosity. IU was
not found to predict children’s emotional responses, however children did seek more
information under higher uncertainty than lower uncertainty, but this was not related to
either IU or curiosity. Lastly, Study 3 replicated Study 2 but with adult participants. Those
higher in IU were more worried and had more negative affect than those with lower IU,
particularly in high uncertainty trials, but they did not seek more information.
Overall, these studies provide new knowledge about developmental associations
between IU and generalised anxiety and advance current understanding of the construct of IU
and how it is associated with behavioural, cognitive and emotional responses to uncertainty.
Future priorities lie in psychophysiological, observational and qualitative work with children
An effective textured Novel Object Recognition Test (tNORT) for repeated measure of whisker sensitivity of rodents
Get PDFRodents use their whisker system to discriminate surface texture. Whisker-based texture discrimination tasks are often used to investigate the mechanisms encoding tactile sensation. One such task is the textured Novel Object Recognition Test (tNORT). It takes advantage of a tendency of rodents to explore novel objects more than familiar ones and assesses the sensitivity of whiskers in discriminating different textures of objects. It requires little training of the animals and the equipment involved is a simple arena with typically two objects placed inside. The success of the test relies on rodents spending sufficient time exploring these objects. Animals may lose interests in such tasks when performed repetitively within a limited time frame. However, such repeated tests may be crucial when establishing a sensitivity threshold of the whisker system. Here we present an adapted rodent tNORT protocol designed to maintain sustained interest in the objects even with repeated testing. We constructed complex objects from three simple-shaped objects. Different textures were provided by sandpapers of varying grit sizes. To minimise olfactory clues, we used the sandy and the laminar side of the same sandpaper as the familiar and novel textures assigned at random. We subsequently conducted repeated tNORTs on eight rats in order to identify a critical threshold of the sandpaper grit size below which rats would be unable to discriminate the sandy from the laminar side. With an inter-test-interval of seven days and after five tNORTs, the protocol enabled us to successfully identify the threshold. We suggest that the proposed tNORT is a useful tool for investigating the sensitivity threshold of the whisker system of rodent, and for testing the effectiveness of an intervention by comparing sensitivity threshold pre- and post-intervention
The combined effect of chitosan and high hydrostatic pressure on Listeria monocytogenes and Escherichia coli
Get PDFThis study explores the combined effect of different High Hydrostatic Pressures (HHP; 200–300 MPa) with
various chitosan concentrations (up to 0.2%) on five Listeria monocytogenes strains and one of Escherichia coli, at
temperatures 20 & 35 ◦C. Cells were resuspended in ACES buffer 1 h prior to HHP. A synergistic effect of chitosan
and HHP was reported for first time in the above bacterial species tested. Synergistic effect up to 1 log reduction was
observed at 300 MPa and chitosan at 20 ◦C against L.monocytogenes LO28 with FBR13 being the most sensitive
strain at 250 MPa and 0.1% chitosan. Higher combined effect was found at 35 ◦C compared to 20 ◦C at 200 MPa
highlighting for first time the significant role of temperature in the above synergistic action. Pressure and temperature
had a greater impact on inactivation and synergism than chitosan concentrations. Synergistic effect (1 log
reduction) was also observed in E. coli K12 at 0.1% chitosan and 200 MPa.
Industrial relevance: This study presents the significance of combining HHP with natural antimicrobials to control
L. monocytogenes and E. coli. Even though the technology is used for 3 decades in the food industry, its cost is still
relatively high. Therefore, it is important to investigate novel ways to reduce the pressure intensity resulting in
reduced costs, lower energy consumption and a broader product portfolio. This research demonstrates for first
time the synergistic action of chitosan and HHP on L. monocytogenes and E. coli and the significant role of
temperature that could contribute in the enhancement of the antimicrobial effect and optimization of the processing
conditions. This aligns also with the growing demand for more sustainable and natural systems regarding
the food production
An investigation into cognitive and linguistic variables that influence the learning and production of formulaic sequences by undergraduate students via a speaking task in an English-as-a-second-language context
Get PDFA key problem for second language (L2) learners in many contexts is to improve the fluency
of their speech (Tavakoli & Wright, 2020). As fluent speakers often make use of fixed
expressions – i.e. formulaic sequences (FS), improving our understanding of these
expressions will help us understand how they impact language ability in general and fluency
in particular. Although many studies focus on the complexity, accuracy and fluency (CAF) of
L2 learners’ output, there are still few in-depth studies that examine the CAF of the FSs
themselves as used by L2 learners. Therefore, this study aimed to address this gap by
investigating the correlation between various linguistic and cognitive variables and (a) the
CAF of entire speech and (b) the CAF of FSs elicited via a speech sample.
