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The beautiful focus of this film is a quilt made in c.1890 in Swaledale and its journey through the generations of a family and on to the Quilters’ Guild collection in the early twenty-first century. It conveys how textiles hold powerful emotions for their makers and the relatives who have inherited them, and communicates the pleasures of hand quilting in the past and today. It also shows how inherited objects offer insights into our history, reflecting on the way inherited quilts provide insights into changing regional patterns of women’s work and lives. With Deborah McGuire and Joanne Begiato.

Big data analytics can be used by smart cities to improve their citizens’ liveability, health, and wellbeing. Social surveys and also social media can be employed to engage with their communities, and these can require sophisticated analysis techniques. This research was focused on carrying out a sentiment analysis from social surveys. Data analysis techniques using RStudio and Python were applied to several open-source datasets, which included the 2018 Social Indicators Survey dataset published by the City of Melbourne (CoM) and the Casey Next short survey 2016 dataset published by the City of Casey (CoC). The qualitative nature of the CoC dataset responses could produce rich insights using sentiment analysis, unlike the quantitative CoM dataset. RStudio analysis created word cloud visualizations and bar charts for sentiment values. These were then used to inform social media analysis via the Twitter application programming interface. The R codes were all integrated within a Shiny application to create a set of user-friendly interactive web apps that generate sentiment analysis both from the historic survey data and more immediately from the Twitter feeds. The web apps were embedded within a website that provides a customisable solution to estimate sentiment for key issues. Global sentiment was also compared between the social media approach and the 2016 survey dataset analysis and showed some correlation, although there are caveats on the use of social media for sentiment analysis. Further refinement of the methodology is required to improve the social media app and to calibrate it against analysis of recent survey data.

AbstractThe fossil record of marine invertebrates has long fuelled the debate as to whether or not there are limits to global diversity in the sea1–5. Ecological theory states that, as diversity grows and ecological niches are filled, the strengthening of biological interactions imposes limits on diversity6,7. However, the extent to which biological interactions have constrained the growth of diversity over evolutionary time remains an open question1–5,8–11. Here we present a regional diversification model that reproduces the main Phanerozoic eon trends in the global diversity of marine invertebrates after imposing mass extinctions. We find that the dynamics of global diversity are best described by a diversification model that operates widely within the exponential growth regime of a logistic function. A spatially resolved analysis of the ratio of diversity to carrying capacity reveals that less than 2% of the global flooded continental area throughout the Phanerozoic exhibits diversity levels approaching ecological saturation. We attribute the overall increase in global diversity during the Late Mesozoic and Cenozoic eras to the development of diversity hotspots under prolonged conditions of Earth system stability and maximum continental fragmentation. We call this the ‘diversity hotspots hypothesis’, which we propose as a non-mutually exclusive alternative to the hypothesis that the Mesozoic marine revolution led this macroevolutionary trend12,13.

[Review] Lynn Turner, Undine Sellbach and Ron Broglio, editors. The Edinburgh Companion to Animal Studies. Edinburgh University Press, 2018, 2019. 559 pp.

Ceramic containers, intentionally deposited into wetlands, offer detailed insights into Early Neolithic culinary practices. Additionally, they are key for ascertaining the Neolithisation process in Denmark since they appear to form a typo-chronological sequence. Here, we use a combination of organic residue analysis (ORA) of pottery alongside Bayesian chronological modelling of the radiocarbon dates obtained on these vessels to explore the initial stages of votive deposition in wetlands, a practice that stretches from the Mesolithic to the onset of Christianity in Northern Europe. We consider 34 Early-Middle Neolithic (c. 3900–2350 cal BC) ‘bog pots’ from Denmark, of which 20 have ORA data, and 26 have been dated directly. Carbonised surface residues and absorbed lipids from powdered sherds were analysed using a combination of bulk carbon and nitrogen stable isotope analysis, gas chromatography-mass spectrometry (GC–MS) and GC-combustion-isotope ratio MS (GC-CIRMS). The molecular and isotopic compositions of the analysed samples revealed the presence of aquatic, ruminant carcass and dairy fats as well as plant waxes with the majority containing mixtures thereof. Dairy fats were present from the onset of the Funnel Beaker culture, whilst aquatic foods, prevalent at the close of the preceding Mesolithic period, continued to be processed in pottery for the following thousand years.

With the rapid development of the economy and society in recent years, the ecological environment has deteriorated significantly. The governments at all levels, departments, and relevant scholars have begun to pay attention to urban ecological construction and research on urban disaster prevention and mitigation. The concept of resilience has gained widespread attention in this context. However, at present, urban ecological resilience research is still in its infancy, and there are many qualitative but few quantitative studies in terms of assessment methods. This study explores the complex dynamic evolution mechanism of urban ecosystem resilience based on the three resilience characteristics and selects Nanchang, an important ecological barrier in the middle and lower reaches of the Yangtze River and a model area for integrated management of the Great Lakes basin, as an assessment target. This study establishes a quantitative measurement and evaluation framework for urban ecological resilience in three dimensions (resistance, adaptation, and vitality) and conducts a comprehensive evaluation of urban ecosystem resilience. The results show that the trend of land-use change from 1990 to 2020 is mainly characterized by the continuous decrease in arable land and ecological land (forestland, grassland, and water) and the continuous increase in construction land, among which the land-use dynamic attitude of construction land is the largest, reaching 5.33% from 1990 to 2005. During the study period, the overall ecosystem resilience of Nanchang showed a gradual decline and was always at a moderate-to-low level, with a long-term distribution pattern of “low in the middle and high in the surrounding areas” and clear spatial heterogeneity. This study helps clarify the security status of the regional ecosystem and provides a reference for exploring the complex dynamic evolution mechanism of ecological resilience.

A pooling operation is essential for effective graph-level representation learning, where the node drop pooling has become one mainstream graph pooling technology. However, current node drop pooling methods usually keep the top-k nodes according to their significance scores, which ignore the graph diversity in terms of the node features and the graph structures, thus resulting in suboptimal graph-level representations. To address the aforementioned issue, we propose a novel plug-and-play score scheme and refer to it as MID, which consists of a \textbf{M}ultidimensional score space with two operations, \textit{i.e.}, fl\textbf{I}pscore and \textbf{D}ropscore. Specifically, the multidimensional score space depicts the significance of nodes through multiple criteria; the flipscore encourages the maintenance of dissimilar node features; and the dropscore forces the model to notice diverse graph structures instead of being stuck in significant local structures. To evaluate the effectiveness of our proposed MID, we perform extensive experiments by applying it to a wide variety of recent node drop pooling methods, including TopKPool, SAGPool, GSAPool, and ASAP. Specifically, the proposed MID can efficiently and consistently achieve about 2.8\% average improvements over the above four methods on seventeen real-world graph classification datasets, including four social datasets (IMDB-BINARY, IMDB-MULTI, REDDIT-BINARY, and COLLAB), and thirteen biochemical datasets (D\&D, PROTEINS, NCI1, MUTAG, PTC-MR, NCI109, ENZYMES, MUTAGENICITY, FRANKENSTEIN, HIV, BBBP, TOXCAST, and TOX21). Code is available at~\url{https://github.com/whuchuang/mid}. 14 pages, 14 figures