10,228 research outputs found

    Assessing the species boundary and ecological niche in freshwater gastropods of the family Physidae (Gastropoda, Hygrophila)

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    The present thesis contributed to increasing the knowledge about the diversity of the neotropical freshwater mollusks. Through the use of different methodologies for analyzing molecular and geographical occurrence data, we address important taxonomic issues and show new paths for future taxonomic research on the Physidae family. This family for a long time had classification proposals based only on morphological characters of the shell and, later, on the anatomy of the soft parts. The application of molecular delimitation methods based on coalescence showed the inadequacy of morphological criteria in discriminating intraspecific variability (overestimating family diversity) and in detecting the existence of cryptic species complexes (underestimating family diversity). The data on the occurrence along with the use of georeferencing tools, modeling, and ecological niche analyses applied to South American physid species, indicated the possibility of errors in species identification and the need to reassess the distribution of these physids using other operational criteria such as molecular approaches to access the actual family diversity and distribution for the continent.A presente tese contribuiu para ampliar o conhecimento sobre a diversidade da malacofauna dulcĂ­cola neotropical. AtravĂ©s do emprego de diferentes metodologias de anĂĄlise de dados moleculares e de ocorrĂȘncia geogrĂĄfica abordamos importantes questĂ”es taxonĂŽmicas e mostramos novos caminhos para futuras pesquisas taxonĂŽmicas da famĂ­lia Physidae. FamĂ­lia essa que por muito tempo teve propostas de classificação embasadas apenas em caracteres morfolĂłgicos da concha e, posteriormente, na anatomia das partes moles. A aplicação de mĂ©todos de delimitação molecular baseados em coalescĂȘncia, evidenciou a insuficiĂȘncia dos critĂ©rios morfolĂłgicos em discriminar a variabilidade intraespecĂ­fica (superestimando a diversidade da famĂ­lia) e, em detectar a existĂȘncia de complexos de espĂ©cies crĂ­pticas (subestimando a diversidade da famĂ­lia). A abordagem de busca intensiva por dados de ocorrĂȘncia junto a utilização de ferramentas de georreferenciamento, modelagem e anĂĄlises de nicho ecolĂłgico aplicadas Ă s espĂ©cies de fisĂ­deos sul-americanos, indicaram a possibilidade de erros de identificação de espĂ©cies e a necessidade de reavaliar a distribuição desses fisĂ­deos usando outros critĂ©rios operacionais, incluindo abordagens moleculares, para acessar a diversidade e distribuição reais da famĂ­lia para o continente

    Neural morphological generators for Hungarian

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    Here we present a set of morphological generators for Hungarian that generate surface forms from emMorph and Universal Dependencies (UD) morphological tags with high accuracy. We experimented with two approaches: first, neural machine translation models were trained based on the morphological analysis as the source format and the corresponding surface form as the target format. Second, we tackled the problem as a text generation task, where the morphological analysis is followed by the correct word form. The corpus we used is a normalised version of Webcorpus 2.0 (Nemeskey, 2020). Marian MT proved to produce the best results, thus we evaluated its output manually on NerKor (Simon and VadĂĄsz, 2021). Our analysis shows that the generator achieves a high accuracy of 96.27% in the case of emMorph and 94.94% in the case of UD. After manual evaluation, we counted a more concise accuracy, which is 99.43% (emMorph) and 98.69% (UD). This model may be used for several NLP tasks, such as anonymisation and terminology translation

    Evaluation of image quality and reconstruction parameters in recent PET-CT and PET-MR systems

