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  • Digital Humanities and Cultural Heritage

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  • Open Access English
    Authors: 
    Andrej Kotljarchuk;
    Publisher: Södertörns högskola, Samtidshistoriska institutet
    Country: Sweden

    AbstractThousands of Roma were killed in Ukraine by the Nazis and auxiliary police on the spot. There are more than 50,000 Roma in today’s Ukraine, represented by second and third generation decendants of the genocide survivors. The discussion on Roma identity cannot be isolated from the memory of the genocide, which makes the struggle over the past a reflexive landmark that mobilizes the Roma movement. About twenty Roma genocide memorials have been erected in Ukraine during last decade, and in 2016 the national memorial of the Roma genocide was opened in Babi Yar. However, scholars do not have a clear picture of memory narratives and memory practices of the Roma genocide in Ukraine. A comprehensive analysis of the contemporary situation is not possible without an examination of the history and memory of the Roma genocide before 1991.

  • Open Access English
    Authors: 
    Irena Spasic; Dominik Krzemiński; Padraig Corcoran; Alexander Balinsky;
    Publisher: JMIR Publications

    Background Clinical trials are an important step in introducing new interventions into clinical practice by generating data on their safety and efficacy. Clinical trials need to ensure that participants are similar so that the findings can be attributed to the interventions studied and not to some other factors. Therefore, each clinical trial defines eligibility criteria, which describe characteristics that must be shared by the participants. Unfortunately, the complexities of eligibility criteria may not allow them to be translated directly into readily executable database queries. Instead, they may require careful analysis of the narrative sections of medical records. Manual screening of medical records is time consuming, thus negatively affecting the timeliness of the recruitment process. Objective Track 1 of the 2018 National Natural Language Processing Clinical Challenge focused on the task of cohort selection for clinical trials, aiming to answer the following question: Can natural language processing be applied to narrative medical records to identify patients who meet eligibility criteria for clinical trials? The task required the participating systems to analyze longitudinal patient records to determine if the corresponding patients met the given eligibility criteria. We aimed to describe a system developed to address this task. Methods Our system consisted of 13 classifiers, one for each eligibility criterion. All classifiers used a bag-of-words document representation model. To prevent the loss of relevant contextual information associated with such representation, a pattern-matching approach was used to extract context-sensitive features. They were embedded back into the text as lexically distinguishable tokens, which were consequently featured in the bag-of-words representation. Supervised machine learning was chosen wherever a sufficient number of both positive and negative instances was available to learn from. A rule-based approach focusing on a small set of relevant features was chosen for the remaining criteria. Results The system was evaluated using microaveraged F measure. Overall, 4 machine algorithms, including support vector machine, logistic regression, naïve Bayesian classifier, and gradient tree boosting (GTB), were evaluated on the training data using 10–fold cross-validation. Overall, GTB demonstrated the most consistent performance. Its performance peaked when oversampling was used to balance the training data. The final evaluation was performed on previously unseen test data. On average, the F measure of 89.04% was comparable to 3 of the top ranked performances in the shared task (91.11%, 90.28%, and 90.21%). With an F measure of 88.14%, we significantly outperformed these systems (81.03%, 78.50%, and 70.81%) in identifying patients with advanced coronary artery disease. Conclusions The holdout evaluation provides evidence that our system was able to identify eligible patients for the given clinical trial with high accuracy. Our approach demonstrates how rule-based knowledge infusion can improve the performance of machine learning algorithms even when trained on a relatively small dataset.

