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Abstract. Saving earth's biodiversity for future generations is an important global task, where automatic recognition of pollen species by means of computer vision represents a highly prioritized issue. This work focuses on analysis and classification stages. A combination of geometrical measures, Fourier descriptors of morphological details using Discrete Cosine Transform (DCT) in order to select their most significant values, and colour information over decorrelated stretched images are proposed as pollen grains discriminative features. A Multi-Layer neural network was used as classifier applying scores fusion techniques. 17 tropical honey plant species have been classified achieving a mean of 96.49% ± 1.16 of success.

Background: Linking survey data to administrative records requires informed participant consent. When linkage includes child data, this includes parental and child consent. Little is known of the potential impacts of introducing consent to data linkage on response rates and biases in school-based surveys. This paper assessed: i) the impact on overall parental consent rates and sample representativeness when consent for linkage was introduced and ii) the quality of identifiable data provided to facilitate linkage. Methods: Including an option for data linkage was piloted in a sub-sample of schools participating in the Student Health and Wellbeing survey, a national survey of adolescents in Wales, UK. Schools agreeing to participate were randomized 2:1 to receive versus not receive the data linkage question. Survey responses from consenting students were anonymised and linked to routine datasets (e.g. general practice, inpatient, and outpatient records). Parental withdrawal rates were calculated for linkage and non-linkage samples. Multilevel logistic regression models were used to compare characteristics between: i) consenters and non-consenters; ii) successfully and unsuccessfully linked students; and iii) the linked cohort and peers within the general population, with additional comparisons of mental health diagnoses and health service contacts. Results: The sub-sample comprised 64 eligible schools (out of 193), with data linkage piloted in 39. Parental consent was comparable across linkage and non-linkage schools. 48.7% (n = 9232) of students consented to data linkage. Modelling showed these students were more likely to be younger, more affluent, have higher positive mental wellbeing, and report fewer risk-related behaviours compared to non-consenters. Overall, 69.8% of consenting students were successfully linked, with higher rates of success among younger students. The linked cohort had lower rates of mental health diagnoses (5.8% vs. 8.8%) and specialist contacts (5.2% vs. 7.7%) than general population peers.

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Introduction: Although the evidence base on bullying victimization and self-harm in young people has been growing, most studies were cross-sectional, relied on self-reported non-validated measures of self-harm, and did not separate effects of in-person and cyberbullying. This study aimed to assess associations of self-harm following in-person bullying at school and cyberbullying victimization controlling for covariates. Methods: School survey data from 11 to 16 years pupils collected in 2017 from 39 Welsh secondary schools were linked to routinely collected data. Inverse probability weighting was performed to circumvent selection bias. Survival analyses for recurrent events were conducted to evaluate relative risks (adjusted hazard ratios [AHR]) of selfharm among bullying groups within 2 years following survey completion. Results: A total of 35.0% (weighted N = 6813) of pupils reported being bullied, with 18.1%, 6.4% and 10.5% being victims of in-person bullying at school only, cyberbullying only and both in-person bullying at school and cyberbullying respectively. Adjusting for covariates, effect sizes for self-harm were significant after being in-person bullied at school only (AHR = 2.2 [1.1-4.3]) and being both in-person bullied at school and cyberbullied (AHR = 2.2 [1.0-4.7]) but not being cyberbullied only (AHR = 1.2 [0.4-3.3]). Feeling lonely during recent summer holidays was also a robust predictor (AHR = 2.2 [1.2-4.0]). Conclusions: We reaffirm the role of in-person bullying victimization on self-harm. Pupils were twice as likely to self-harm following in-person bullying as their nonvictimised peers. Interventions for young people that minimize the potential impacts of bullying on self-harm should also include strategies to prevent loneliness.

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