10,228 research outputs found
Assessing the species boundary and ecological niche in freshwater gastropods of the family Physidae (Gastropoda, Hygrophila)
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
morfológicos 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 critérios operacionais, incluindo abordagens moleculares, para acessar a
diversidade e distribuição reais da famĂlia para o continente
Neural morphological generators for Hungarian
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
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Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
Evaluation of image quality and reconstruction parameters in recent PET-CT and PET-MR systems
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
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
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
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
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After Creation: Intergovernmental Organizations and Member State Governments as Co-Participants in an Authority Relationship
This is a re-amalgamation of what started as one manuscript and became two when the length proved to be more than any publisher wanted to consider. The splitting consisted of removing what are now Parts 3, 4, and 5 so that the manuscript focused on the outcome-related shared beliefs holding an authority relationship together. Those parts were last worked on in 2018. The rest were last worked on in late 2021 but also remain incomplete.
The relational approach adopted in this study treats intergovernmental organizations and the governments of member states as co-participants in an authority relationship with the governments of their member states. Authority relationships link two types of actor, defined by their authority-holder or addressee role in the relationship, through a set of shared beliefs about why the relationship exists and how the participants should fulfill their respective roles. The IGO as authority holder has a role that includes a right to instruct other actors about what they should or should not do; the governments of member states as addressees are expected to comply with the instructions. Three sets of shared beliefs provide the conceptual âglueâ holding the relationship together. The first defines the goal of the collective effort, providing both the rationale for having the authority relationship and providing a lode star for assessments of the collective effortâs success or lack of success. The second set defines the shared understanding about allocation of roles and the process of interaction by establishing shared expectations about a) the selection process by which particular actors acquire authority holder roles, b) the definitions identifying one or more categories of addressees expected to follow instructions, and c) the procedures through which the authority holder issues instructions. The third set focus on the outcomes of cooperation through the relationship by defining a) the substantive areas in which the authority holder may issue instructions, b) the bases for assessing the relevance actions mandated in instructions for reaching the goal, and c) the relative efficacy of action paths chosen for reaching the goal as compared to other possible action paths.
Using an authority relationship framework for analyzing cooperation through IGOs highlights the inherently bi-directional nature of IGO-member government activity by viewing their interaction as involving a three-step process in which the IGO as authority holder decides when to issue what instruction, the member state governments as followers react to the instruction with anything from prompt and full compliance through various forms of pushback to outright rejection, and the IGO as authority holder responds to how the followers react with efforts to increase individual compliance with instructions and reinforce continuing acceptance of the authority relationship. Foregrounding the dynamics produced by the interaction of these two streams of perception and action reveals more clearly how far intergovernmental organizations acquire capacity to operate as independent actors, the dynamic ways they maintain that capacity, and how much they influence member governmentsâ beliefs and actions at different times. The approach fosters better understanding of why, when, and for how long governments choose cooperation through an IGO even in periods of rising unilateralism
Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning
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 âMulti-task, Multilingual, Multi-modal Language Generationâ (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 Unionâs 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 âHOLOTRAINâ (grant no. 29/221 ap2/07.04.2020, SMIS code: 129077) and by the German Academic Exchange Service (DAAD) through the project âAWAKEN: content-Aware and netWork-Aware faKE News mitigationâ (grant no. 91809005). ESA is partially funded by the German Academic Exchange Service (DAAD) through the project âDeep-Learning Anomaly Detection for Human and Automated Users Behaviorâ (grant no. 91809358)
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