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    In this PhD dissertation, we propose to evaluate the impact of using different PET isotopes for the National Electrical Manufacturers Association (NEMA) tests performance evaluation of the GE Signa integrated PET/MR. The methods were divided into three closely related categories: NEMA performance measurements, system modelling and evaluation of the image quality of the state-of-the-art of clinical PET scanners. NEMA performance measurements for characterizing spatial resolution, sensitivity, image quality, the accuracy of attenuation and scatter corrections, and noise equivalent count rate (NECR) were performed using clinically relevant and commercially available radioisotopes. Then we modelled the GE Signa integrated PET/MR system using a realistic GATE Monte Carlo simulation and validated it with the result of the NEMA measurements (sensitivity and NECR). Next, the effect of the 3T MR field on the positron range was evaluated for F-18, C-11, O-15, N-13, Ga-68 and Rb-82. Finally, to evaluate the image quality of the state-of-the-art clinical PET scanners, a noise reduction study was performed using a Bayesian Penalized-Likelihood reconstruction algorithm on a time-of-flight PET/CT scanner to investigate whether and to what extent noise can be reduced. The outcome of this thesis will allow clinicians to reduce the PET dose which is especially relevant for young patients. Besides, the Monte Carlo simulation platform for PET/MR developed for this thesis will allow physicists and engineers to better understand and design integrated PET/MR systems

    Improving the estimation of Cost-of-Illness in rheumatoid arthritis

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    Cost-of-illness (COI) studies measure the economic burden of a disease and estimate the maximum amount that could potentially be saved or gained if a disease were to be eradicated. Estimates of the COI can help appropriately target specific problems and policies on a disease in policy agenda setting. COI studies are particularly useful for chronic diseases that impact heavily on health expenditures and productivity loss for the whole society. It is essential for policymakers to know where costs are incurred. Consequently, appropriate interventions can be implemented and prioritised. Over the past two decades, the accumulation of coexisting long-term conditions within an individual has been confirmed as the best predictor of sustained high costs. It is now an established priority for both research and clinical practice owing to the high prevalence of coexisting diseases among patients, particularly with ageing populations. Because of this shift in how we approach chronic diseases in medical research, it is pertinent that we also think about how this impacts the way we look at COI. On the other hand, inconsistencies in the designs and methodologies that COI studies are conducted and a lack of transparency in reporting have made interpretation and comparison difficult and have limited the usefulness of results in health decision making. Variations include data sources, perspectives, cost components, and costing approaches. On the other hand, while standardisation of methodology through the implementation of guidelines is becoming increasingly important, some flexibility may be required for diseases or different contexts with unique characteristics to be adequately described. Rheumatoid arthritis (RA), as one of the most common chronic diseases, is a leading cause of work disability worldwide. Although numerous COI studies have attempted to quantify the economic burden of RA, the cost estimates vary substantially due to different methodological approaches, perspectives and settings. This thesis aims to improve the estimation of COI. To explore the differences in estimating COI, two case studies were developed in diverse contexts: Scotland and Tanzania. Both studies were complementary to each other in terms of different approaches and contexts to estimating COI. The former was in a high-income country, using secondary data analysis from a RA inception cohort linked to routinely collected health records to estimate the COI. In contrast, the latter was in a low- and middle-income country with limited treatment options. Due to the absence of routinely collected health data and the availability of screening tools for RA, a widening criterion of musculoskeletal (MSK) disorders was adopted. A context-specific questionnaire was developed to collect primary data to estimate the COI of MSK in Tanzania. This thesis confirms the need for improved estimation of COI studies. Good quality COI studies are not easy to do. Current evidence shows a lack of consistency in taking into account indirect costs, resulting in underestimating COI in RA. Moreover, indirect costs need more attention, with improvements in terms of data collection and costing approaches. Health conditions are complex and multi-dimensional, especially when the way we look at them have evolved over time. It is becoming clear that context is also an influencing factor in estimating COI. These complexities need to be considered in COI. While many systematic reviews for COI studies have urged the need to increase comparability, it is more crucial to be transparent in reporting contexts and methodological clarity, including identifying, measuring, and valuing COI

    Palaeoecological data indicates land-use changes across Europe linked to spatial heterogeneity in mortality during the Black Death pandemic