  • Open Access English
    Authors: 
    Wallinder-Pierini, Linda;
    Publisher: Zenodo
    Country: Switzerland

    Is it possible to claim ownership of the Buddhist dharma; the teachings of the Buddha? Does a group's relationship to its cultural productions constitute a form of ownership? Can a religious image be copyrighted? This article will focus on the emergence and transformation of the Moji-Mandala or Gohonzon (御本尊), created by the Japanese monk Nichiren (1222-1282). Nichiren's followers were persecuted, and some were executed when the scroll was found in their possession. Nichiren's hanging mandala was previously available only to individuals seriously practicing Nichiren's Buddhism. Currently, Nichiren's mandala is reproduced electronically over the internet by websites claiming to represent various Buddhist lay organizations. The digital revolution has increased the ability of individuals to appropriate and profit from the cultural knowledge of religious groups that are largely unprotected by existing intellectual property law.

  • Open Access English
    Authors: 
    Yinping Wang;
    Publisher: Hindawi

    In this study, multidimensional feature extraction is performed on the U-language recordings of the test takers, and these features are evaluated separately, with five categories of features: pronunciation, fluency, vocabulary, grammar, and semantics. A deep neural network model is constructed to model the feature values to obtain the final score. Based on the previous research, this study uses a deep neural network training model instead of linear regression to improve the correlation between model score and expert score. The method of using word frequency for semantic scoring is replaced by the LDA topic model for semantic analysis, which eliminates the need for experts to manually label keywords before scoring and truly automates the critique. Also, this paper introduces text cleaning after speech recognition and deep learning-based speech noise reduction technology in the scoring model, which improves the accuracy of speech recognition and the overall accuracy of the scoring model. Also, innovative applications and improvements are made to key technologies, and the latest technical solutions are integrated and improved. A new open oral grading model is proposed and implemented, and innovations are made in the method of speech feature extraction to improve the dimensionality of open oral grading.

  • Open Access English
    Authors: 
    Esther Fernández-Molina; Raquel Bartolomé Gutiérrez;
    Publisher: SAGE
    Country: Spain

    One of the most robust findings in criminology is the fall in crime rates throughout the Western world. However, there is still much to be learnt about this and its causes. This case study analyses the Spanish juvenile crime trends and tests the explanatory capacity of the sociodemographic hypotheses. We use aggregate data provided by the police and self-report data. Our analysis could be of interest in a worldwide debate on the crime drop. Demographic changes and the economic situation have little relevance in explaining the changes. However, public policies seem to have had a greater impact on crime trends. Furthermore, gender equality can be considered a possible explanatory factor.

  • Open Access English
    Authors: 
    Youxu Li; Qiang Dai; Rong Hou; Zhihe Zhang; Peng Chen; Rui Xue; Feifei Feng; Chen Chao; Jiabin Liu; Xiaodong Gu; +2 more
    Publisher: Nature Publishing Group UK

    A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

  • Publication . Other literature type . Article . 2020
    Open Access English
    Authors: 
    Hiroyuki Hosokawa; Ellen V. Rothenberg;

    Recent evidence has elucidated how multipotent blood progenitors transform their identities in the thymus and undergo commitment to become T cells. Together with environmental signalling, a core group of transcription factors have essential roles in this process by directly activating and repressing specific genes. Many of these transcription factors also function again, but controlling different genes, in later T cell development. Here, we review how these transcription factors work to change the activities of specific genomic loci during early intrathymic development to establish T lineage identity. We introduce the key regulators and highlight newly emergent insights into the rules that govern their actions. Whole-genome deep sequencing-based analysis has revealed unexpectedly rich relationships between inherited epigenetic states, transcription factor-DNA binding affinity thresholds, and influences of given transcription factors on the activities of other factors in the same cells. Together, these mechanisms determine T cell identity and make the lineage choice irreversible.

