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This is the initial release of the research compendium for the article by Tsirintoulaki, K., Matzig, D.N., Riede, F. (2022) "A 2D geometric morphometric assessment of chrono-cultural trends in osseous barbed points of the European Final Palaeolithic and Early Mesolithic" submitted to Open Archaeology. It contains all data and code, and will generate the results as found in the publication. The files hosted at https://github.com/yesdavid/Osseous_Barbed_Points_2D_GMM are the development versions and may have changed since the publication.

This paper, seeks to examine the correlation between stock price and public sentiment expressed through social media. Through twitter scraping and pre- processing, sentiment can be extracted from text. The paper will be based on a heuristic approach to natural language processing. Furthermore, the paper will rely on the most common forms of sentiment analysis, using a rule-based and a machine-learning approach as a starting point and weigh these up against each other. Finally, we will continue with the best performing method, and weigh this up against real market data in a pursuit to find a correlation, should one exist. The paper found a sentiment-to-market accuracy 75%. And the accuracy score utilizing the rules-based approach of 72,72%.

This project will deep into the motives and reasons behind cultural destruction. It will underline the will to entirely wipe off a distinctive group of population and its culture. Taking Syria as our main case given the events of the last decade; centring in the civil war where lives and art have been lost forever, together with the morale of its population, which fled to other countries in big numbers throughout the war. As for the perpetrators, ISIS will be the focus of our project, guilty of intentionally destroying many monuments, especially in Syria. Before explaining and answering to the questions of the project regarding culture, it is more than mandatory to analyse Syria’s history, tribes and regions. After reaching the core of our project and describing the possible reasons behind these actions, the third part of our project, which focuses on the emotional sphere of the victims. War brings with itself grief, loss, damage and destruction to a country and its material environment. To focus on the emotional attachment and emotional damage during this war shall be a matter of discussion nevertheless. We will not only analyse and discuss cultural destruction and the loss for humanity whenever perpetrators decide to damage forever something so important as our, as humans, common and singular past.

Description This package is a helpful wrapper around functions from mainly the Momocs (Bonhomme et al. 2014), EBImage (Pau et al. 2010), and imager (Barthelme et al. 2020) packages. It is designed for the fast and easy extraction of single outline shapes of, for example, stone tools from images containing multiple thereof, such as the ones present in archaeological publications. This release is provided with a testing dataset, using the Morar Quartz Industry image (Credit: Wellcome Collection, https://wellcomecollection.org/works/th7egtfj, distributed under CC BY 4.0). A brief explanation of the workflow and the package functions can be found on github.com/yesdavid/outlineR. References Barthelme et al. 2020: Barthelme, S., Tschumperle, D., Wijffels, J., Assemlal, H. E., & Ochi, S. (2020). imager: Image Processing Library Based on “CImg” (0.42.3) [Computer software]. https://CRAN.R-project.org/package=imager Bonhomme et al. 2014: Bonhomme, V., Picq, S., Gaucherel, C., & Claude, J. (2014). Momocs: Outline Analysis Using R. Journal of Statistical Software, 56(13). https://doi.org/10.18637/jss.v056.i13 Pau et al. 2010: Pau, G., Fuchs, F., Sklyar, O., Boutros, M., & Huber, W. (2010). EBImage—An R package for image processing with applications to cellular phenotypes. Bioinformatics, 26(7), 979–981. https://doi.org/10.1093/bioinformatics/btq046

In the past few months more than a billion people have faced restrictions unlike any seen before. Shops are closed; the death toll is rising; people across the globe have been forced to rise to an extraordinary challenge. But it is important to remember that humans have experienced pandemics before. In this documentary Dan Snow explores some of these previous pandemics and what they can teach us about Covid-19. He talks to Dr James Rogers about what lessons we can learn from WW2.

Dr James Rogers explains how we can draw parallels between the current COVID-19 pandemic and the Second World War, particularly in how humans have responded to an extraordinary challenge.

Historian and broadcaster James Rogers joins us to give a breakdown of the weapons that he believes are the most significant in the history of civilisation, spanning from ancient times to the modern day.

Over the covid-19 lockdown period, Dr James Rogers worked with history teachers and academics to keep the learning going in lockdown. He now has a fantastic range of videos and podcasts available. All content is free to access and is explicitly designed to help teachers and students undertake A-Level and GCSE history revision.Podcast - Slavery and Emancipation in the United States, with Dr Cathrine Armstrong.Podcast - The History of Terrorism - The IRA, with Professor Caroline Kennedy-Pipe.Video - The Rise of Hitler - Hitler, Power, and War, with Ms Laurie Matthews.Video - The Home Front in WW2 - The Butterfly Bombing of Grimsby, with Dr James Rogers.

Online review of The Tesserae Project, a resource that seeks to take advantage of digital corpora to enable the user to find connections between texts. Its web interface allows users to search two texts or corpora from Greek and Latin literature for occurrences of two or more shared words within a line or phrase.

This project was set out to explore the role of the Turing Test in the development of Artificial Intelligence (AI), with emphasis on the historical perspective. This report contains an introductory presentation of the Turing Test and Artificial Intelligence. Furthermore, it presents two methods for analysis. The first method is a quantitative search in extracting the number of results from Google Scholars for search range between 1950 and 2019. The searched terms are ‘Turing Test’ and ‘Artificial Intelligence’. The second method is the one used for the analysis of two case studies, ELIZA and Google Duplex. In exploring the historical development, ELIZA is an early research topic from 1966 and Google Duplex is a contemporary project from 2018. This report concludes that the Turing Test appears to have played a role in the historical development of AI. Results from the quantitative search show that there is an exponential growth, followed by a short stabilisation, before it begins to decay towards the last decade. Both case studies failed when subjected to a strict Turing Test. Though when subjected to the Total Turing Test, Google Duplex seems to surpass it. Finally, this report also concludes that the Turing Test may no longer be relevant, as mediums for AI have evolved beyond text-based and most developments are no longer concerned with tricking humans.