Visual identification of individual Holstein-Friesian cattle via deep metric learning

Holstein-Friesian cattle exhibit individually-characteristic black and white coat patterns visually akin to those arising from Turing's reaction-diffusion systems. This work takes advantage of these natural markings in order to automate visual detection and biometric identification of individual Holstein-Friesians via convolutional neural networks and deep metric learning techniques. Existing approaches rely on markings, tags or wearables with a variety of maintenance requirements, whereas we present a totally hands-off method for the automated detection, localisation, and identification of individual animals from overhead imaging in an open herd setting, i.e. where new additions to the herd are identified without re-training. We propose the use of SoftMax-based reciprocal triplet loss to address the identification problem and evaluate the techniques in detail against fixed herd paradigms. We find that deep metric learning systems show strong performance even when many cattle unseen during system training are to be identified and re-identified - achieving 98.2% accuracy when trained on just half of the population. This work paves the way for facilitating the non-intrusive monitoring of cattle applicable to precision farming and surveillance for automated productivity, health and welfare monitoring, and to veterinary research such as behavioural analysis, disease outbreak tracing, and more. Key parts of the source code, network weights and underpinning datasets are available publicly.Comment: 37 pages, 14 figures, 2 tables; Submitted to Computers and Electronics in Agriculture; Source code and network weights available at https://github.com/CWOA/MetricLearningIdentification; OpenCows2020 dataset available at https://doi.org/10.5523/bris.10m32xl88x2b61zlkkgz3fml1

Universal Bovine Identification via Depth Data and Deep Metric Learning

This paper proposes and evaluates, for the first time, a top-down (dorsal view), depth-only deep learning system for accurately identifying individual cattle and provides associated code, datasets, and training weights for immediate reproducibility. An increase in herd size skews the cow-to-human ratio at the farm and makes the manual monitoring of individuals more challenging. Therefore, real-time cattle identification is essential for the farms and a crucial step towards precision livestock farming. Underpinned by our previous work, this paper introduces a deep-metric learning method for cattle identification using depth data from an off-the-shelf 3D camera. The method relies on CNN and MLP backbones that learn well-generalised embedding spaces from the body shape to differentiate individuals -- requiring neither species-specific coat patterns nor close-up muzzle prints for operation. The network embeddings are clustered using a simple algorithm such as $k$-NN for highly accurate identification, thus eliminating the need to retrain the network for enrolling new individuals. We evaluate two backbone architectures, ResNet, as previously used to identify Holstein Friesians using RGB images, and PointNet, which is specialised to operate on 3D point clouds. We also present CowDepth2023, a new dataset containing 21,490 synchronised colour-depth image pairs of 99 cows, to evaluate the backbones. Both ResNet and PointNet architectures, which consume depth maps and point clouds, respectively, led to high accuracy that is on par with the coat pattern-based backbone

Inducible deletion of CD28 prior to secondary nippostrongylus brasiliensis infection impairs worm expulsion and recall of protective memory CD4 (+) T cell responses