Participants in the study were adult L2 learners of English in Kuwait. The sample
under study (N = 51) were mostly at A1 to A2 level according to the CEFR, with some
participants at B1 to C1 levels. Participants carried out a monologic speaking task revolving
around the topic of giving self-introduction in a work-life context. Participants also carried
out the following tasks: a general proficiency test (the Quick Placement Test), a vocabulary
test (New Vocabulary Levels Test), a FSs test (the Phrasal Vocabulary Size Test), a test of
familiarity of FSs (operationalised as expressions learned from the participants’ textbook) and
working memory tasks (Wechsler Adult Intelligence Scale IV).
This study proposes a novel complexity index of FSs, derived from TAALES indices
(Kyle et al., 2018), and monolinguals’ judgements of the transparency of each FS and their
complexity. The analysis of fluency of FSs is based on a study of the pauses before and after
each FSs, while accuracy of FSs examination focuses on errors and error-free chunks within
FSs.
Results from hierarchical regression analysis indicate that working memory was
significantly associated with the complexity of overall speech, aligning with recent studies
(Awwad & Tavakoli, 2022). This suggests that learners with higher working memory capacity
(WMC) can store and retain more complex speech compared to those with lower WMC.
However, no significant associations were found between learners’ working memory and
CAF of FSs, suggesting that for learners with lower working memory, the use of FSs serves
as a compensatory strategy to overcome the challenges linked with limited WMC. These
findings highlight the strategic role of FSs in enhancing speech production, addressing
complexities in language use, accuracy and fluency.
Interestingly, scores from the vocabulary test showed a less significant correlation
with both the CAF of speech and CAF of FSs elicited via speech samples. This finding
suggests several implications, including that low-proficiency learners may compensate for
limited vocabulary by relying more on FSs, given their prior exposure to these sequences
Similarly, general proficiency test scores showed a moderately positive correlation with
CAF-FSs. This highlights the importance of general proficiency in language learning,
although with a potentially less pronounced impact on the utilisation and integration of FSs
into spoken language. These findings are important as they highlight the importance of
concentrating on FSs in language learning, especially for this groups of participants –
beginners.
Furthermore, while the study shows that scores from the test of familiarity of FSs
significantly predict CAF of FSs scores derived from speech samples, the FS test derived
from literature containing unfamiliar FSs had a weaker association with both CAF of entire
speech and CAF of FSs in speech. This underscores the importance of prior exposure and
familiarity with domain knowledge. It is argued that it may also be the case that the FS test
derived from the literature was too advanced to accurately capture beginner learners’
knowledge or to establish an association, considering that the participants were mostly lower-proficiency learners, even though this test was not restricted to a specific language
proficiency level; instead, it was advocated for use by all L2 learners. These findings have
several significant implications for L2 research, educators and those interested in pedagogy.
