7 research outputs found
Chalk Streams of the Future report.pdf
No full textChalk streams of the future: The effects of climate change on biodiversity in England’s iconic river ecosystems.
A report written by Rachel Stubbington and Jake Dimon (Nottingham Trent University; NTU), and Judy England and Glenn Watts (Environment Agency; EA), with design by
bwa design.
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From Consumption to Prosumption - Operational Cost Optimization for Refrigeration System With Heat Waste Recovery
No full textImplementation of liquid cooling transforms a refrigeration system into a combined cooling and heating system. Reclaimed heat can be used for building heating purposes or can be sold. Carbon dioxide based refrigeration systems are considered to have a particularly high potential for becoming ecient heat energy producers. In this paper a CO2 system that operates in the subcritical region is examined. Modelling approach is presented, and used for operation optimisation by way of non-linear model predictive control techniques. Assuming that the heat is sold when using both objective functions, it turns out that the system have negative operational cost. In case when Cost Minimization objective function is used daily revenue is about 7:9 [eur], for Prosumption one it is 11:9 [eur]
The silent extinction of freshwater mussels in Portugal
No full textFreshwater mussels are one of the most threatened animal groups in the world. In the European Union, threatened and protected mussel species are not adequately monitored, while species considered to be common and widespread receive even less attention. This is particularly worrying in the Mediterranean region, where species endemism is high and freshwater habitats are severely affected by water scarcity. In the absence of hard data on population trends, we report here a long-term comparison of freshwater mussel assemblages at 132 sites covering 15 different hydrological basins in Portugal. This study reveals a widespread decline of 60 % in the number of sites and 67 % in the overall abundance of freshwater mussels across Portugal over the last 20 years, indicating that all species are rapidly declining and threatened with extinction. These results show that current legislation and conservation measures are largely ineffective and highlight the importance of updating the Habitats Directive to enforce standard monitoring protocols for threatened species in the European Union and to extend monitoring to other freshwater species thought to be common and widespread. Efficient water management, restrictions on irrigation expansion in important biodiversity areas, mitigation of hydrological changes and loss of aquatic habitat connectivity caused by physical alterations are urgently needed to reverse these declining population trends. For the severely endangered species Margaritifera margaritifera, Potomida littoralis, and Unio tumidiformis, where populations are now critically low, more urgent action is needed, such as ex-situ conservation, protection of remaining populations and large-scale habitat restoration.We would like to thank Jake Dimon, José Tourais, Filipe Rolo, and Elza Fonseca for their help in the surveys. This research was developed under the project EdgeOmics - Freshwater Bivalves at the edge: Adaptation genomics under climate-change scenarios (PTDC/CTA-AMB/3065/2020) funded by the Portuguese Foundation for Science and Technology (FCT) through national funds. FCT also funded MLL under
contract 2020.03608.CEECIND, EF under contract CEECINST/00027/2021/CP2789/CT0003, AGS under the grants SFRH/BD/137935/2018 and COVID/DB/152933/2022, and JGN under the grant 2020.04637.
BD. The baseline survey was funded by the project “Documentos Estruturantes” (POA 1.100021) of the Instituto da Conservaçã da Natureza
The freshwater mussels (Bivalvia: Unionida) of Java: first island-wide assessment reveals new species, endemism, and urgent conservation needs
No full textThe freshwater mussel (Bivalvia: Unionida) fauna of Java has never been examined comprehensively in a modern context, leading to a lack of a species inventory and knowledge on current species distributions and how these have been impacted by human activities over the past 70 years. In 2022/23, we surveyed 66 sites across 18 river basins of Java, and one site near the Rectidens sumatrensis type locality in Sumatra. Species were delineated and identified through an integrated morphological–molecular approach using COI-based phylogenetic and haplotype analyses. We found and sequenced 76 populations (= species-site occurrences) across 42 sites and 16 river basins, comprising eight native and one non-native species. Whilst confirming the presence of Lens contradens, Physunio superbus, Pilsbryoconcha exilis, Pseudodon vondembuschianus stat. rev., Rectidens orientalis comb. rev., and Sinanodonta pacifica (non-native), we provide the first records of Lens lugens, Pilsbryoconcha linguaeformis, and Pseudodon cokelatus sp. nov. Rectidens sumatrensis is absent from Java. Comparing our data to historical records indicates considerable population losses of most native species driven by the steep increase in urbanization, industrialization, mining, and other human activities. Conservation actions are urgently needed, particularly in the species-rich Bengawan Solo and Brantas River basins
Automated detection and staging of malaria parasites from cytological smears using convolutional neural networks
No full textMicroscopic examination of blood smears remains the gold standard for laboratory inspection and diagnosis of malaria. Smear inspection is, however, time consuming and dependent on trained microscopists with results varying in accuracy. We sought to develop an automated image analysis method to improve accuracy and standardisation of smear inspection that retains capacity for expert confirmation and image archiving. Here we present a machine-learning method that achieves red blood cell (RBC) detection, differentiation between infected/uninfected cells and parasite life stage categorisation from unprocessed, heterogeneous smear images. Based on a pre-trained Faster Region-Based Convolutional Neural Networks (R-CNN) model for RBC detection, our model performs accurately, with average precision of 0.99 at an intersection-over-union threshold of 0.5. Application of a residual neural network (ResNet)-50 model to infected cells also performs accurately, with an area under the receiver operating characteristic curve of 0.98. Lastly, combining our method with a regression model successfully recapitulates intra-erythrocytic developmental cycle with accurate lifecycle stage categorisation. Combined with a mobile-friendly web-based interface, called PlasmoCount, our method permits rapid navigation through and review of results for quality assurance. By standardising assessment of Giemsa smears, our method markedly improves inspection reproducibility and presents a realistic route to both routine lab but also future field-based automated malaria diagnosis
