Contrasting Distributions of Urban Green Infrastructure across Social and Ethno-racial Groups

Links between urban green infrastructure (UGI) and public health benefits are becoming well established. Despite this, how UGI is distributed varies widely. Although not a universal finding, sectors of society that are disadvantaged often suffer from poor provision, something which might be due to which UGI are examined. We assess the distribution of street trees and public greenspaces (two types of publicly-owned and accessible UGI) across the city of Bradford, UK which is characterised by high levels of inequality and variation in ethno-racial background. We do this through statistical and spatial analyses. Street tree density was distributed unevenly and was highest in neighbourhoods with a high proportion of Asian/Asian British residents and with lower socio-economic status. Conversely, neighbourhoods with better access to public greenspaces were characterised by high income and/or a high proportion of White households. While the quality of public greenspace was spatially clustered, there were only limited spatial associations with ethno-racial group or socio-economic status. Population density was a key determinant of the distribution of UGI, suggesting understanding UGI distributions should also focus on urban form. Nevertheless, within the same city we show that equitable distribution of UGI differs according to the form and characteristics of UGI. To fully realise the public health benefits of UGI, it is necessary to map provision and understand the causal drivers of unequal distributions. This would facilitate interventions that promote equitable distributions of UGI based on the needs of the target populations

An evaluation of learning analytics to identify exploratory dialogue in online discussions

Social learning analytics are concerned with the process of knowledge construction as learners build knowledge together in their social and cultural environments. One of the most important tools employed during this process is language. In this paper we take exploratory dialogue, a joint form of co-reasoning, to be an external indicator that learning is taking place. Using techniques developed within the field of computational linguistics, we build on previous work using cue phrases to identify exploratory dialogue within online discussion. Automatic detection of this type of dialogue is framed as a binary classification task that labels each contribution to an online discussion as exploratory or non-exploratory. We describe the development of a self-training framework that employs discourse features and topical features for classification by integrating both cue-phrase matching and k-nearest neighbour classification. Experiments with a corpus constructed from the archive of a two-day online conference show that our proposed framework outperforms other approaches. A classifier developed using the self-training framework is able to make useful distinctions between the learning dialogue taking place at different times within an online conference as well as between the contributions of individual participants

Music emotion recognition based on segment-level two-stage learning

AbstractIn most Music Emotion Recognition (MER) tasks, researchers tend to use supervised learning models based on music features and corresponding annotation. However, few researchers have considered applying unsupervised learning approaches to labeled data except for feature representation. In this paper, we propose a segment-based two-stage model combining unsupervised learning and supervised learning. In the first stage, we split each music excerpt into contiguous segments and then utilize an autoencoder to generate segment-level feature representation. In the second stage, we feed these time-series music segments to a bidirectional long short-term memory deep learning model to achieve the final music emotion classification. Compared with the whole music excerpts, segments as model inputs could be the proper granularity for model training and augment the scale of training samples to reduce the risk of overfitting during deep learning. Apart from that, we also apply frequency and time masking to segment-level inputs in the unsupervised learning part to enhance training performance. We evaluate our model on two datasets. The results show that our model outperforms state-of-the-art models, some of which even use multimodal architectures. And the performance comparison also evidences the effectiveness of audio segmentation and the autoencoder with masking in an unsupervised way.</jats:p

Biogenesis of the inner membrane complex is dependent on vesicular transport by the alveolate specific GTPase Rab11B

Apicomplexan parasites belong to a recently recognised group of protozoa referred to as Alveolata. These protists contain membranous sacs (alveoli) beneath the plasma membrane, termed the Inner Membrane Complex (IMC) in the case of Apicomplexa. During parasite replication the IMC is formed de novo within the mother cell in a process described as internal budding. We hypothesized that an alveolate specific factor is involved in the specific transport of vesicles from the Golgi to the IMC and identified the small GTPase Rab11B as an alveolate specific Rab-GTPase that localises to the growing end of the IMC during replication of Toxoplasma gondii. Conditional interference with Rab11B function leads to a profound defect in IMC biogenesis, indicating that Rab11B is required for the transport of Golgi derived vesicles to the nascent IMC of the daughter cell. Curiously, a block in IMC biogenesis did not affect formation of sub-pellicular microtubules, indicating that IMC biogenesis and formation of sub-pellicular microtubules is not mechanistically linked. We propose a model where Rab11B specifically transports vesicles derived from the Golgi to the immature IMC of the growing daughter parasites

Multidirectional chromosome painting substantiates the occurrence of extensive genomic reshuffling within Accipitriformes.

