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Experimental investigation of kerosene single droplet ignition and combustion under simulated high-altitude pressure and temperature conditions
No full textThis study experimentally investigates the ignition and combustion characteristics of single kerosene droplet under simulated high-altitude conditions, focusing on the effects of reduced ambient pressure (100 kPa–20 kPa) and temperature (293 K–253 K). Results show that spark assisted ignition time exhibits a strong inverse power-law dependence on ambient pressure and a non-linear relationship with ambient temperature. At reduced pressures, significantly longer heat accumulation periods are required for ignition, with delayed and more variable ignition behaviour. The combustion process displays distinct stages of droplet swelling, preferential gasification, and disruptive microexplosions, which intensify and become more irregular as pressure decreases. Flame temperature and structure are also strongly pressure-sensitive, with reduced buoyancy at low pressures resulting in more spherical flames and increased flame standoff ratios. While ambient temperature has limited influence on burning rate and microexplosion intensity, it amplifies variability when combined with pressure reduction
The determination of ClNO2 via thermal dissociation–tunable infrared laser direct absorption spectroscopy
Get PDFNitryl chloride (ClNO2) is a reservoir species of chlorine atoms and nitrogen oxides, both of which play important roles in atmospheric chemistry. To date, all ambient ClNO2 observations have been obtained by chemical ionization mass spectrometry (CIMS). In this work, thermal dissociation–tunable infrared laser direct absorption spectrometry (TD-TILDAS) is shown to be a viable method for quantifying ClNO2 in laboratory and field settings. This technique relies on the thermal dissociation of ClNO2 to create chlorine radicals, which undergo fast reactions with hydrocarbons to produce hydrogen chloride (HCl) that is detectable by the TILDAS instrument. Complete quantitative conversion of ClNO2 to HCl was achieved at temperatures > 400 °C, achieving 1 Hz measurement precision of 11 ± 1 pptv (3σ limits of detection of 34 ± 2 pptv) during laboratory comparisons with other ClNO2 detection methods. After blank and line loss corrections, method accuracy is estimated to be within ± 5 %. Performance metrics of TD-TILDAS during ambient sampling were a 1 Hz precision of 19 ± 1 pptv and 3σ limits of detection of 57 ± 3 pptv, which is directly comparable to previously reported ClNO2 detection by quadrupole CIMS. Thus, TD-TILDAS can provide an alternative analytical approach for a direct measurement of ClNO2 that can complement existing datasets and future studies. The quantitative nature of TD-TILDAS also makes it a potentially useful tool for the calibration of CIMS instruments. However, interpretation of ambient data may be complicated by potential interferences from unaccounted-for sources of thermolabile chlorine, such as ClNO, chloramines, and organochlorides
Life Worth Living: Caring for our Educators and Principals: Evaluation and Impact Report
No full textThe ‘Life Worth Living: Caring for our Educators & Principals’ (LIFE) project was an initiative funded by the European Union through the ERASMUS+ programme, aiming to enhance the well-being of primary and secondary school teachers and principals in Belgium, Bulgaria, Greece, Iceland, and Italy. Recognizing the pressing challenges faced by educators across Europe—such as low wages, high workloads, and job dissatisfaction—the project sought to address these issues by fostering personal growth, meaningful reflection, and supportive communities among educators
Developing indoor heat-health warning systems for vulnerable populations
No full textWith respect to the changing environmental conditions and extreme heat events associated with climate change, this article presents a review of existing heat-health warning systems1 and discusses how such systems can be further augmented to account for indoor environmental conditions. The development of indoor heat-health warning systems is urgently needed to enhance the health and social care for vulnerable populations who spend long hours indoors. As a proof-of-principle study, we first introduce an indoor heat-health warning system developed for the general population in the UK, demonstrating its use case based on the 2013 heatwave event. Focusing on older people living in residential care — one of the most vulnerable populations worldwide — we illustrate the capabilities of an indoor heathealth warning system through a modelling framework which evaluates the impact of climate (change) on a building’s heat and energy performance, from neighbourhood to city scales. An indoor heat-health warning system deployed at care homes should be able to foretell residents’ indoor heat exposures given forecasts of impending heatwave events
On calculating structural similarity metrics in population-based structural health monitoring
Get PDFThe newly introduced discipline of Population-Based Structural Health Monitoring (PBSHM) has been developed in order to circumvent the issue of data scarcity in “classical” SHM. PBSHM does this by using data across an entire population, in order to improve diagnostics for a single data-poor structure. The improvement of inferences across populations uses the machine-learning technology of transfer learning. In order that transfer makes matters better, rather than worse, PBSHM assesses the similarity of structures and only transfers if a threshold of similarity is reached. The similarity measures are implemented by embedding structures as models —Irreducible-Element (IE) models— in a graph space. The problem with this approach is that the construction of IE models is subjective and can suffer from author-bias, which may induce dissimilarity where there is none. This paper proposes that IE-models be transformed to a canonical form through reduction rules, in which possible sources of ambiguity have been removed. Furthermore, in order that other variations —outside the control of the modeller— are correctly dealt with, the paper introduces the idea of a reality model, which encodes details of the environment and operation of the structure. Finally, the effects of the canonical form on similarity assessments are investigated via a numerical population study. A final novelty of the paper is in the implementation of a neural-network-based similarity measure, which learns reduction rules from data; the results with the new graph-matching network (GMN) are compared with a previous approach based on the Jaccard index, from pure graph theory
Objective demonstration and quantitation of musical learning in older adult novices across a 12-month online study
Get PDFThis work aimed to objectively (mainly computationally) measure the extent to which 68 older adult novices developed specific musical abilities. The participants learned aural and keyboard performance skills in a 12-month online course with an expert piano teacher, spending six months each on a digital piano keyboard and an iPad virtual piano. Within each 6 months, 3 were devoted successively to each of melodic replication and improvisation. Teaching sought correctness of pitches/sequences (for replication), and introduction of systematic diversity thereof (for improvisation). We measured aural perception using melody detection and beat alignment tests; and replication and improvisation learning using computational measures of MIDI-recordings. Bayesian modelling showed that melody detection, replication and improvisation were learned successfully and seemingly progressively, while beat detection, and rhythmic precision in replication, which were not our focus, were not. These skills were retained over a 6-month follow-up period. Improvisation teaching was the bigger predictor of melody detection, and replication teaching of replication performance. Potential applications for these findings in learning contexts are discussed
Patterns, socioeconomic inequalities and determinants of healthy eating in Kenya: results from a national cross-sectional survey
Get PDFObjective
The burden of non-communicable diseases is rising in low-and-middle-income countries, with diet being a key risk factor. This study aimed to assess the patterns, socioeconomic inequalities and determinants of eating healthy in Kenya. The study is the first in Kenya to use a healthy diet index to assess dietary patterns.
