617 research outputs found
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Ditransitives in germanic languages. Synchronic and diachronic aspects
This volume brings together twelve empirical studies on ditransitive constructions in Germanic languages and their varieties, past and present. Specifically, the volume includes contributions on a wide variety of Germanic languages, including English, Dutch, and German, but also Danish, Swedish, and Norwegian, as well as lesser-studied ones such as Faroese. While the first part of the volume focuses on diachronic aspects, the second part showcases a variety of synchronic aspects relating to ditransitive patterns. Methodologically, the volume covers both experimental and corpus-based studies. Questions addressed by the papers in the volume are, among others, issues like the cross-linguistic pervasiveness and cognitive reality of factors involved in the choice between different ditransitive constructions, or differences and similarities in the diachronic development of ditransitives. The volume’s broad scope and comparative perspective offers comprehensive insights into well-known phenomena and furthers our understanding of variation across languages of the same family
Digital agriculture: research, development and innovation in production chains.
Digital transformation in the field towards sustainable and smart agriculture. Digital agriculture: definitions and technologies. Agroenvironmental modeling and the digital transformation of agriculture. Geotechnologies in digital agriculture. Scientific computing in agriculture. Computer vision applied to agriculture. Technologies developed in precision agriculture. Information engineering: contributions to digital agriculture. DIPN: a dictionary of the internal proteins nanoenvironments and their potential for transformation into agricultural assets. Applications of bioinformatics in agriculture. Genomics applied to climate change: biotechnology for digital agriculture. Innovation ecosystem in agriculture: Embrapa?s evolution and contributions. The law related to the digitization of agriculture. Innovating communication in the age of digital agriculture. Driving forces for Brazilian agriculture in the next decade: implications for digital agriculture. Challenges, trends and opportunities in digital agriculture in Brazil
Behavior quantification as the missing link between fields: Tools for digital psychiatry and their role in the future of neurobiology
The great behavioral heterogeneity observed between individuals with the same
psychiatric disorder and even within one individual over time complicates both
clinical practice and biomedical research. However, modern technologies are an
exciting opportunity to improve behavioral characterization. Existing
psychiatry methods that are qualitative or unscalable, such as patient surveys
or clinical interviews, can now be collected at a greater capacity and analyzed
to produce new quantitative measures. Furthermore, recent capabilities for
continuous collection of passive sensor streams, such as phone GPS or
smartwatch accelerometer, open avenues of novel questioning that were
previously entirely unrealistic. Their temporally dense nature enables a
cohesive study of real-time neural and behavioral signals.
To develop comprehensive neurobiological models of psychiatric disease, it
will be critical to first develop strong methods for behavioral quantification.
There is huge potential in what can theoretically be captured by current
technologies, but this in itself presents a large computational challenge --
one that will necessitate new data processing tools, new machine learning
techniques, and ultimately a shift in how interdisciplinary work is conducted.
In my thesis, I detail research projects that take different perspectives on
digital psychiatry, subsequently tying ideas together with a concluding
discussion on the future of the field. I also provide software infrastructure
where relevant, with extensive documentation.
Major contributions include scientific arguments and proof of concept results
for daily free-form audio journals as an underappreciated psychiatry research
datatype, as well as novel stability theorems and pilot empirical success for a
proposed multi-area recurrent neural network architecture.Comment: PhD thesis cop
Knowledge and pre-trained language models inside and out: a deep-dive into datasets and external knowledge
Pre-trained Language Models (PLMs) have greatly advanced the performance of various NLP tasks and have undoubtedly been serving as foundation models for this field. These pre-trained models are able to capture rich semantic patterns from large-scale text corpora and learn high-quality representations of texts. However, such models still have shortcomings - they underperform when faced with tasks that requires implicit external knowledge to be understood, which is difficult to learn with commonly employed pre-training objectives. Moreover, there lacks a comprehensive understanding of PLMs’ behaviour in learning knowledge during the fine-tuning phase. Therefore, in order to address the aforementioned challenges, we propose a set of approaches to inject external knowledge into PLMs and demonstrate experiments investigating their behaviour in learning knowledge during the fine-tuning phase, primarily focusing on Sentiment Analysis, Question Answering and Video Question Answering.
Specifically, we introduce novel approaches explicitly using textual historical reviews of users and products for improving sentiment analysis. To overcome the problem of context-question lexical overlap and data scarcity for question generation, we propose a novel method making use of linguistic and semantic knowledge with heuristics. Additionally, we explore how to utilise multimodal (visual and acoustic) information/knowledge to improve Video Question Answering.