An important avenue for future research involves replicating this study with learners
at higher proficiency levels to explore whether similar individual difference variables
associate with CAF of speech and subsequently CAF of FSs. Additionally, investigating
whether scores from test of familiarity of FSs maintain their explanatory power for CAF of
FSs, compared to more general FS tests, would provide insights into the dynamics of
language production across proficiency levels
Ecofeminist kitchens: reimagining professional kitchens as spaces of sustainable foodwork
Get PDFProfessional kitchens are both producers and
consumers of food and many operate through
unsustainable practices which have significant
social and ecological impacts. Socially, they
are spaces of low paid, high-pressured work,
where gendered occupational discrimination
is common. Ecologically, food production in
these spaces contributes significantly to the
demand for unethical meat production and
the commodification of nature globally. The
main aim of this article is to reimagine professional kitchens as spaces of sustainable
and equitable foodwork. To this end, this
research combines an empirical analysis of
the relation between gender, power, and sustainability in professional kitchens in Glasgow
with a theoretical examination of ecofeminist
scholarship. In Glasgow, data were collected
through semi-structured interviews with both
male and female head chefs on the everyday
(un)sustainable practices and norms of professional chefs and the ways they intertwine with
gender. This research found that kitchens are
organised in ways that normalize toxic masculinity, disempower women, and seriously
harm non-human others. Furthermore, the
absence of ecological literacy in professional kitchens is shown to be a significant driver of unsustainable behaviours. Drawing on
ecofeminist scholarship, this article goes on to envision what changes are needed for
a sustainable and equitable transformation in professional kitchens. Based on this
theoretical engagement, I argue that transforming professional kitchens requires a
redistribution of power across genders to eradicate sexist hierarchies. Furthermore,
there is a need to decenter economic profit to make space for an ethic of compassion
which fulfils our moral obligations to both human and non-human others
People’s experiences living with achalasia: new insights into long-term management
Get PDFBackground: Achalasia is a rare, chronic condition that affects the motility of the oesophagus and
significantly impacts the lives of people affected. Recognising the importance of understanding the lived
experience, this thesis sets out to identify the challenges faced by people living with achalasia and
collaboratively develop a potential solution for improved long-term management.
Methods: The thesis utilised a mixed-method approach across three distinct studies, incorporating
process mapping, intervention co-design, and a feasibility study. The first study collected qualitative
data from process mapping sessions, detailing the experiences and challenges faced by people living
with achalasia and identifying key areas for support. The second study focussed on the primary
challenge prioritised by participants. A series of online focus groups were conducted to provide a
comprehensive analysis of this challenge, facilitating collaborative discussions around potential
intervention strategies. Building on the insights gathered from these focus group discussions, an
intervention was co-designed to meet the identified need. The thesis concludes with a mixed-method
feasibility assessment, utilising questionnaires and semi-structured interviews to measure the
acceptability, usability, and potential efficacy of the proposed intervention.
Results: In addition to the clear physical problems, achalasia also brings about hidden social challenges
that people living with achalasia face in their everyday lives. In study 1, a process map was developed to
detail the lived experiences of people living with achalasia from diagnosis to long-term management.
One of the predominant challenges consistently identified was issues related to eating behaviour,
evident at every stage of their journey with achalasia. Informed by these insights, participants in study 2
specifically identified "eating in social settings" as a target behaviour for intervention. Using the COM-B
model as a framework, the behaviour change intervention was co-designed, and an evidence-based
workbook was developed. Testing the feasibility and practicality of this workbook, implemented in a
real-world setting, was the focus of study 3. This feasibility study provided insight into participant
recruitment and retention. Positive feedback on the workbook's usability was a key finding, along with
the potential effectiveness in supporting people living with achalasia. Participants reported that the
significant strength of the workbook was its content alignment with their unique experiences and
challenges.
