Hierarchical Agglomerative Cluster Analysis Applied to WIBS 5-Dimensional Bioaerosol Data Sets

Peer reviewe

Detection of Airborne Biological Particles in Indoor Air Using a Real-Time Advanced Morphological Parameter UV-LIF Spectrometer and Gradient Boosting Ensemble Decision Tree Classifiers

We present results from a study evaluating the utility of supervised machine learning to classify single particle ultraviolet laser-induced fluorescence (UV-LIF) signatures to investigate airborne primary biological aerosol particle (PBAP) concentrations in a busy, multifunctional building using a Multiparameter Bioaerosol Spectrometer. First we introduce and demonstrate a gradient boosting ensemble decision tree algorithm’s ability to accurately classify laboratory generated PBAP samples into broad taxonomic classes with a high level of accuracy. We then develop a framework to appraise the classification accuracy and performance using the Hellinger distance metric to compare product parameter probability density function similarity; this framework showed that key training classes were sufficiently different in terms of particle fluorescence and morphology to facilitate classification. We also demonstrate the utility of including advanced morphological parameters to minimise inter-class conflation and improve classification confidence, where relying on the fluorescent spectra alone would likely result in misattribution. Finally, we apply these methods to ambient data collected within a large multi-functional building where ambient bacterial- and fungal-like classes were identified to display trends corresponding to human activity; fungal-like classes displayed a consistent diurnal trend with a maximum at midday and hourly peaks correlating to movements within the building; bacteria-like aerosol displayed complex, episodic events during opening hours. All PBAP classes fell to low baseline concentrations when the building was unoccupied overnight and at weekendsPeer reviewe

Tree vigour influences secondary growth but not responsiveness to climatic variability in Holm oak

Many tree species from Mediterranean regions have started to show increased rates of crown defoliation, reduced groth, and dieback associated with the increase in temperatures and changes in the frequency and intensity of drought events experienced during the last decades. In this regard, Quercus ilex L. subsp. ballota (Desf.) (Holm oak), despite being a drought-tolerant species widely distributed in the Mediterranean basin, it has recently started to show acute signs of decline, extended areas from Spain being affected. However, few studies have assessed the role of climatic variability (i.e., temperature, precipitation, and drought) on the decline and resilience of Holm oak. Here, we measured secondary growth of seventy Holm oaks from a coppice stand located in central Spain. Sampled trees had different stages of decline, so they were classified into four vigour groups considering their crown foliar lost: healthy (0%), low defoliated (25%), highly defoliated (25 70%), and dying (70 100%). Our results showed that during the study period (1980 2009) the highly defoliated and dying Holm oaks grew significantly less than their healthy and low defoliated neighbours, suggesting permanent growth reduction in the less vigorous individuals. Despite these differences, all four vigour groups showed similar responses to climatic variations, especially during winter and late spring early summer seasons, and similar resilience after severe drought events, managing to significantly recover to pre-drought growth rates after only two years. Our findings, hence, illustrate that tree vigour influences secondary growth but not responsiveness to climatic variability in Holm oak. Still, as reduced growth rates are frequently associated with the process of tree mortality, we conclude that the less vigorous Holm oaks might not be able to cope with future water stress conditions, leading to increased mortality rates among this emblematic Mediterranean specie

Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel

A major use of the 1000 Genomes Project (1000GP) data is genotype imputation in genome-wide association studies (GWAS). Here we develop a method to estimate haplotypes from low-coverage sequencing data that can take advantage of single-nucleotide polymorphism (SNP) microarray genotypes on the same samples. First the SNP array data are phased to build a backbone (or 'scaffold') of haplotypes across each chromosome. We then phase the sequence data 'onto' this haplotype scaffold. This approach can take advantage of relatedness between sequenced and non-sequenced samples to improve accuracy. We use this method to create a new 1000GP haplotype reference set for use by the human genetic community. Using a set of validation genotypes at SNP and bi-allelic indels we show that these haplotypes have lower genotype discordance and improved imputation performance into downstream GWAS samples, especially at low-frequency variants. © 2014 Macmillan Publishers Limited. All rights reserved