IL-13 driven Th2 immunity is indispensable for host protection against infection with the gastrointestinal nematode Nippostronglus brasiliensis. Disruption of CD28 mediated costimulation impairs development of adequate Th2 immunity, showing an importance for CD28 during the initiation of an immune response against this pathogen. In this study, we used global CD28−/− mice and a recently established mouse model that allows for inducible deletion of the cd28 gene by oral administration of tamoxifen (CD28−/loxCre+/−+TM) to resolve the controversy surrounding the requirement of CD28 costimulation for recall of protective memory responses against pathogenic infections. Following primary infection with N. brasiliensis, CD28−/− mice had delayed expulsion of adult worms in the small intestine compared to wild-type C57BL/6 mice that cleared the infection by day 9 post-infection. Delayed expulsion was associated with reduced production of IL-13 and reduced serum levels of antigen specific IgG1 and total IgE. Interestingly, abrogation of CD28 costimulation in CD28−/loxCre+/− mice by oral administration of tamoxifen prior to secondary infection with N. brasiliensis resulted in impaired worm expulsion, similarly to infected CD28−/− mice. This was associated with reduced production of the Th2 cytokines IL-13 and IL-4, diminished serum titres of antigen specific IgG1 and total IgE and a reduced CXCR5+ TFH cell population. Furthermore, total number of CD4+ T cells and B220+ B cells secreting Th1 and Th2 cytokines were significantly reduced in CD28−/− mice and tamoxifen treated CD28−/loxCre+/− mice compared to C57BL/6 mice. Importantly, interfering with CD28 costimulatory signalling before re-infection impaired the recruitment and/or expansion of central and effector memory CD4+ T cells and follicular B cells to the draining lymph node of tamoxifen treated CD28−/loxCre+/− mice. Therefore, it can be concluded that CD28 costimulation is essential for conferring host protection during secondary N. brasiliensis infection

Early indicators of exposure to biological threat agents using host gene profiles in peripheral blood mononuclear cells

<p>Abstract</p> <p>Background</p> <p>Effective prophylaxis and treatment for infections caused by biological threat agents (BTA) rely upon early diagnosis and rapid initiation of therapy. Most methods for identifying pathogens in body fluids and tissues require that the pathogen proliferate to detectable and dangerous levels, thereby delaying diagnosis and treatment, especially during the prelatent stages when symptoms for most BTA are indistinguishable flu-like signs.</p> <p>Methods</p> <p>To detect exposures to the various pathogens more rapidly, especially during these early stages, we evaluated a suite of host responses to biological threat agents using global gene expression profiling on complementary DNA arrays.</p> <p>Results</p> <p>We found that certain gene expression patterns were unique to each pathogen and that other gene changes occurred in response to multiple agents, perhaps relating to the eventual course of illness. Nonhuman primates were exposed to some pathogens and the <it>in vitro</it> and <it>in vivo</it> findings were compared. We found major gene expression changes at the earliest times tested post exposure to aerosolized <it>B. anthracis </it>spores and 30 min post exposure to a bacterial toxin.</p> <p>Conclusion</p> <p>Host gene expression patterns have the potential to serve as diagnostic markers or predict the course of impending illness and may lead to new stage-appropriate therapeutic strategies to ameliorate the devastating effects of exposure to biothreat agents.</p

Metal-Poor Stars and the Chemical Enrichment of the Universe

Metal-poor stars hold the key to our understanding of the origin of the elements and the chemical evolution of the Universe. This chapter describes the process of discovery of these rare stars, the manner in which their surface abundances (produced in supernovae and other evolved stars) are determined from the analysis of their spectra, and the interpretation of their abundance patterns to elucidate questions of origin and evolution. More generally, studies of these stars contribute to other fundamental areas that include nuclear astrophysics, conditions at the earliest times, the nature of the first stars, and the formation and evolution of galaxies -- including our own Milky Way. We illustrate this with results from studies of lithium formed during the Big Bang; of stars dated to within ~1 Gyr of that event; of the most metal-poor stars, with abundance signatures very different from all other stars; and of the build-up of the elements over the first several Gyr. The combination of abundance and kinematic signatures constrains how the Milky Way formed, while recent discoveries of extremely metal-poor stars in the Milky Way's dwarf galaxy satellites constrain the hierarchical build-up of its stellar halo from small dark-matter dominated systems. [abridged]Comment: Book chapter, emulated version, 34 pages; number of references are limited by publisher; to appear in Vol. 5 of textbook "Planets, Stars and Stellar Systems", by Springer, in 201

The global abundance of tree palms

Aim Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location Tropical and subtropical moist forests. Time period Current. Major taxa studied Palms (Arecaceae). Methods We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co‐occurring non‐palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long‐term climate stability. Life‐form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non‐tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above‐ground biomass, but the magnitude and direction of the effect require additional work. Conclusions Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests