A primary effect of palmitic acid on mouse oocytes is the disruption of the structure of the endoplasmic reticulum.

Exposure of mouse oocytes to saturated fatty acids such as palmitic acid has been shown to increases lipid content and cause an endoplasmic reticulum stress response and changes in the mitochondrial redox state. The links between these changes, or whether they are prevented by mono-unsaturated fatty acids such as oleic acid is unclear. Here, we have investigated the effects of fatty acids on mouse oocytes, that are maturated in vitro, using coherent anti-Stokes Raman scattering and two-photon fluorescence microscopy. When oocytes were matured in the presence of palmitic acid there were changes in the aggregation pattern and size of lipid droplets. Maturation in palmitic acid alone also caused a distinctive disruption of the endoplasmic reticulum structure. This effect was prevented by incubation of oleic with palmitic acid. In contrast, maturation of mouse oocytes in medium containing palmitic acid was not associated with any significant change in the redox state of mitochondria or the Ca2+ content of intracellular stores. These data suggest that a primary effect of saturated fatty acids such as PA on oocytes, is to disrupt the structure of the endoplasmic reticulum and this is not due to any other effect on mitochondria or Ca2+ stores.

Two-stage algorithms for visually exploring spatio-temporal clustering of avian influenza virus outbreaks in poultry farms

The development of visual tools for the timely identification of spatio-temporal clusters will assist in implementing control measures to prevent further damage. From January 2015 to June 2020, a total number of 1463 avian influenza outbreak farms were detected in Taiwan and further confirmed to be affected by highly pathogenic avian influenza subtype H5Nx. In this study, we adopted two common concepts of spatio-temporal clustering methods, the Knox test and scan statistics, with visual tools to explore the dynamic changes of clustering patterns. Since most (68.6%) of the outbreak farms were detected in 2015, only the data from 2015 was used in this study. The first two-stage algorithm performs the Knox test, which established a threshold of 7 days and identified 11 major clusters in the six counties of southwestern Taiwan, followed by the standard deviational ellipse (SDE) method implemented on each cluster to reveal the transmission direction. The second algorithm applies scan likelihood ratio statistics followed by AGC index to visualize the dynamic changes of the local aggregation pattern of disease clusters at the regional level. Compared to the one-stage aggregation approach, Knox-based and AGC mapping were more sensitive in small-scale spatio-temporal clustering.

Sustainable Urban Development for Older Australians: Understanding the Formation of Naturally Occurring Retirement Communities in the Greater Brisbane Region

As most older Australians prefer to age-in-place, providing sustainable and age-friendly communities poses a significant challenge to urban policymakers. The naturally occurring retirement communities (NORCs) have organically emerged as a collaborative model of care to support older adults to age-in-place, but neither academic research nor government policies recognise this housing option for older Australians. This paper aims to analyse the distributions and temporal patterns of NORCs in the Greater Brisbane Region, Australia, to understand the formation and development of NORCs. The geovisualisation method was employed to identify the distribution changes of NORCs between 2006 and 2016. The Global Moran’s I and Local Moran’s I measures were utilised to analyse the spatial correlation and the clusters of NORCs. The results show that NORCs increased significantly from 2006 to 2016, and their distribution was mainly clustered or co-located along the coastline and Brisbane River areas. The evolvement of NORCs reflected the change of aggregation pattern of older population between 2006 and 2016. Understanding the distribution trend of NORCs informs government policy and decisions in addressing issues of service delivery and community cooperation, and eventually leads to sustainable urban development and successful ageing in place for older Australians.

Landscape Ecological Risk Assessment Based on LUCC—A Case Study of Chaoyang County, China

The ecological environment is suffering from great human disturbance. Scientific assessment of landscape ecological risks can provide scientific guidance for land use management. This study focused on Chaoyang County in China, used ecological risk assessment methods to characterize the impact of land use/land cover (LUCC) change, and revealed the risk aggregation pattern with the help of spatial autocorrelation analysis. The results showed that ecological risk was increased from 2000 to 2010 but decreased from 2010 to 2018. The ecological risk of the Daling River and Xiaoling River basin was at a relatively high level, and low in the northwest and southeast of the study which covered by forest land. Occupying cultivated land for built-up and large-scale deforestation were two of the main factors to contribute to the increase of ecological risk. The distribution of High-High (HH) and Low-Low (LL) risk agglomeration areas was basically the same as risk levels, but the scope is smaller and more precise. Thus, HH and LH risk agglomeration area should be paid more attention to prevent the adverse impact of adjacent areas. Our study gave a novel perspective to investigate the pattern of ecological risk in order for government managers to identify key risk areas.

A Presentation of Ionic Liquids as Lubricants: Some Critical Comments

Ionic liquids (ILs) are liquid materials at room temperature with an ionic intrinsic nature. The electrostatic interactions therefore play a pivotal role in dictating their inner structure, which is then expected to be far from the traditional pattern of classical simple liquids. Therefore, the strength of such interactions and their long-range effects are responsible for the ionic liquid high viscosity, a fact that itself suggests their possible use as lubricants. More interestingly, the possibility to establish a wide scenario of possible interactions with solid surfaces constitutes a specific added value in this use. In this framework, the ionic liquid complex molecular structure and the huge variety of possible interactions cause a complex aggregation pattern which can depend on the presence of the solid surface itself. Although there is plenty of literature focusing on the lubricant properties of ionic liquids and their applications, the aim of this contribution is, instead, to furnish to the reader a panoramic view of this exciting problematic, commenting on interesting and speculative aspects which are sometimes neglected in standard works and trying to furnish an enriched vision of the topic. The present work constitutes an easy-to-read critical point of view which tries to interact with the imagination of readers, hopefully leading to the discovery of novel aspects and interconnections and ultimately stimulating new ideas and research.