BACKGROUND: Previous cross-species painting studies with probes from chicken (Gallus gallus) chromosomes 1-10 and a paint pool of nineteen microchromosomes have revealed that the drastic karyotypic reorganization in Accipitridae is due to extensive synteny disruptions and associations. However, the number of synteny association events and identities of microchromosomes involved in such synteny associations remain undefined, due to the lack of paint probes derived from individual chicken microchromosomes. Moreover, no genome-wide homology map between Accipitridae species and other avian species with atypical karyotype organization has been reported till now, and the karyotype evolution within Accipitriformes remains unclear. RESULTS: To delineate the synteny-conserved segments in Accipitridae, a set of painting probes for the griffon vulture, Gyps fulvus (2n = 66) was generated from flow-sorted chromosomes. Together with previous generated probes from the stone curlew, Burhinus oedicnemus (2n = 42), a Charadriiformes species with atypical karyotype organization, we conducted multidirectional chromosome painting, including reciprocal chromosome painting between B. oedicnemus and G. fulvus and cross-species chromosome painting between B. oedicnemus and two accipitrid species (the Himalayan griffon, G. himalayensis 2n = 66, and the common buzzard, Buteo buteo, 2n = 68). In doing so, genome-wide homology maps between B. oedicnemus and three Accipitridae species were established. From there, a cladistic analysis using chromosomal characters and mapping of chromosomal changes on a consensus molecular phylogeny were conducted in order to search for cytogenetic signatures for different lineages within Accipitriformes. CONCLUSION: Our study confirmed that the genomes of the diurnal birds of prey, especially the genomes of species in Accipitriformes excluding Cathartidae, have been extensively reshuffled when compared to other bird lineages. The chromosomal rearrangements involved include both fusions and fissions. Our chromosome painting data indicated that the Palearctic common buzzard (BBU) shared several common chromosomal rearrangements with some Old World vultures, and was found to be more closely related to other Accipitridae than to Neotropical buteonine raptors from the karyotypic perspective. Using both a chromosome-based cladistic analysis as well as by mapping of chromosomal differences onto a molecular-based phylogenetic tree, we revealed a number of potential cytogenetic signatures that support the clade of Pandionidae (PHA) + Accipitridae. In addition, our cladistic analysis using chromosomal characters appears to support the placement of osprey (PHA) in Accipitridae

Fluorescent labelling and biodistribution of latex nanoparticles formed by surfactant-free RAFT emulsion polymerisation

We report the preparation of a novel range of functional polyacrylamide stabilised polystyrene nanoparticles, obtained by surfactant-free reversible addition-fragmentation chain transfer (RAFT) emulsion polymerisation, their fluorescent tagging, cellular uptake and biodistribution. We show the versatility of the RAFT emulsion process for the design of functional nanoparticles of well-defined size that can be used as drug delivery vectors. Functionalisation with a fluorescent tag offers a useful visualisation tool for tracing, localisation and clearance studies of these carriers in biological models. The studies were carried out by labelling the sterically stabilised latex particles chemically with rhodamine B. The fluorescent particles were incubated in a healthy human renal proximal tubular cell line model, and intravenously injected into a mouse model. Cellular localisation and biodistribution of these particles on the biological models were explored

Reservoir dynamics of rabies in Southeast Tanzania and the roles of cross-species transmission and domestic dog vaccination

