Cellular Imaging in Regenerative Medicine, Cancer and Osteoarthritis

In this thesis we showed different methods to label cells for cellular imaging to determine their role in diagnosis and therapy of various diseases

Every ambiguity isn’t syntactic in nature: Testing the Rational Speech Act model of scope ambiguity

Utterances like ‘Every guest didn’t leave’ are ambiguous between a reading according to which no guest left and a reading according to which not all of the guests left. This ambiguity is often explained by assuming that ‘every-not’ utterances have two different syntactic parses. However, experimental studies have shown that pragmatic factors, such as prior probabilities and the question under discussion, also play an important role in the interpretation of ambiguous ‘every-not’ utterances. Recently, Scontras and Pearl (2020) put forward a probabilistic model of ambiguity resolution that makes it possible to quantify the relative contribution of syntactic and pragmatic factors. Here, we present three experiments aimed at testing this model and measuring the division of labor between syntax and pragmatics. Our results suggest that variability in the interpretation of ‘every-not’ utterances can be explained almost entirely in terms of pragmatics, suggesting only a marginal role for syntax

The role of relevance, competence, and priors for scalar inferences

Although it is often assumed that the natural language expressions 'some' and 'or' are interpreted according to their first-order logic counterparts, in certain contexts, they receive a narrower interpretation: 'some' is strengthened to 'some, but not all', and 'or' to 'A or B, but not both'. This process is typically explained as an instance of scalar inference. To test this scalar implicature hypothesis, we collect experimental evidence for the effects and interactions of three factors that should affect the robustness of the scalar inferences of 'some' and 'or': the relevance of the stronger alternative, the speaker's competence about the alternative, and the prior probability that the alternative is true. We find that the interpretation of both triggers was affected by speaker competence, but only 'some' was also affected by prior probability, while relevance did not affect either trigger. Ultimately, our results suggest that the interdependence of the three factors is more complex than just the sum of their effects

Commitments de lingua and assertoric commitments: the case of expressives

This paper presents the results of two series of experimental studies concerning the interpretation of expressives (e.g., ‘the jerk’) and the sentences they occur in. While expressives are known for their strong speaker-orientation, Harris & Potts (2009) found that in the right context, i.e. when a different subject is introduced into the discourse as a reported speaker, it is possible to interpret the expressive from this subject’s perspective. In our first series of experiments we corroborated the systematic availability of non-speaker oriented readings of expressives, but we also found a strong correlation between the attribution of the expressive and that of the sentence content: participants who attribute the expressive to the subject rather than the speaker, also tend to attribute the sentence as a whole to the subject. In other words, shifted interpretations of expressives do occur, but tend to go hand-in-hand with a reportative reading of the sentence in which the expressive occurs. In our second series of experiments, we identified factors that influence such a reportative reading. Following Kaiser (2015), we found that when we made the subject more prominent as an anchor—by removing the reference to the actual speaker and by adjusting the tense to facilitate a free indirect discourse reading—the number of subject-oriented readings grew significantly. On the basis of these findings we argue for a pragmatic account in terms of commitment attribution with three constraints at work: (i) commitments de lingua for expressives need a salient anchor, (ii) commitments de lingua tend to be attributed in concert with assertoric commitments, and (iii) the main speaker is the most salient anchor by default. These three constraints jointly explain the observations in the experiments

Representing Polar Questions

Although the linguistic properties of polar questions have been extensively studied, comparatively little is known about how polar questions are processed in real time. In this paper, we report on three eye-tracking experiments on the processing of positive and negative polar questions in English and French. Our results show that in the early stages, participants pay attention to both positive and negative states of affairs for both positive and negative questions. In the late stages, positive and certain negative polar questions were associated with a bias for the positive state, and this bias appears to be pragmatic in nature. We suggest that different biases in mental representations reflect the hearer’s reasoning about the speaker’s purposes of enquiry