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Relationship of edge localized mode burst times with divertor flux loop signal phase in JET

A phase relationship is identified between sequential edge localized modes (ELMs) occurrence times in a set of H-mode tokamak plasmas to the voltage measured in full flux azimuthal loops in the divertor region. We focus on plasmas in the Joint European Torus where a steady H-mode is sustained over several seconds, during which ELMs are observed in the Be II emission at the divertor. The ELMs analysed arise from intrinsic ELMing, in that there is no deliberate intent to control the ELMing process by external means. We use ELM timings derived from the Be II signal to perform direct time domain analysis of the full flux loop VLD2 and VLD3 signals, which provide a high cadence global measurement proportional to the voltage induced by changes in poloidal magnetic flux. Specifically, we examine how the time interval between pairs of successive ELMs is linked to the time-evolving phase of the full flux loop signals. Each ELM produces a clear early pulse in the full flux loop signals, whose peak time is used to condition our analysis. The arrival time of the following ELM, relative to this pulse, is found to fall into one of two categories: (i) prompt ELMs, which are directly paced by the initial response seen in the flux loop signals; and (ii) all other ELMs, which occur after the initial response of the full flux loop signals has decayed in amplitude. The times at which ELMs in category (ii) occur, relative to the first ELM of the pair, are clustered at times when the instantaneous phase of the full flux loop signal is close to its value at the time of the first ELM

International consensus statement for the screening, diagnosis, and treatment of adolescents with concurrent Attention-Deficit/Hyperactivity Disorder and substance use disorder

Education and Child Studie

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

The fluorescence properties of aerosol larger than 0.8 mu m in urban and tropical rainforest locations

Original article can be found at : http://www.atmos-chem-phys.net/ Copyright the Authors 2011. This work is distributed under the Creative Commons Attribution 3.0 License.UV-LIF measurements were performed on ambient aerosol in Manchester, UK (urban city centre, winter) and Borneo, Malaysia (remote, tropical) using a Wide Issue Bioaerosol Spectrometer, version 3 (WIBS3). These sites are taken to represent environments with minor and significant primary biological aerosol (PBA) influences respectively, and the urban dataset describes the fluorescent background aerosol against which PBA must be identified by researchers using LIF. The ensemble aerosol at both sites was characterised over 2-3 weeks by measuring the fluorescence intensity and optical equivalent diameter (D(P)) of single particles sized 0.8 = 1 mu m. The WIBS3 features three fluorescence channels: the emission following a 280 nm excitation is recorded at 310-400 nm (channel F1) and 400-600 nm (F2), and fluorescence excited at 350 nm is detected at 400-600 nm (F3). In Manchester the primary size mode of fluorescent and non-fluorescent material was present at 0.8-1.2 mu m, with a secondary fluorescent mode at 2-4 mu m. In Borneo non-fluorescent material peaked at 0.8-1.2 mu m and fluorescent at 3-4 mu m. Agreement between fluorescent number concentrations in each channel differed at the two sites, with F1 and F3 reporting similar concentrations in Borneo but F3 outnumbering F1 by a factor of 2-3 across the size spectrum in Manchester. The fluorescence intensity in each channel generally rose with D(P) at both sites with the exception of F1 intensity in Manchester, which peaked at D(P) = 4 mu m, causing a divergence between F1 and F3 intensity at larger D(P). This divergence and the differing fluorescent particle concentrations demonstrate the additional discrimination provided by the F1 channel in Manchester. The relationships between fluorescence intensities in different pairs of channels were also investigated as a function of D(P). Differences between these metrics were apparent at each site and provide some distinction between the two datasets. Finally, particle selection criteria based on the Borneo dataset were applied to identify a median concentration of 10 "Borneo-like" fluorescent particles per litre in Manchester.Peer reviewe