Forgotten voices: reflections on Latvia during World War Two

The occasion of the 90th anniversary of Latvia’s declaration of independence seemed a suitable occasion to reflect on this author’s decade long commitment to studying the history of Latvia during the Second World War. In 2003 Routledge published Between Stalin and Hitler: Class War and Race War on the Dvina, 1940-46, a detailed case study of Latgale under Soviet and Nazi rule. Since then, two articles have appeared on the National Partisans: “Divided We Fall: Divisions within the National Partisans of Vidzeme and Latgale, Fall 1945”, Journal of Baltic Studies 38/2 2007 and “Latvia’s Democratic Resistance: a Forgotten Episode from the Second World War”, European History Quarterly 39/2 2009. Prior to that, in January 2004, there was also a short paper to the XIII Scientific Readings of the Humanities Faculty, Daugavpils University, on the subject “From Source to Person: the Case of Jānis Niedre”, published in Proceedings of the 13th International Scientific Readings of the Faculty of Humanities. History VII (Saule, Daugavpils 2004). These studies all focus on the power of the great ideologies of the twentieth century and the way those ideologies could justify the abandonment of accepted morality. Yet they also say something else about ideology: the years of Soviet and now post-Soviet historiography have drowned out the voices of those who did not quite fit in with the dominant ideologies of the time. The aim of this short paper, therefore, is to restore to the historical record the voices of some of those who have been marginalised or forgotten. Three examples are taken: the case of Jānis Niedre; the demands of Latvia’s former Red Partisans; and the decisions taken by many, possibly a majority of Latvia

LSE RB feature essay: the centenary of the Russian Revolution by Geoffrey Swain

2017 marks the centenary of the Russian Revolution, which served as the inspiration for the recent LSE Literary Festival on the theme of ‘Revolution’. Following the publication of his new book, A Short History of the Russian Revolution (IB Tauris, 2017), Geoffrey Swain reflects on the events of October 2017, challenging the notion that the revolution was largely the result of a Bolshevik coup

The Centenary of the Russian Revolution: New Directions in Research

No abstract available

Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal's movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal specie

Semantic Segmentation for Fully Automated Macrofouling Analysis on Coatings after Field Exposure

Biofouling is a major challenge for sustainable shipping, filter membranes, heat exchangers, and medical devices. The development of fouling-resistant coatings requires the evaluation of their effectiveness. Such an evaluation is usually based on the assessment of fouling progression after different exposure times to the target medium (e.g., salt water). The manual assessment of macrofouling requires expert knowledge about local fouling communities due to high variances in phenotypical appearance, has single-image sampling inaccuracies for certain species, and lacks spatial information. Here we present an approach for automatic image-based macrofouling analysis. We created a dataset with dense labels prepared from field panel images and propose a convolutional network (adapted U-Net) for the semantic segmentation of different macrofouling classes. The establishment of macrofouling localization allows for the generation of a successional model which enables the determination of direct surface attachment and in-depth epibiotic studies.Comment: 33 pages, 10 figure

Forecasting the Impact of Stellar Activity on Transiting Exoplanet Spectra

Exoplanet host star activity, in the form of unocculted starspots or faculae, alters the observed transmission and emission spectra of the exoplanet. This effect can be exacerbated when combining data from different epochs if the stellar photosphere varies between observations due to activity. Here, we present a method to characterize and correct for relative changes due to stellar activity by exploiting multi-epoch (⩾2 visits/transits) observations to place them in a consistent reference frame. Using measurements from portions of the planet's orbit where negligible planet transmission or emission can be assumed, we determine changes to the stellar spectral amplitude. With the analytical methods described here, we predict the impact of stellar variability on transit observations. Supplementing these forecasts with Kepler-measured stellar variabilities for F-, G-, K-, and M-dwarfs, and predicted transit precisions by the James Webb Space Telescope's (JWST) NIRISS, NIRCam, and MIRI, we conclude that stellar activity does not impact infrared transiting exoplanet observations of most presently known or predicted TESS targets by current or near-future platforms, such as JWST, as activity-induced spectral changes are below the measurement precision

Constraining Exoplanet Metallicities and Aerosols with ARIEL: An Independent Study by the Contribution to ARIEL Spectroscopy of Exoplanets (CASE) Team

Launching in 2028, ESA's Atmospheric Remote-sensing Exoplanet Large-survey (ARIEL) survey of $\sim$1000 transiting exoplanets will build on the legacies of Kepler and TESS and complement JWST by placing its high precision exoplanet observations into a large, statistically-significant planetary population context. With continuous 0.5--7.8~$\mu$m coverage from both FGS (0.50--0.55, 0.8--1.0, and 1.0--1.2~$\mu$m photometry; 1.25--1.95~$\mu$m spectroscopy) and AIRS (1.95--7.80~$\mu$m spectroscopy), ARIEL will determine atmospheric compositions and probe planetary formation histories during its 3.5-year mission. NASA's proposed Contribution to ARIEL Spectroscopy of Exoplanets (CASE) would be a subsystem of ARIEL's FGS instrument consisting of two visible-to-infrared detectors, associated readout electronics, and thermal control hardware. FGS, to be built by the Polish Academy of Sciences' Space Research Centre, will provide both fine guiding and visible to near-infrared photometry and spectroscopy, providing powerful diagnostics of atmospheric aerosol contribution and planetary albedo, which play a crucial role in establishing planetary energy balance. The CASE team presents here an independent study of the capabilities of ARIEL to measure exoplanetary metallicities, which probe the conditions of planet formation, and FGS to measure scattering spectral slopes, which indicate if an exoplanet has atmospheric aerosols (clouds and hazes), and geometric albedos, which help establish planetary climate. Our design reference mission simulations show that ARIEL could measure the mass-metallicity relationship of its 1000-planet single-visit sample to $>7.5\sigma$ and that FGS could distinguish between clear, cloudy, and hazy skies and constrain an exoplanet's atmospheric aerosol composition to $>5\sigma$ for hundreds of targets, providing statistically-transformative science for exoplanet atmospheres.Comment: accepted to PASP; 23 pages, 6 figure