Imbalance-aware Presence-only Loss Function for Species Distribution Modeling

In the face of significant biodiversity decline, species distribution models (SDMs) are essential for understanding the impact of climate change on species habitats by connecting environmental conditions to species occurrences. Traditionally limited by a scarcity of species observations, these models have significantly improved in performance through the integration of larger datasets provided by citizen science initiatives. However, they still suffer from the strong class imbalance between species within these datasets, often resulting in the penalization of rare species--those most critical for conservation efforts. To tackle this issue, this study assesses the effectiveness of training deep learning models using a balanced presence-only loss function on large citizen science-based datasets. We demonstrate that this imbalance-aware loss function outperforms traditional loss functions across various datasets and tasks, particularly in accurately modeling rare species with limited observations.Comment: Tackling Climate Change with Machine Learning at ICLR 202

A comparative study of Norse palaeodemography in the North Atlantic

Acknowledgements British Academy Global Professorship GP2\190224. The authors would like to thank Ricky Craig, Independent GIS Specialist and Cartographer, Scotland, for preparing Figure 1, the map.Peer reviewe

Quantitative Imaging Biomarkers of Knee Cartilage Composition

For a long time, radiography and subsequently conventional magnetic resonance imaging (MRI) were used as imaging biomarkers for evaluating cartilage morphological disease state in osteoarthritis (OA). Because research is switching its focus towards disease modification or even prevention to target OA at an early stage, imaging techniques that measure cartilage composition rather than its morphology became of interest. Several MRI and computed tomography (CT) based quantitative imaging biomarkers for cartilage composition were developed. These techniques were advocated to allow a quantitative measure of the sulphated glycosaminoglycan (sGAG) content, an important composite of the cartilage extracellular matrix. The main aims of this thesis is based have been divided between MRI and CT based quantitative imaging biomarkers since their different stage of application in research. MRI has already been applied in human OA research, whereas CT was still to be translated and implemented in clinical research. The first part of this thesis focused on MRI based techniques and aimed at optimization of image post processing, assessing reproducibility, comparison of different MRI sequences and application in clinical OA research. Since accurate image post processing is of utmost importance to generate reliable and robust quantitative MRI outcomes, an imaging post processing tool was developed and described in chapter 2. This tool corrects for intra-sequence patient motion during acquisition of quantitative MR images, by applying image registration reducing errors and incorrect outcomes. This resulted in 6-14% improvement in accuracy of delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) T1 relaxation time. Using image registration, the tool also allows assessment of the same cartilage region throughout multiple MRI acquisitions, which makes analyses less time consuming. Finally, the algorithm also involves a fitting technique which corrects for unreliable quantitative MRI biomarker data by calculating a weighted mean outcome for all voxels in a specific cartilage region based on the inaccuracy of each voxel. Because of these abilities and the fact that this tool could be used in any quantitative MRI biomarker, e.g. T1rho-mapping or T2-mapping, the image post processing tool was used in all chapters in this thesis where MRI based measures were used for cartilage sGAG content. Along with robust image processing tools, the outcomes of the MRI exam itself should also be reproducible in order to be able to apply the particular technique in cross-sectional or longitudinal study designs. Therefore, chapter 3 described a reproducibility study of dGEMRIC acquired at 3 Tesla in early stage knee OA patient. It was shown that dGEMRIC is highly reproducible in terms of results in large cartilage regions, as well as for differentiating between spatial distributions of diverse cartilage quality within a single slice. dGEMRIC can therefore be used as an imaging biomarker in cross-sectional and longitudinal study designs. In addition, a threshold for defining significant changes in dGEMRIC results for longitudinal follow-up was determined. T1rho-mapping has been proposed as a non-contrast-enhanced alternative to dGEMRIC for sGAG quantification in clinical studies. However, no thorough validation has been performed comparing both techniques within the same OA patients using a reference standard for cartilage sGAG. Therefore, in chapter 4 an in vivo comparison and validation study assessing the capability of dGEMRIC and T1rho-mapping was performed. In knee OA patients, dGEMRIC results strongly correlate with cartilage sGAG content, whereas T1rho-mapping did not. Therefore, it appears that T1rho-mapping cannot be regarded as an alternative for dGEMRIC to measure cartilage sGAG content in clinical OA research. It was also shown that resu