Design and methods
We analysed cross-sectional data from the 2015/16 Kenya Integrated Household Budget Survey. The study’s outcome variable was a continuous healthy diet index (HDI) constructed using principal component analysis from nine WHO/Food and Agriculture Organization (FAO) healthy diet recommendations. The HDI score and WHO/FAO healthy diet recommendations met were summarised for Kenyan households. Using the concentration index, we examined the socioeconomic disparities in healthy eating. In addition, multivariable linear regression was used to determine factors that influence healthy eating in Kenya.
Results
A total of 21 512 households in Kenya were included, of which 60% were rural and about two-thirds headed by males. The HDI score ranged between −1.13 and 1.70, with a higher value indicating healthier eating. Overall, the average HDI score was 0.24 (95% CI: 0.24 to 0.25), interpreted as moderate. We identified key determinants including socioeconomic status and urban–rural residency differences. Healthy eating was concentrated among higher socioeconomic households, regardless of gender or location. Higher socioeconomic status (β=0.28, 95% CI 0.26 to 0.30), rural residence (β=0.18, 95% CI 0.15 to 0.20), household head being in union (β=0.04, 95% CI 0.02 to 0.06) or employed (β=0.05, 95% CI 0.02 to 0.08) were significantly associated with increased HDI scores, whereas male-headed households and lack of education were associated with significant decreases in HDI scores on average.
Conclusions
Most Kenyan households do not meet all the healthy dietary recommendations, and socioeconomic inequalities exist in eating healthy. Targeted interventions that promote healthy eating based on key determinants in Kenya are required
Identifying Classes and Correlates of Anti-social Behaviour in Early Adolescence
Get PDFDespite evidence that early anti-social behaviours can persist and escalate into adulthood, understanding of how these behaviours present in early adolescence and the associated factors, is limited. Using secondary data from 11,868 9-to-10-year-olds recruited to the Adolescent Brain Cognitive Development study, we applied latent class analysis (LCA) to 20 items from the parent-rated Child Behaviour Checklist. Three classes were identified: Rule-abiding (66.52%), Infrequent-disobedient (27.85%) and Frequent-delinquent (5.63%). The socio-demographic composition of these classes varied based on sex, ethnicity and household income. A multinomial regression demonstrated that, while the classes were mostly associated with independent sets of factors, there was some commonality in factors associated with increased anti-social behaviour, including the presence of parental mental disorders, increased parental transgressive behaviour and family conflict. Generally, environmental factors were more strongly associated with class membership than psychological factors. These findings can be used to inform the development of targeted preventative policies and interventions
A call to action for deciphering genetic variants in human pluripotent stem cells for cell therapy
No full textHuman pluripotent stem cell (hPSC)-based therapies offer promise but pose potential risks due to culture-acquired genetic variants, some of which have been linked with cancer. An international workshop addressed these concerns, highlighting the need for improved strategies to stratify variants and chart a path toward definitive guidelines in hPSC-based therapy
Increasing drivers’ intentions to use intelligent speed assistance: a randomised controlled trial of a theory of planned behaviour-based intervention
Get PDFTechnological advances can provide an opportunity to reduce road traffic crashes.Intelligent Speed Assistance (ISA) is one technology that is increasingly available in modern vehicles. The full realisation of ISA's safety potential is contingent upon the extent to which drivers choose to drive with the system turned on. Based on the theory of planned behaviour, we designed a brief online intervention (comprising a leaflet and animation) to strengthen intention to use ISA that could be presented to drivers when purchasing an ISA enabled vehicle. A randomised controlled trial with a sample of 1029 participants showed that the intervention had a small-to-medium sized effect in strengthening intention to use ISA in drivers who do not have ISA installed in the vehicle they usually drive compared to those in an active control condition. This effect remained significant one week and one month after the intervention. Further analysis revealed that the effect of the intervention was partially mediated by attitudes toward ISA use, underpinned by changes in in behavioural beliefs about the advantages and disadvantages of turning ISA on. The results support the use of our freely available intervention to encourage drivers to voluntarily turn ISA on when purchasing an ISAenabled vehicle
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