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    Historical accounts of the mortality outcomes of the Black Death plague pandemic are variable across Europe, with much higher death tolls suggested in some areas than others. Here the authors use a 'big data palaeoecology' approach to show that land use change following the pandemic was spatially variable across Europe, confirming heterogeneous responses with empirical data.The Black Death (1347-1352 ce) is the most renowned pandemic in human history, believed by many to have killed half of Europe's population. However, despite advances in ancient DNA research that conclusively identified the pandemic's causative agent (bacterium Yersinia pestis), our knowledge of the Black Death remains limited, based primarily on qualitative remarks in medieval written sources available for some areas of Western Europe. Here, we remedy this situation by applying a pioneering new approach, 'big data palaeoecology', which, starting from palynological data, evaluates the scale of the Black Death's mortality on a regional scale across Europe. We collected pollen data on landscape change from 261 radiocarbon-dated coring sites (lakes and wetlands) located across 19 modern-day European countries. We used two independent methods of analysis to evaluate whether the changes we see in the landscape at the time of the Black Death agree with the hypothesis that a large portion of the population, upwards of half, died within a few years in the 21 historical regions we studied. While we can confirm that the Black Death had a devastating impact in some regions, we found that it had negligible or no impact in others. These inter-regional differences in the Black Death's mortality across Europe demonstrate the significance of cultural, ecological, economic, societal and climatic factors that mediated the dissemination and impact of the disease. The complex interplay of these factors, along with the historical ecology of plague, should be a focus of future research on historical pandemics

    The Adirondack Chronology

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    The Adirondack Chronology is intended to be a useful resource for researchers and others interested in the Adirondacks and Adirondack history.https://digitalworks.union.edu/arlpublications/1000/thumbnail.jp

    Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning

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    Developing artificial learning systems that can understand and generate natural language has been one of the long-standing goals of artificial intelligence. Recent decades have witnessed an impressive progress on both of these problems, giving rise to a new family of approaches. Especially, the advances in deep learning over the past couple of years have led to neural approaches to natural language generation (NLG). These methods combine generative language learning techniques with neural-networks based frameworks. With a wide range of applications in natural language processing, neural NLG (NNLG) is a new and fast growing field of research. In this state-of-the-art report, we investigate the recent developments and applications of NNLG in its full extent from a multidimensional view, covering critical perspectives such as multimodality, multilinguality, controllability and learning strategies. We summarize the fundamental building blocks of NNLG approaches from these aspects and provide detailed reviews of commonly used preprocessing steps and basic neural architectures. This report also focuses on the seminal applications of these NNLG models such as machine translation, description generation, automatic speech recognition, abstractive summarization, text simplification, question answering and generation, and dialogue generation. Finally, we conclude with a thorough discussion of the described frameworks by pointing out some open research directions.This work has been partially supported by the European Commission ICT COST Action “Multi-task, Multilingual, Multi-modal Language Generation” (CA18231). AE was supported by BAGEP 2021 Award of the Science Academy. EE was supported in part by TUBA GEBIP 2018 Award. BP is in in part funded by Independent Research Fund Denmark (DFF) grant 9063-00077B. IC has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 838188. EL is partly funded by Generalitat Valenciana and the Spanish Government throught projects PROMETEU/2018/089 and RTI2018-094649-B-I00, respectively. SMI is partly funded by UNIRI project uniri-drustv-18-20. GB is partly supported by the Ministry of Innovation and the National Research, Development and Innovation Office within the framework of the Hungarian Artificial Intelligence National Laboratory Programme. COT is partially funded by the Romanian Ministry of European Investments and Projects through the Competitiveness Operational Program (POC) project “HOLOTRAIN” (grant no. 29/221 ap2/07.04.2020, SMIS code: 129077) and by the German Academic Exchange Service (DAAD) through the project “AWAKEN: content-Aware and netWork-Aware faKE News mitigation” (grant no. 91809005). ESA is partially funded by the German Academic Exchange Service (DAAD) through the project “Deep-Learning Anomaly Detection for Human and Automated Users Behavior” (grant no. 91809358)
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