1) Understanding the role of different species in the transmission of multi-host pathogens, such as rabies virus, is vital for effective control strategies. Across most of sub-Saharan Africa domestic dogs (Canis familiaris) are considered the reservoir for rabies, but the role of wildlife has been long debated. Here we explore the multi-host transmission dynamics of rabies across southeast Tanzania. 2) Between January 2011 and July 2019 data on probable rabies cases were collected in the regions of Lindi and Mtwara. Hospital records of animal-bite patients presenting to healthcare facilities were used as sentinels for animal contact tracing. The timing, location and species of probable rabid animals was used to reconstruct transmission trees to infer who infected whom and the relative frequencies of within-and between-species transmission. 3) During the study, 688 probable human rabies exposures were identified, resulting in 47 deaths. Of these exposures, 389 were from domestic dogs (56.5%) and 262 from jackals (38.1%). Over the same period 549 probable animal rabies cases were traced: 303 in domestic dogs (55.2%) and 221 in jackals (40.3%). 4) Although dog-to-dog transmission was most commonly inferred (40.5% of transmission events), a third of inferred events involved wildlife-to-wildlife transmission (32.6%) and evidence suggested some sustained transmission chains within jackal populations. 5) A steady decline in probable rabies cases in both humans and animals coincided with the implementation of widespread domestic dog vaccination during the first six years of the study. Following the lapse of this programme dog rabies cases began to increase in one of the northernmost districts. 6) Synthesis and applications: in southeast Tanzania, despite a relatively high incidence of rabies in wildlife and evidence of wildlife-to-wildlife transmission, domestic dogs remain essential to the reservoir of infection. Continued dog vaccination alongside improved surveillance would allow a fuller understanding of the role of wildlife in maintaining transmission in this area. Nonetheless, dog vaccination clearly suppressed rabies in both domestic dog and wildlife populations, reducing both public health and conservation risks and, if sustained, has potential to eliminate rabies from this region

Performance and specific emissions contours throughout the operating range of hydrogen-fueled compression ignition engine with diesel and RME pilot fuels

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)This paper presents the performance and emissions contours of a hydrogen dual fueled compression ignition (CI) engine with two pilot fuels (diesel and rapeseed methyl ester), and compares the performance and emissions iso-contours of diesel and rapeseed methyl ester (RME) single fueling with diesel and RME piloted hydrogen dual fueling throughout the engines operating speed and power range. The collected data have been used to produce iso-contours of thermal efficiency, volumetric efficiency, specific oxides of nitrogen (NO X ), specific hydrocarbons (HC) and specific carbon dioxide (CO2) on a power-speed plane. The performance and emission maps are experimentally investigated, compared, and critically discussed. Apart from medium loads at lower and medium speeds with diesel piloted hydrogen combustion, dual fueling produced lower thermal efficiency everywhere across the map. For diesel and RME single fueling the maximum specific NO X emissions are centered at the mid speed, mid power region. Hydrogen dual fueling produced higher specific NO X with both pilot fuels as compared to their respective single fueling operations. The range, location and trends of specific NO X varied significantly when compared to single fueling cases. The volumetric efficiency is discussed in detail with the implications of manifold injection of hydrogen analyzed with the conclusions drawn.Peer reviewedFinal Published versio

Detection of associations with rare and common SNPs for quantitative traits: a nonparametric Bayes-based approach

We propose a nonparametric Bayes-based clustering algorithm to detect associations with rare and common single-nucleotide polymorphisms (SNPs) for quantitative traits. Unlike current methods, our approach identifies associations with rare genetic variants at the variant level, not the gene level. In this method, we use a Dirichlet process prior for the distribution of SNP-specific regression coefficients, conduct hierarchical clustering with a distance measure derived from posterior pairwise probabilities of two SNPs having the same regression coefficient, and explore data-driven approaches to select the number of clusters. SNPs falling inside the largest cluster have relatively low or close to zero estimates of regression coefficients and are considered not associated with the trait. SNPs falling outside the largest cluster have relatively high estimates of regression coefficients and are considered potential risk variants. Using the data from the Genetic Analysis Workshop 17, we successfully detected associations with both rare and common SNPs for a quantitative trait. We conclude that our method provides a novel and broadly applicable strategy for obtaining association results with a reasonably low proportion of false discovery and that it can be routinely used in resequencing studies