Spatial Distribution of Hunting Billbugs (Coleoptera: Curculionidae) in Sod Farms

The hunting billbug, Sphenophorus venatus vestitus Chittenden (Coleoptera: Curculionidae), is an important turfgrass pest, especially in sod farms. S. venatus vestitus larvae feed on the stems and roots of turfgrass. Damaged turfgrass is loosely held together and poses a challenge for machine harvesting. Additionally, the normal growth of turfgrass is affected, especially after winter dormancy. Because S. venatus vestitus larvae are hidden inside the stems or under the soil, larval management is challenging. To improve sampling and management, the spatial distribution patterns of S. venatus vestitus larvae and adults were assessed at four sod farm sites with a history of S. venatus vestitus infestation in central Georgia (USA). The larvae were sampled by soil cores using a hole cutter, whereas adults were collected using pitfall traps for 7 d. The spatial distributions of larvae and adults was analyzed using SADIE and variograms. The SADIE and variogram analyses revealed a significant aggregation pattern for adults, whereas aggregated distributions were detected for larvae with variogram analyses. The average ranges of spatial dependence for larval and adult samples were 3.9 m and 5.4 m, respectively. Interpolated distribution maps were created to visually depict S. venatus vestitus infestation hotspots within the sod farms.

Ricci Curvature-Based Semi-Supervised Learning on an Attributed Network

In recent years, on the basis of drawing lessons from traditional neural network models, people have been paying more and more attention to the design of neural network architectures for processing graph structure data, which are called graph neural networks (GNN). GCN, namely, graph convolution networks, are neural network models in GNN. GCN extends the convolution operation from traditional data (such as images) to graph data, and it is essentially a feature extractor, which aggregates the features of neighborhood nodes into those of target nodes. In the process of aggregating features, GCN uses the Laplacian matrix to assign different importance to the nodes in the neighborhood of the target nodes. Since graph-structured data are inherently non-Euclidean, we seek to use a non-Euclidean mathematical tool, namely, Riemannian geometry, to analyze graphs (networks). In this paper, we present a novel model for semi-supervised learning called the Ricci curvature-based graph convolutional neural network, i.e., RCGCN. The aggregation pattern of RCGCN is inspired by that of GCN. We regard the network as a discrete manifold, and then use Ricci curvature to assign different importance to the nodes within the neighborhood of the target nodes. Ricci curvature is related to the optimal transport distance, which can well reflect the geometric structure of the underlying space of the network. The node importance given by Ricci curvature can better reflect the relationships between the target node and the nodes in the neighborhood. The proposed model scales linearly with the number of edges in the network. Experiments demonstrated that RCGCN achieves a significant performance gain over baseline methods on benchmark datasets.

Patterns of flea infestation in rodents and insectivores from intensified agro-ecosystems, Northwest Spain

Background Fleas frequently infest small mammals and play important vectoring roles in the epidemiology of (re)emerging zoonotic disease. Rodent outbreaks in intensified agro-ecosystems of North-West Spain have been recently linked to periodic zoonotic diseases spillover to local human populations. Obtaining qualitative and quantitative information about the composition and structure of the whole flea and small mammal host coexisting communities is paramount to understand disease transmission cycles and to elucidate the disease-vectoring role of flea species. The aims of this research were to: (i) characterise and quantify the flea community parasiting a small mammal guild in intensive farmlands in North-West Spain; (ii) determine and evaluate patterns of co-infection and the variables that may influence parasitological parameters. Methods We conducted a large-scale survey stratified by season and habitat of fleas parasitizing the small mammal host guild. We report on the prevalence, mean intensity, and mean abundance of flea species parasitizing Microtus arvalis, Apodemus sylvaticus, Mus spretus and Crocidura russula. We also report on aggregation patterns (variance-to-mean ratio and discrepancy index) and co-infection of hosts by different flea species (Fager index) and used generalized linear mixed models to study flea parameter variation according to season, habitat and host sex. Results Three flea species dominated the system: Ctenophthalmus apertus gilcolladoi, Leptopsylla taschenbergi and Nosopsyllus fasciatus. Results showed a high aggregation pattern of fleas in all hosts. All host species in the guild shared C. a. gilcolladoi and N. fasciatus, but L. taschenbergi mainly parasitized mice (M. spretus and A. sylvaticus). We found significant male-biased infestation patterns in mice, seasonal variations in flea abundances for all rodent hosts (M. arvalis, M. spretus and A. sylvaticus), and relatively lower infestation values for voles inhabiting alfalfas. Simultaneous co-infections occurred in a third of all hosts, and N. fasciatus was the most common flea co-infecting small mammal hosts. Conclusions The generalist N. fasciatus and C. a. gilcolladoi dominated the flea community, and a high percentage of co-infections with both species occurred within the small mammal guild. Nosopsyllus fasciatus may show higher competence of inter-specific transmission, and future research should unravel its role in the circulation of rodent-borne zoonoses.

Analysis on spatial distribution pattern of football fields: A case study in Wuhan, China

In order to promote the sustainable development of sports facilities, the statistical data of football fields in 13 districts of Wuhan city were selected. Based on geographic information system (GIS) and exploratory spatial data analysis (ESDA) technology, this paper analyzed the global and local autocorrelation of the number of football fields per capita in Wuhan city. The results indicate that: (1) Comparing to the new districts in Wuhan, the number of football fields per capita in the central districts was relatively few. (2) In the global scale, the number of football fields per capita in Wuhan presented a spatial aggregation pattern. (3) In the local scale, the regional discrepancy and spatial clusters were confirmed in the local spatial autocorrelation analysis for football fields in Wuhan. At the same time, the research results could provide reasonable references for the planning of football field facilities.