Conclusion: In conclusion, this thesis has illuminated the intricacies of living with achalasia, offering
insights into the experiences of individuals facing this rare condition. Through a patient-centric approach
and by co-designing an intervention specifically targeting the challenge of social eating, this thesis
demonstrates the principles of patient-centred care. The feasibility study indicated the intervention's
©University of Reading 2024 Page 6
potential effectiveness. The application of these findings lies in the real-world impact of the co-designed
intervention, which has the potential to significantly improve the lives of those living with achalasia by
addressing a critical aspect of their daily challenges including social eating. Subsequent research should
focus on assessing the sustained efficacy of this intervention and advocate for the continued inclusion of
patient perspectives in shaping more comprehensive and impactful solutions for individuals living with
rare chronic conditions like achalasia
Peptide lipidation and shortening optimises antibacterial, antibiofilm and membranolytic actions of an amphiphilic polylysine-polyphenyalanine octapeptide
Get PDFThe demand for broad-spectrum antibacterial agents continues with increasing rates of resistance of microbial pathogens to traditional antibiotics. Peptides and lipopeptides are gaining traction as promising novel, class-reference antibiotics for tackling difficult-to-treat infections caused by multi-drug resistant bacteria. To identify novel candidates and expand treatment options in clinical settings, we explored the in vitro antibacterial potential and mode of action of a short octapeptide combining a cationic block of four lysines and a highly hydrophobic segment of four phenylalanines (K4F4), and two K4F4-inspired lipopeptides (Palmitoyl-K4F4 and K4-NH-Palmitoyl). Preliminary AI-based screening had revealed the antimicrobial potential of the K4F4 peptide coupled with limited haemolytic activity. Broth dilution and haemolytic assays have confirmed these in silico predictions. Overall, our lipidated peptides were more active at lower MIC values compared to non-lipidated species, indicating the beneficial impact of tailing lipidation on design of peptide-based antimicrobials. An integrated view of the membrane-active mechanism of these novel therapeutic templates was obtained using a combination of flow cytometry, fluorescence microscopy and dye-based permeabilization assays. K4F4 and its lipidated derivatives act via a fast-disrupting mechanism without inducing bacterial resistance mechanisms in a long-term exposure assay. A K4F4-inspired lipopeptide together with its shorter version (K4-NH-Palmitoyl), were more stable in environments closer emulating physiological conditions, showing a higher antibacterial response in physiological salts and serum than their parent peptide. Our findings reveal the antibacterial and antibiofilm potential of a novel polylysine-polyphenyalanine peptide and highlight the significant contribution of lipidation and shortening as molecular engineering strategies to improve and guide the future design of next-generation membrane-targeting antibiotics
Improving referral triage in rheumatology using large language model and multimodal machine learning
No full textRheumatic and musculoskeletal disease (RMDs) is a chronic disease, which affects
over 20 million people in the UK, and approximately 1.71 billion people in the world.
Particularly, there are two prominent subdivisions of RMDs, inflammatory arthritis (IA)
and non-inflammatory conditions (NIC), which have clearly different treatment and
management pathways (e.g., disease-modifying drugs for IA; surgeries such as joint
replacements for NIC e.g., osteoarthritis). Therefore, accurately differentiate IA and NIC
is essential for patients to be referred to the right specialists and receive the right treatment
rapidly.
Early detection of RMDs is challenging because it often features vague symptoms,
and there is currently no diagnostically definitive single biomarker for the detection.
Moreover, the prevailing manual review process is hampered by low efficiency, primarily
attributed to the intricacy of data modalities originating from general practitioners (GP),
which encompasses unstructured GP referral letters, structured blood test results, and
semi-structured clinical information summary (CIS).
In this thesis, extracting features from various above-mentioned data modalities acts
as the main challenge to develop a machine learning based system for the early RMDs
identification. To address these data challenges, distinct machine learning-based methods
have been proposed, including large language model (LLM) based methods to address
unstructured data challenge, general machine learning model-based methods to address
structured data challenge, graph neural network (GNN) based methods to deal with semistructured data challenge, and multimodal machine learning based methods to address
multimodal data challenge that happened during the referral triage process.
Experimental findings demonstrated relatively strong performance of the proposed
methods on various datasets that have been collected from the Royal Berkshire
Foundation Trust (RBFT), Reading, UK. Additionally, a small pilot trial has been
conducted at the Rheumatology Department of RBFT. The experimental results indicated
that the proposed models outperformed clinicians across various measurement metrics.
Overall, this thesis is the first study to research early rheumatic disease diagnosis by
using machine learning-based decision support methods, aimed at improving the hospital
referral triage with interpretable and trustworthy results provided for clinicians. This
study revealed promising performance of machine learning-based risk stratification methods in early RMDs differentiation, demonstrating great potential for future practical
applications