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Disaster capitalism and the political ecology of wildfire recovery in North Evia, Greece
No full textAmid the global proliferation of wildfires, in this article we explore post-disaster fire governance in Greece. Drawing on empirical research into the aftermath of the 2021 North Evia wildfires and engaging with scholarship on the political ecology of fires and disaster capitalism, we examine how the wildfire was framed as an opportunity for spatial restructuring. Our analysis unpacks the mechanisms through which state and non-state actors reconfigured planning and environmental governance to bypass democratic processes, undermine local environmental claims and marginalize resin cultivators, beekeepers, shepherds and farmers in favor of touristification and urban expansion. We argue that, under the guise of the climate emergency, recovery strategies not only displace rural livelihoods but also erode socio-environmental resilience, facilitating processes of wildland gentrification that reproduce and intensify vulnerabilities to climate change-induced catastrophes in fire-prone areas. Elite actors hold a key role in these processes as they attempt to capitalize upon their involvement in climate change adaptation strategies and gear recovery policy towards their interests
Assessment and design of RC frames incorporating effects of restraint to beam hysteresis elongation
No full textIn reinforced concrete (RC) frames, beam elongation under cyclic loading is typically restrained by columns, hence inducing axial compression that results in beam overstrength and elevated force demands on adjacent columns and joints. Despite the pronounced influence of these restraint effects, they are not explicitly addressed in current seismic design procedures due to the lack of reliable methods for estimating the beam axial restraint stiffness and the resulting compression. To address this, a thermal analogy approach to evaluate the restraint stiffness is proposed and validated against cyclic test results. A prediction model is also developed for determining the restraint-induced axial compression, with due account for the degradation caused by column yielding. Based on these developments, a seismic design methodology that incorporates the beam axial compression effects is established. The proposed methodology is applied to a multi-story RC frame and compared with detailed numerical results. It is shown that the proportion of restraint-induced force demands increases from the frame center toward the edges. Importantly, despite employing various capacity design amplification factors, design codes are found to grossly underestimate these effects by up to 50%, particularly for shear demands in exterior columns. Considerable beam overstrength are also shown to occur in code-designed frames, with interior beams exhibiting overstrength approaching 40%. In contrast, the methodology proposed in this study effectively mitigates the beam overstrength and captures the restraint-induced force demands on both the columns and joints. By dealing with the restraint effects through beam reinforcement optimization and column-joint strengthening, the proposed methodology enables the mobilization of the intended strong-column/weak-beam and strong-joint mechanisms, hence offering a rational and practical solution for significantly improving the seismic performance of RC frame structures
Deep learning approaches for impact identification on composite structures under environmental and operational variabilities: a comparative study
No full textThis study presents a comprehensive evaluation of deep learning approaches for impact identification in composite structures under environmental and operational variabilities (EOVs). Five representative architectures—Convolutional Neural Networks (CNNs), Temporal Convolutional Networks (TCNs), Recurrent Neural Networks (RNNs), Graph Neural Networks (GNNs), and Transformers (XFMRs)—are compared across two key tasks: impact localisation (predicting spatial coordinates) and impact force reconstruction (estimating time-varying force histories). Particular emphasis is placed on model robustness when testing conditions deviate from those used in training, including temperature changes and impact mass variation. Additionally, the effects of critical data acquisition parameters—such as sampling frequency, signal window length, and sensor density—on model performance and generalisability are systematically investigated. Experimental validation is conducted using controlled impact tests on composite panels, providing insight into the strengths and limitations of each model architecture in realistic structural health monitoring scenarios
Rain or shine, default risks align: exploring the climate-default nexus in small and micro firms
No full textWe investigate the impact of escalating temperatures and heavy rainfall on the default probability of small and micro enterprises (SMiEs) in six European countries between
2005 and 2014. Our findings reveal that a one standard deviation increase (2.56 °C) in the yearly mean temperature raises a firm’s default probability by 86.5 basis points.
Additionally, a one standard deviation increase (2.46 mm) in the Simple Precipitation Intensity Index increases the default probability by 32.4 basis points. We argue that
one channel explaining the adverse impact of climate risk on default probability is labour productivity loss. In addition, micro and financially constrained firms exhibit
increased vulnerability to these risks. However, when the ultimate owners also serve as the firms’ managers, they can mitigate the adverse effects of rising temperatures and
heavy rainfall
Fine Chemicals Sector 2025. Sectoral systems of innovation and the UK’s competitiveness
No full textExecutive Summary
We are extremely grateful to Lord David
Sainsbury and the Gatsby Charitable Foundation
for generously supporting this sectoral study
of the fine chemicals industry. It is a sector with
significant contributions to the UK’s economy
(both directly and by underpinning other sectors)
but is facing multiple challenges within and
outside the UK. As such, it deserves a closer
inspection of its status and the development
of potential interventions. We aimed to provide
a diagnosis of the industry by looking at its
landscape, productivity, skills requirements,
technology, innovation, business, and regulatory
environment. We coupled these with deep dives
with UK chemical industry organisations to
support our findings. Based on these analyses
and stakeholder engagements, we developed
our high-level conclusions, recommendations to
stakeholders, and areas of further detailed study.
Our key conclusions so far are the following:
• The global fine chemicals industry is a thriving and
growing industry marked by a competitive market,
wherein the major players dominate at 40% to 45%.
Most of the fine chemicals businesses are involved
in manufacturing (80% of the market). Having R&D
capabilities, manufacturing expertise & efficiency,
supply chain management, global presence reach,
and regulatory compliance are crucial competitive
advantages in the global landscape.
• Being the birthplace of fine chemicals, the UK’s industry
has been well-established with highly diversified
products. The UK’s fine chemicals sector interlinks its
own bulk (or commodity) chemicals industry to various
end-use sectors within the country and internationally.
Our estimates show that fine chemicals contribute 40%
of the GDP value of chemical manufacturing (£11bn to
£12bn), which is commonly reported.
• The UK’s broad chemicals industry (bulk + fine), while
significant, has struggled with consistent productivity
growth since the global financial crisis. The industry’s
international competitiveness, particularly against
countries like China and India, is being challenged by
high energy prices, raw material shortages, and skilled
labour shortages. Zooming in on the UK fine chemicals
sector, it may in principle be insulated from these
challenges due to its nature of business and the high
value of its products. Drivers of productivity growth
in the fine chemicals industry include technology
and product innovation and scaling up, meeting skills
requirements, an enabling business environment,
and an enabling policy and regulatory environment.
• Our calculations show that the UK’s fine chemicals
industry has a Gross Value Added (GVA) of £33 billion
and employs over 231,000 people, which translates into
a labour productivity of £143,000 per employee as of
2024. The top five contributing subsectors are Catalysts,
Contract chemicals, Specialty polymers, Pigments &
dyes, and Construction chemicals. This highlights the
fine chemicals sector’s importance, beyond its own KPIs,
as it underpins other key industries of the UK including
pharmaceuticals, agrochemicals, fast-moving consumer
goods, automotive, aerospace, and building and
construction.
• The fine chemicals industry primarily uses chemical
synthesis and biotechnology, with chemical synthesis
being the focus of this report due to its extensive toolbox
of available reactions. Fine chemicals production typically
occurs in multi-purpose batch plants, which are designed
to handle various chemical reactions and synthesis,
and purification steps, allowing for efficient production
of a diverse range of products. These plants, while
costly, offer flexibility and cost-effectiveness, especially
when compared to dedicated plants for each product.
Key technology innovation and scale-up requirements
include competency in synthesising complex fine
chemicals, flexible manufacturing, process intensification,
and increasing biotechnology integration. Drivers of
innovation include product design, sustainability, the
net-zero transition, biomass conversion, and synthetic
biology. Digital technologies are another driver that will
revolutionise sustainable manufacturing of fine chemicals
whilst increasing efficiency and reducing costs. Lastly, the
battery industry is another technology innovation driver,
which driven by the net-zero transition, will create demand
for innovative fine chemicals.
