Using Machine-Learning to Optimize phase contrast in a Low-Cost Cellphone Microscope

Cellphones equipped with high-quality cameras and powerful CPUs as well as GPUs are widespread. This opens new prospects to use such existing computational and imaging resources to perform medical diagnosis in developing countries at a very low cost. Many relevant samples, like biological cells or waterborn parasites, are almost fully transparent. As they do not exhibit absorption, but alter the light's phase only, they are almost invisible in brightfield microscopy. Expensive equipment and procedures for microscopic contrasting or sample staining often are not available. By applying machine-learning techniques, such as a convolutional neural network (CNN), it is possible to learn a relationship between samples to be examined and its optimal light source shapes, in order to increase e.g. phase contrast, from a given dataset to enable real-time applications. For the experimental setup, we developed a 3D-printed smartphone microscope for less than 100 \$ using off-the-shelf components only such as a low-cost video projector. The fully automated system assures true Koehler illumination with an LCD as the condenser aperture and a reversed smartphone lens as the microscope objective. We show that the effect of a varied light source shape, using the pre-trained CNN, does not only improve the phase contrast, but also the impression of an improvement in optical resolution without adding any special optics, as demonstrated by measurements

Using Machine-Learning to Optimize phase contrast in a Low-Cost Cellphone Microscope

Cellphones equipped with high-quality cameras and powerful CPUs as well as GPUs are widespread. This opens new prospects to use such existing computational and imaging resources to perform medical diagnosis in developing countries at a very low cost. Many relevant samples, like biological cells or waterborn parasites, are almost fully transparent. As they do not exhibit absorption, but alter the light's phase only, they are almost invisible in brightfield microscopy. Expensive equipment and procedures for microscopic contrasting or sample staining often are not available. By applying machine-learning techniques, such as a convolutional neural network (CNN), it is possible to learn a relationship between samples to be examined and its optimal light source shapes, in order to increase e.g. phase contrast, from a given dataset to enable real-time applications. For the experimental setup, we developed a 3D-printed smartphone microscope for less than 100 \$ using off-the-shelf components only such as a low-cost video projector. The fully automated system assures true Koehler illumination with an LCD as the condenser aperture and a reversed smartphone lens as the microscope objective. We show that the effect of a varied light source shape, using the pre-trained CNN, does not only improve the phase contrast, but also the impression of an improvement in optical resolution without adding any special optics, as demonstrated by measurements

Geographies of landscape aesthetics: mapping landscape terminology in digitised historical travel accounts of Loch Lomond and the Trossachs

This study spatially analyses aesthetic terms in historical travel accounts of the landscapes of Loch Lomond and the Trossachs from the eighteenth to the twentieth century. We applied a hybrid approach, combining qualitative methods of textual analysis with quantitative techniques of a Geographical Information System (GIS), to a corpus of 38 digitised works featuring a range of historic guidebooks and travelogues. To identify relationships between place names, landscape features and the aesthetic terms beautiful, magnificent, picturesque, romantic and sublime, we first analysed how these terms occurred together in the text. We also used digital terrain model data in GIS to explore relationships between the aesthetic terms and the elevation of place names and landscape features. The results provide evidence that the aesthetic terms magnificent and sublime were applied to describe places and landforms at higher elevations, whilst beautiful, picturesque and romantic were applied to lower-lying regions of the Loch Lomond and the Trossachs landscapes. Our findings illustrate how the cartographic capabilities of GIS, combined with text analysis, can shed light on how landscapes were historically represented in travel literature

Rewilding in the British policy landscape. : A qualitative analysis of policy documents related to rewilding

Acknowledgements The authors would like to thank two anonymous reviewers and the editor for helpful feedback that improved our manuscript. Funding This research was financially supported by the Natural Environment Research Council (NERC) and the University of Aberdeen through QUADRAT DTP.Peer reviewe

Describing and mapping where people experience tranquillity. An exploration based on interviews and Flickr photographs

Peer reviewedPublisher PD

Geographies of landscape aesthetics : mapping landscape terminology in digitised historical travel accounts of Loch Lomond and the Trossachs

Acknowledgements Ogg.: Conceptualisation, Methodology, Formal Analysis, Investigation, Visualisation, Writing –Original Draft Preparation. Wartmann.: Conceptualisation, Supervision, Writing – Review & Editing.Peer reviewedPublisher PD

Investigating sense of place as a cultural ecosystem service in different landscapes through the lens of language

We are grateful for the comments and feedback of three anonymous reviewers. We thank Olga Chesnokova for her help in calculating cosine similarity measures. The research on which this paper is based was financially supported by the cogito foundation through the project ‘How language shapes our sense of place’, grant no. 15-129-R.Peer reviewedPublisher PD

Prolactin Mediated Intracellular Signaling in Mammary Epithelial Cells

Prolactin binds to a member of the cytokine receptor superfamily. The cytoplasmic domain of the prolactin receptor (PrlR)4 displays no enzymatic activity yet prolactin treatment leads to the induction of protein tyrosine phosphorylation. PrlR is associated with JAK2, a protein tyrosine kinase whose activity is stimulated following receptor dimerization. JAK2 subsequently phosphorylates PrlR and other cellular proteins which are recruited to the activated receptor complex. Among the JAK2 substrates is the transcription factor Stat5 whose phosphorylation mediates the transcriptional activation of β-casein gene expression. In this review we discuss the prolactin induced signaling pathways which mediate differentiation of the mammary glan