  • Open Access English
    Authors: 
    Lauren Dundler;
    Publisher: MDPI AG

    and finally, some dealers utilise a suite of justifications for their behaviours, practices and values (known as neutralisation techniques) to undermine their legal obligations. Such results confirm existing claims of the failure of self-regulation in the internet antiquities market and reveal a demand for educational campaigns targeted at raising consumer awareness by challenging misleading market narratives and highlighting the ethical and legal issues involved with the trade of cultural heritage. The global internet antiquities market exists in a complex cultural heritage framework, comprised of international law and domestic legislation. In this paper, the questions I seek to answer are the following: how do internet antiquities dealers engage with their legal obligations, and how is this engagement translated to the ethics of their businesses? This paper presents a comparative examination of 45 antiquities dealers split across three categories&mdash revealing three key insights about the internet antiquities market: firstly, that the level of legal literacy in the market is depicted as being quite poor secondly, that the performance of legal awareness does not always correspond with ethical dealer practices internet dealers, eBay dealers and social media dealers&mdash

  • Open Access English
    Authors: 
    Bas van Geel; Otto Brinkkemper; Guido van Reenen; Nathalie Van der Putten; Jasmijn E. Sybenga; Carla Soonius; Annemieke Kooijman; Tom Hakbijl; William D. Gosling;
    Publisher: MDPI AG
    Country: Netherlands

    We studied twelve late Holocene organic deposits in West-Frisia, The Netherlands. Pollen, spores, non-pollen palynomorphs, mosses, other botanical macrofossils and insect remains were recorded for reconstructions of changing environmental conditions. Eastern West-Frisia was a cultivated landscape during the Bronze Age, but it became a freshwater wetland in the Late Bronze Age. In most of our sites, radiocarbon dates show that time transgressive inundation of soils preceded the climate shift at 850 cal BC for several centuries. We suggest that solar forcing of climate change may have delivered the final push to the inundation and depopulation of West-Frisia, which had already commenced several centuries before, due to sealevel rise. We did not find evidence for significant Bronze Age tree growth in West-Frisia before the inundations. Vegetation successions in the new wetlands developed from shallow mineral-rich freshwater to rich-fen vegetation. Subsequently poor fen vegetation with birch and pine developed, and the natural succession led to ombrotrophic raised bog vegetation. Complete successions from shallow, mineral-rich lakes to raised bog lasted between 1000 and 1500 calendar years. We hypothesize that medieval drainage and reclamation became possible only when the mires of West-Frisia had reached the raised bog stage. Reclamation of raised bogs by medieval farmers (drainage, eutrophication, peat digging) caused compaction, oxidation and loss of the upper part of the peat deposit. Seeds of salt-tolerant and salt-demanding plant species indicate that the medieval sites were inundated during storm surges with brackish or salt water, which triggered the farmers to build artificial mounds and, later, dikes. Under mounds and dikes, peat deposits remained protected against further decay. With our data we deliver a long-term perspective on contemporary ecosystem dynamics of freshwater wetlands, relevant for nature conservation and future climate change.

  • Open Access English
    Authors: 
    Ishani Chatterjee; Mengchu Zhou; Abdullah Abusorrah; Khaled Sedraoui; Ahmed Alabdulwahab;
    Publisher: MDPI

    People nowadays use the internet to project their assessments, impressions, ideas, and observations about various subjects or products on numerous social networking sites. These sites serve as a great source to gather data for data analytics, sentiment analysis, natural language processing, etc. Conventionally, the true sentiment of a customer review matches its corresponding star rating. There are exceptions when the star rating of a review is opposite to its true nature. These are labeled as the outliers in a dataset in this work. The state-of-the-art methods for anomaly detection involve manual searching, predefined rules, or traditional machine learning techniques to detect such instances. This paper conducts a sentiment analysis and outlier detection case study for Amazon customer reviews, and it proposes a statistics-based outlier detection and correction method (SODCM), which helps identify such reviews and rectify their star ratings to enhance the performance of a sentiment analysis algorithm without any data loss. This paper focuses on performing SODCM in datasets containing customer reviews of various products, which are (a) scraped from Amazon.com and (b) publicly available. The paper also studies the dataset and concludes the effect of SODCM on the performance of a sentiment analysis algorithm. The results exhibit that SODCM achieves higher accuracy and recall percentage than other state-of-the-art anomaly detection algorithms.