• The current UK chemical industry requires skilled
workers, particularly technicians with level 3 to level 5
qualifications. There is a shortage of a skilled workforce
due to a “lost generation” and labour shortages. While the
industry currently relies on external labour markets and
in-house training, future skills requirements must be met;
these include topics such as chemistry and engineering
innovation, data analysis, and leadership, which are
going to be crucial for addressing complex commercial
challenges and opportunities brought about by the
UK’s net-zero commitment and the advent of Industry
4.0. These emerging skills requirements reflect a
transitioning chemicals industry requiring new thinking
and strong leadership.
• Business-to-business transactions, custom
manufacturing, and R&D-driven fast-to-market
products are integral in doing fine chemicals
business. Considering these, enabling mechanisms
for the UK fine chemicals sector include strategic
procurement, government-supported logistics,
market access support, prioritising IP ownership,
and SME acceleration. These mechanisms aim
to drive innovation, competitiveness, and economic
growth within the sector.
• Fine chemical manufacturers, both globally and in
the UK, are subject to a range of regulations, including
the Registration, Evaluation, Authorisation and Restriction
of Chemicals (REACH). While the UK REACH is largely
aligned with the EU REACH, its potential divergence of
standards and processes from internationally accepted
regulations may pose additional overhead compliance
and hamper trade, considering how chemical value chains
are integrated across the globe. A new development in
the EU is that of “Safe and Sustainable by Design” which
may create additional opportunities for innovation in
new chemicals and materials while also subjecting
these to increased scrutiny.
• Our deep dives with organisations in the UK’s
chemical industry revealed insights that resonated
with our review and analysis, to date. According to
the Chemical Industry Association (CIA), the UK fine
chemicals industry faces challenges including energy
and feedstock costs, consistent sustainability reporting,
and a skills gap. CIA recommends streamlining
regulations, supporting alternative feedstocks, and
regionalising policies as pathways toward better
international competitiveness of the industry. On the
other hand, the Society of Chemical Industry (SCI)
reported that the UK chemical industry faces challenges
in policy coordination and investments, despite its
historical importance and innovations. SCI recommended
that the UK must address industry structure, energy
productivity, and regulatory alignment to capitalise on
growth opportunities, especially from new chemistries
and circular carbon, and overcome threats. Lastly,
The Centre for Process Innovation (CPI) stated that
the challenges of the UK chemical industry are due
to declining domestic production and reliance on
global supply chains. CPI recommended, to improve
competitiveness, the UK should incentivise platform
chemicals production, support disruptive technology
adoption, and bridge the gap between academic
research and industry application.
We believe our recommendations to stakeholders
(academia, industry, and government) are going to
be a collective and collaborative effort. These can
be grouped into six interconnected priorities to
form a robust enabling ecosystem for the UK’s
fine chemicals sector.
Priority 1. Sector strategy planning:
An agreed industry-led sector strategy is vital to
address immediately the short-term challenges and
create a supportive ecosystem in the long term.
Priority 2. Economic and business development:
An enabling chemical business environment to
enhance the industry’s GVA and grow its global
competitiveness.
Priority 3. Regulation and policy:
A more streamlined policy environment to prevent
deviations from international standards and to foster
innovations creating a competitive edge.
Priority 4. Skills:
A skills roadmap to meet both the skill required
now, and the skills required in the future to ensure
a globally competitive workforce.
Priority 5. Innovation:
A strong focus on the R&D of product innovation,
flexible manufacturing and process intensification
whilst ensuring the IP developed is exploited first
within the UK.
