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Urban heat stress, air quality and climate change adaptation strategies in UK cities
Get PDFConsistently threatened by climate change, cities need to adapt to emerging hazards and risks. One such risk relates to extreme heat, which is a particular problem in urban areas and is also linked to air pollution. Together, these risks can have a substantial impact on human health. Our analysis of air quality, ambient temperatures, and climate change adaptation plans in 30 UK cities found strong evidence that London and Cambridge exhibit the highest risk of both extreme temperature and air pollution. Furthermore, although a heatwave in London led to lower levels of PM10 and NO2, it was highly correlated with increased levels of O3, a low-level pollutant that exacerbates respiratory problems. We also found a lack of data availability (e.g., O3, PM10) in some local authorities and inconsistencies in their climate change adaptation strategies. We therefore identify a clear need for standardised assessment of hazards at the city level, and their incorporation into local adaptation plans. Further assessment of climate hazards and risks at the city level are required for effectively adapting to a changing climate in the UK and other cities worldwide
Time-varying global energy budget since 1880 from a new reconstruction of ocean warming
Get PDFThe global energy budget is fundamental for understanding climate change. It states that the top-of-atmosphere imbalance between radiative forcing (which drives climate change) and radiative response (which resists the forcing) equals energy storage in Earth's heat reservoirs (i.e.\ the ocean, atmosphere, land and cryosphere). About 90\% of Earth's energy imbalance is stored as heat content in the ocean interior, which is poorly sampled before 1960. Here, we reconstruct Earth's energy imbalance since 1880 by inferring subsurface ocean warming from surface observations via a Green's function approach. Our estimate of Earth's energy imbalance is consistent with the current best estimates of radiative forcing and radiative response during 1880--2020. The consistency is improved in this study compared to previous ones. We find two distinct phases in the global energy budget. In 1880--1980, Earth's energy imbalance closely followed the radiative forcing. After 1980, however, Earth's energy imbalance increased at a slower rate than the forcing; in 2000--2020, the imbalance amounted to less than 50\% of the forcing. In simulations of historical climate change, the model-mean energy imbalance is consistent with observations within uncertainties, but individual models with a ``weak'' response to anthropogenic aerosol agree better with observations than those with a ``strong'' response. Because the global energy budget before and after 1980 imply very different global warming in the future, further studies are required to better understand the cause of this historical variation
A retrieval-augmented multiagent system for financial sentiment analysis
No full textFinancial sentiment analysis (FSA) has seen substantial advancements with the use of large language models (LLMs). Previous research highlighted the effectiveness of retrieval-augmented generation (RAG) and multiagent LLMs for FSA as these approaches alleviate the problems of hallucination, a lack of factual knowledge, and limited complex problem-solving capability. Despite this, the interplay and potential synergies between these two methods remain largely unexplored. This study presents a notable leap forward by introducing a retrieval-augmented multiagent system (RAMAS) to enhance LLM-based FSA performance. An RAMAS is specifically designed to deepen understanding of the critical factors that are inherent in FSA and mimic human-like consensus-making processes by adaptively learning from semantically similar few-shot samples and engaging in conversations among the generator, discriminator, and arbitrator agents. Our evaluation of RAMASs demonstrates improved accuracy and F1-score across multiple established FSA benchmark datasets
Word learning in children with developmental language disorder: a meta-analysis testing the encoding hypothesis
Get PDFMany children with Developmental Language Disorder (DLD) find learning new words difficult, which negatively affects their educational and psycho-social outcomes. Word learning involves encoding, consolidation and reconsolidation of words, but the most challenging phase and factors which moderate word learning remain unclear.
We conducted a systematic review and meta-analysis to determine which phase is most challenging and which factors predict oral word learning success in children with DLD. The search including PsycINFO, PubMed, Web of Science, and LLBA identified forty-six studies published before April 2024 comparing children with DLD and typically developing (TD) age-matched peers in word learning tasks. Seventy-eight effect sizes were calculated for encoding (n DLD = 1462, n TD = 2161), eight for consolidation (n DLD = 107, n TD = 112), and 19 for reconsolidation (n DLD = 296, n TD = 278).
The random effect model identified an effect for encoding (k = 78, d = 0.82, [0.66, 0.98], p < .001) but not consolidation (k = 8, d = −0.2, [−0.68, 0.29], p = .43) or reconsolidation (k = 19, d = 0.23, [−0.14, 0.59], p = .22) of new words. The moderator analysis via random effects models identified verbal short-term memory and lexical knowledge as significant moderators of encoding, while word length was the most important task characteristic.