Priority 6. Mindset change:
A need for greater recognition of our home-grown
chemicals industry in terms of its importance and
role in everyday life of British citizens
Impact of the Federated Data Platform’s digital surgery scheduling system on elective theatre utilisation at an NHS Trust: an interrupted time series analysis
No full textObjectives: To evaluate the NHS Federated Data Platform (FDP) Inpatient Care Coordination Solution (CCS) digital scheduling tool on elective theatre utilisation.
Methods: An interrupted time series assessed changes in theatre utilisation and cancellations following tool adoption (January 2022). Weekly data spanned 90 weeks (April 2021 to December 2023). Outcomes included weekly median theatre utilisation (actual, booked, and bookings per session) and the percentage of cancelled bookings. Models incorporated a 5-week lag and estimated level (step-change) and trend (slope) effects.
Results: Post-intervention level and trend increases were observed for booked (β=4.40, P=0.045; β=0.26, P=0.002) and actual (β=3.98, P=0.064; β=0.23, P=0.006) utilisation. Bookings per session showed a significant level increase (β=0.34, P=0.002) with no trend change (β=0.00, P=0.790). Across the post-intervention period, compared with counterfactual estimates, booked and actual utilisation were 15.0% (95% CI: 13.4 to 16.5%, P<0.0001) and 12.2% (95% CI: 10.8 to 13.5%, P<0.0001) higher, while bookings per session were 10.9% (95% CI: 9.5 to 12.4%, P<0.0001) higher. Significant positive effects were observed for Urology, General Surgery, Gynaecology, Plastic Surgery and Ophthalmology. A significant upward trend in cancellation rates was associated with the introduction of the tool (β=2.1, P=0.001).
Discussion: Findings suggest that centralised digital scheduling tools can improve theatre capacity by enabling more efficient use of existing capacity through improved scheduling visibility. Future research should explore differences in speciality-level usage and long-term sustainability of gains.
Conclusion: The introduction of the NHS FDP Inpatient CCS product was associated with improved elective theatre utilisation
Socioeconomic inequalities in the self-reported use of antibiotics in the European Union, 2009-2022: a repeated cross-sectional analysis
No full textObjectives: This study aims to explore trends in the use of antibiotics, in the context of the COVID-19 pandemic, across the European Union (EU), focusing on socioeconomic inequalities.
Design: Repeated cross-sectional analysis.
Setting: 26 EU Member States.
Participants: Analyses were conducted using data from five waves of the Eurobarometer survey (2009-2022, n=127,299).
Primary and secondary outcome measures: We used multilevel logistic regression, stratified by financial difficulty, to examine changes in past-year use of
antibiotics and in obtaining antibiotics inappropriately over time, adjusting for gender, age, type of community, children under-10 in household and antibiotic-related
knowledge.
Results: We found that the odds of self-reported use of antibiotics decreased between 2009 and 2022 in those with (Odds Ratio [OR]=0.59, 95% Confidence Interval [CI]:0.55-0.63) and without financial difficulties (OR=0.53, 95%CI:0.50-0.56), with a substantial reduction between 2018 and 2022. However, a relatively higher proportion of Europeans who used antibiotics in the past year were obtaining them inappropriately in those with (OR=2.03, 95%CI:1.68-2.45) and without financial difficulties (OR=1.83, 95%CI:1.53-2.19) in 2022. Among those with financial difficulties, higher self-reported use of antibiotics and inappropriately obtaining antibiotics were associated with lesser knowledge about antibiotics.
Conclusions: Despite notable progress made in the EU in reducing antibiotic use, current efforts fall short in addressing the issue of inappropriate antibiotic use. A
targeted approach prioritising outreach to vulnerable populations to advance attitudes and behaviours related to appropriate antibiotic use may be required to
achieve further progress.
Strengths and limitations of this study
• We analysed data covering 26 countries over a 13-year period.
• We used consistent measures across countries and over time.
• The cross-sectional study design limits causal inference.
• Data on antibiotic use are self-reported and do not include information on frequency and duration
Predicting rates of cognitive and functional decline in Alzheimer’s disease and mild cognitive impairment
No full textBackground The global population of People Living with Dementia (PLWD) is expected to grow rapidly in the coming decades, increasing the need for personalised, generalisable, and scalable prognosis and care planning support. However, current prognostic guidance does not adequately capture the heterogeneity in dementia trajectories, and existing predictive models of dementia
progression rely on costly and inaccessible data, limiting their scalability in resource-constrained settings.
Methods Using clinical assessments, demographic, and medical history data from 153 12-month clinical trajectories collected over three years, two machine learning algorithms were developed to predict 12-month cognitive and functional decline in Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI). Models were externally validated on 741 trajectories from the ADNI cohort. Cognitive and functional decline were estimated using the Mini-Mental State Exam (MMSE) and Bristol
Activities of Daily Living (BADL).
Results The MMSE model achieves a mean absolute error (MAE) of 1.84 (95% CI: 1.64–2.04) internally and 2.19 in external validation. The BADL model achieves an MAE of 3.88 (95% CI: 3.46–4.30). Baseline scores on ideational praxis, orientation, and word recall are among the strongest predictors of cognitive decline, while independence in food preparation, finances, and
dressing are among the top predictors of functional decline.
Conclusions Our models use only routinely collected and easily accessible data, offering high translational potential. If im plemented, our scalable, data-driven prognostic support tool could streamline clinical workflows, support personalised care planning, and provide PLWD and their families with greater clarity and reassurance
Behavioural Signals
No full textThis chapter provides an overview of how behavioural signalling differentially impacts the formation, reinforcement, and decline of social evaluations. Drawing from prior literature, the chapter acknowledges that behavioural signalling serves as a foundational driver across various social evaluations and distil the general manner in which it works across social evaluations. It then turns to the variations and idiosyncrasies that may arise for how behavioural signalling affects different social evaluations. To this end, the chapter examines the relationship between types of behaviour, sources of behaviour, behavioural frequency, and behavioural consistency in their roles in gaining, maintaining, or removing the evaluations, as well as how possession of the social evaluation may impact interpretations of subsequent behavioural signals. It explores the significance of these features in shaping diverse social evaluations and the distinct implications for each evaluation. The chapter concludes by pointing towards promising avenues for future research at the intersection of behavioural signalling and social evaluations
TraN variants mediate conjugation species specificity of IncA/C, IncH and Acinetobacter baumannii plasmids
No full textIncA/C and IncH plasmids commonly carry antimicrobial resistance genes, notably blaNDM-1. Although these plasmids disseminate among Gram-negative pathogens via conjugation, the mechanisms underlying mating pair stabilisation (MPS) and conjugation species specificity
remain poorly understood. In IncF plasmids, MPS is mediated by interactions between outer membrane proteins (OMP) encoded by the plasmids in the donor (TraN) and by the chromosome in the recipient. Using the Plascad database, we extracted 1,436 TraN sequences from 1517 plasmids: 62.5% (898/1,436), mainly in IncF plasmids, are 550–660aa (we renamed TraN short, TraNS); 15% (216/1,436), in IncA/C plasmids, are 880–950aa (TraN medium, TraNM); and 11% (160/1,436), in IncH plasmids, are 1,050–1,070aa (TraN long, TraNL). One TraN, found in six plasmids from Acinetobacter baumannii (891aa), was designated TraN V-shaped (TraNV). Like TraNS, TraNM and TraNL contain a base and one distal tip domain essential for conjugation, whereas TraNV has a base and two distinct tip domains forming a V-shaped structure. TraNM, TraNL and TraNV determine conjugation species specificity, with TraNL cooperating with OmpA. Tip swapping reverses conjugation specificity, revealing how TraNM and TraNL diversity influence plasmid host range and AMR dissemination. Our new data reveal the molecular basis of plasmid host specificity and broaden our understanding of how conjugation drives the dissemination of antimicrobial resistance genes among clinically relevant bacteria