Despite limited data for consolidation and reconsolidation, our findings provide new insights into oral word learning difficulties in children with DLD. These insights help clinicians and teachers identify support strategies while also highlighting gaps in existing research, driving future studies forward
Energy consumption analysis of using mashrabiya as a retrofit solution for a residential apartment in Al Ain Square, Al Ain, UAE
Get PDFThe city of Al Ain is a fast-developing area. With building typology varying from lowrise to mid-rise, sustainable design in buildings is needed. As the majority of the city’s
population is Emirati Citizens, the percentage of expats is increasing. The expats tend to
live in mid-rise buildings. One of the central midrise areas is AL Ain Square. This study
aims to investigate how an optimized mashrabiya pattern can impact the energy and the
Predicted Mean Vote (PMV) in a 3-bedroom apartment, fully oriented to the south, of
an expat family. The methodology is as follows: case study selection, Weather analysis,
Modeling/Validation of the base case scenario, Optimization of the mashrabiya pattern,
Simulation of various scenarios, and Results. Analyzing the selected case study is the
initial step of the methodology. This analysis begins with the district, building typology,
and the chosen apartment. The weather analysis is relevant for using the mashrabiya
(screen device) and the need to improve energy consumption and thermal comfort. The
modeling of the base case shall be performed in Rhino Grasshopper. The validation is
based on a one-year electricity bill provided by the owner. The optimization of mashrabiya
patterns is an innovative process, where various designs are compared and then optimized
to select the most efficient pattern. The solutions to the selected scenarios will then yield
the results of the optimal scenario. This study is relevant to industry, academia, and local
authorities as an innovative approach to retrofitting buildings. Additionally, the research
presents a creative vision that suggests optimized mashrabiya patterns can significantly
enhance energy savings, with the hexagonal grid configuration demonstrating the highest
efficiency. This finding highlights the potential for geometry-driven shading optimization
tailored to specific climatic and building conditions. Contrasting earlier mashrabiya studies
that assess one static pattern, we couple a geometry-agnostic evolutionary solver with a
utility-calibrated EnergyPlus model to test thousands of square, hexagonal, and triangular
permutations. This workflow uncovers a previously undocumented non-linear depth
perforation interaction. It validates a hexagonal screen that reduces annual cooling energy
by 12.3%, establishing a replicable, grid-specific retrofit method for hot-arid apartments
Thiol-ene click hydrogels from pentaerythritol tetrakis(3-mercaptopropionate) and polyethylene glycol diacrylate: mucoadhesive and antimicrobial platforms for drug delivery
No full textHydrogels with mucoadhesive properties offer significant potential for drug delivery due to their tunable physicochemical characteristics and sustained drug release capabilities. This research investigates polymer hydrogels synthesized via thiol-ene click reactions between pentaerythritol tetrakis(3-mercaptopropionate) (PEMP) and polyethylene glycol diacrylate (PEGDA), exploring their potential as effective mucoadhesive and antimicrobial drug delivery systems. Sol–gel analysis revealed that gel formation efficiency depends on the acrylate-to-thiol ratio, with stoichiometric formulations yielding higher gel fractions. FTIR spectroscopy and elemental analysis confirmed the chemical composition of these hydrogels, showing the presence of residual CC bonds and a decrease in thiol group content with increasing PEGDA concentration. The mechanical properties were superior in hydrogels prepared using stoichiometric (1:1) ratios of the reagents, while mucoadhesiveness—tested on ovine vaginal tissue—was enhanced in samples with higher thiols-bearing PEMP content. Drug loading efficiency and release kinetics were evaluated for clindamycin phosphate and clotrimazole. Hydrophilic gels showed greater clindamycin loading and more sustained release compared to clotrimazole. Antimicrobial testing demonstrated that clindamycin-loaded hydrogels exhibited strong antibacterial activity against Staphylococcus aureus. Clotrimazole-loaded hydrogels showed less pronounced antifungal effects against Candida albicans. These findings highlight the applicability of PEGDA-PEMP hydrogels for mucoadhesive drug delivery and antimicrobial applications
Investigating the effects of microplastics on social behaviours using Caenorhabditis elegans
No full textMicroplastics are pollutants present throughout the food chain in terrestrial and aquatic ecosystems.
Microplastic exposure causes increased oxidative stress, inflammation, and tissue damage. However,
microplastics also impact oestrogenic and androgenic signalling, suggesting that microplastic
treatment may impact hormonally-regulated processes, including social behaviours. Despite this,
there is a lack of studies linking altered hormonal signalling and hormonally-regulated behaviour
changes due to microplastic treatment. This study uses Caenorhabditis elegans to investigate the
effects of microplastic treatment on parental and male mating behaviours with a focus on the
potential role of the putative androgen receptor, NHR-69, and the putative oestrogen receptor,
NHR-14, to understand whether disruption occurs via signalling through these receptors. C. elegans
is genetically traceable, possesses conserved hormonal pathways, and presents established social
behaviours, making it an ideal experimental system to address microplastic toxicity on social
behaviours.
This research developed a method of scoring male mating behaviour to gain an in-depth
understanding of the specific effects of PS-MP treatment on the mating process. While microplastic
treatment caused defects in male mating behaviour, specifically in contact response behaviour and
spicule insertion, C. elegans lacking NHR-69 signalling did not show these changes upon PS-MP
treatment, suggesting that microplastics may act via the NHR-69-regulated androgenic signalling
pathway to disrupt male mating behaviour.
In contrast, microplastic treatment of C. elegans males with impaired NHR-14 signalling led to
exacerbated microplastic toxicity, measured by a reduction in mating stages performed after
scanning behaviour, indicating that microplastics did not impair mating behaviour via this receptor.
This study showed that NHR-14 signalling regulates parental behaviours. However, the impacts of
microplastics on parental behaviours via this receptor are still unclear. This study highlights the
complexity of microplastic interactions with hormonal signalling pathways and outlines the need for
further research to unravel the underlying mechanisms
Insect life and letters: the studies of Hanns Heinz Ewers and Otto and Rose Hecht
Get PDFThis article argues that vast histories of war and displacement in the twentieth century are connected to the small and almost unnoticeable lives of insects, and that philology has much to gain from paying attention to insect worlds. We examine two case studies: the work of the German entomologist Otto Hecht and his wife, Rose Caro Hecht, and the lay entomology of the German writer Hanns Heinz Ewers and his letter exchange with geneticist Richard B. Goldschmidt. Drawing on the cultural‐theoretical work of Walter Benjamin, our analysis sheds light on the entanglement of entomological and philological labour and a recurrent interplay of intimacy and violence in both. We develop an approach which takes seriously the eros of intellectual pursuits and the endless curiosity that drives the study of words and insects, but which also shows how these encounters with the very small intersect with incomprehensibly large‐scale political violence in the twentieth century. We playfully suggest that the method we develop in this article constitutes a form of ‘insect philology’
Ammonia emissions from a poultry farm drive changes in soil biogeochemistry and microbial communities along a treebelt in northern England
No full textAgriculture is responsible for 87 % of ammonia (NH3) emissions in the UK, mostly from concentrated point sources, contributing to the exceedance of critical nitrogen deposition concentrations. Treebelts (also known as shelterbelts) can be planted around emission sources to intercept NH3 and reduce its drift. This study examined how atmospheric NH3 concentration affects soil biogeochemistry, and the composition and richness of fungal and bacterial communities beneath a 13-year-old treebelt on a poultry farm in Cumbria, UK. We measured tree growth and analysed soil samples collected at varying distances from the poultry housing to evaluate the effect of NH3 concentration. Under the highest NH3 concentration, soil pH decreased by 13 % (p < 0.001), six out of the nine nutrients we examined decreased significantly (p < 0.05), while soil organic carbon was 29 % higher under the greatest NH3 concentration within the treebelt (p < 0.05). The community composition of soil fungi and bacteria (based on ITS, LSU, and 16S amplicon sequencing) changed significantly with NH3 concentration (p < 0.001), driven mainly by soil pH, phosphate, C/N ratio and ammonium (plus nitrate for bacteria). Genus richness of arbuscular mycorrhizal fungi, saprotrophic fungi, and bacteria were 80 %, 9 %, and 13 % lower respectively under the highest NH3 concentration (p < 0.05). Overall, higher NH3 concentrations closer to the poultry housing significantly altered soil chemistry and microbial community composition, and reduced richness, highlighting the importance of understanding NH₃ impacts on soil ecology when using treebelts to capture emissions
Home-based attentional bias modification with webcam-based eye tracking with persons with cognitive impairment: a feasibility study
Get PDFObjectives: Remotely delivered attentional bias modification (ABM) studies involving persons with cognitive impairment are lacking. Thus, the feasibility of an adapted ABM paradigm with webcambased eye tracking was explored.
Methods: Four of the eight participants recruited (males, Mage = 69 years, Alzheimer’s disease = 3, mild cognitive impairment = 1) completed up to four daily ABM sessions. Tasks comprised pre- and post-intervention depression (PHQ-9), anxiety (GAD-7), and rumination (RRS) measures, a cognitive screen (TICS) (A), affect (PANAS) (B) and dot-probe AB measures (C), and dot-probe ABM (D) (Session 1–A, B, C, D, C, and B; Sessions 2 to 4–B, D, C, and B).
Results: The intervention was feasible (as defined by completion rates) and appeared beneficial in this small sample (as defined by post-intervention improvements in mood). Sessions were long, and task completion/adherence was impacted by task access/participants’ ability to complete tasks independently. Mind wandering, stimuli familiarity, and eye/fatigue were reported.
Conclusions: The intervention requires further adaptation (e.g. fewer eye-tracking tasks per session). Limitations include participant self-selection/loss, a lack of control group, and that the determinants of mood change are unclear.
Clinical Implications: ABM, a novel intervention, may be an effective mood-disorder treatment for individuals with cognitive impairment