Experiments conducted on benchmark datasets show that our proposed approaches achieve superior performance compared to state-of-the-art models, demonstrating the effectiveness of our methods for injecting external knowledge. Furthermore, we conduct a set of experiments investigating the learning of knowledge for PLMs for question answering under various scenarios. Results reveal that the internal characteristics of QA datasets can pose strong bias for PLMs when learning from downstream tasks datasets. Finally, we present an in-depth discussion of future directions for improving PLMs with external knowledge
Apport de l’IRM structurelle multimodale dans la chirurgie d’épilepsie : le cas de l’épilepsie insulaire
L’épilepsie insulaire (ÉI) est une forme rare d’épilepsie focale qui, en raison des défis liés à son diagnostic, est difficilement cernable. De plus, la prise en charge des patients avec ÉI s’avère complexifiée par le fait que cette pathologie est fréquemment résistante aux médicaments anti-crises. Pour ces cas médico-réfractaires, la chirurgie insulaire est une option viable. Cela dit, les patients subissant une telle intervention développent fréquemment des déficits neurologiques postopératoires; heureusement, la grande majorité de ceux-ci récupèrent complètement et rapidement. Or, le mécanisme sous-tendant ce singulier rétablissement fonctionnel demeure à ce jour mal compris.
Deux modalités modernes d’IRM structurelle, soit l’analyse d’épaisseur corticale et la tractographie, ont permis, dans les dernières années, de décrire les altérations architecturales caractéristiques et potentiellement diagnostiques de divers types d’épilepsie ainsi que de caractériser les remodelages plastiques qui suivent la chirurgie de l’épilepsie extra-insulaire. Cependant, à ce jour, aucune étude ne s’est encore penchée sur le cas de l’ÉI. De ce fait, les études qui constituent cette thèse exploitent l’IRM structurelle afin, d’une part, de dépeindre les altérations d’épaisseur du cortex et de connectivité de matière blanche associées à l’ÉI et, d’autre part, de définir les réarrangements de connectivité subséquents à la chirurgie insulaire pour contrôle épileptique.
Les deux premières études de cette thèse ont révélé que l’ÉI était associée à un pattern majoritairement ipsilatéral d’atrophie corticale et d’hyperconnectivité impliquant principalement des sous-régions insulaires et des régions connectées à l’insula. De manière intéressante, la topologie de ces changements correspondait, au moins en partie, à celle du réseau épileptique de l’ÉI. Ensuite, la troisième étude visait à décrire, par le biais d’une méta-analyse, l’histoire naturelle postopératoire des patients subissant une chirurgie pour ÉI. Cette analyse a, entre autres, confirmé que cette chirurgie était efficace (66.7% de disparition des crises) et qu’elle était fréquemment accompagnée de complications neurologiques (42.5%) qui, dans la plupart des cas, étaient transitoires (78.7% des complications) et récupéraient entièrement dans les trois mois postopératoires (91.6% des complications transitoires). Finalement, la quatrième étude a révélé que la chirurgie pour ÉI était suivie d’altérations de connectivité diffuses et bilatérales. Notamment, les connexions présentant une augmentation de connectivité concernaient particulièrement des régions localisées soit près de la cavité chirurgicale ou dans l’hémisphère controlatéral à l’intervention. De plus, la majorité de ces renforcements structurels se sont produits dans les six premiers mois suivant la chirurgie, un délai comparable à celui durant lequel la majeure partie de la récupération fonctionnelle postopératoire a été observée dans notre méta-analyse.
En somme, nos résultats suggèrent que les altérations morphologiques en lien avec l’ÉI peuvent correspondre à son réseau épileptique sous-jacent. La topologie de ces changements pourrait constituer un biomarqueur structurel diagnostique qui aiderait à la reconnaissance de l’ÉI et, concomitamment, favoriserait possiblement un traitement chirurgical plus adapté et plus efficace. De plus, les augmentations de connectivité postopératoires pourraient correspondre à des réponses neuroplastiques permettant de prendre en charge les fonctions altérées par la chirurgie. Nos constats ont ainsi contribué à la caractérisation des mécanismes étayant la singulière récupération fonctionnelle accompagnant la chirurgie pour ÉI. À plus grande échelle, nos travaux offrent un aperçu du potentiel de l’IRM structurelle à assister au diagnostic de l’épilepsie focale ainsi qu’à participer à la description des changements plastiques subséquents à une résection neurochirurgicale.Insular epilepsy (IE) is a rare type of focal epilepsy that is difficult to diagnose. In addition to the challenging nature of IE detection, management of patients with this condition is complicated by the tendency of insular seizures to be resistant to anti-seizure medications. For such medically refractory cases, insular surgery constitutes a viable and long-lasting therapeutic option. That said, patients who undergo an insular resection for seizure control frequently develop postoperative neurological deficits; fortunately, most of these impairments recover fully and rapidly. While this favorable postoperative course contributes to improving the outcome of IE surgery, the mechanism underlying the functional recovery remains unknown.
Two contemporary structural MRI modalities, namely cortical thickness analysis and tractography, have recently been used to describe characteristic structural alterations of focal epilepsies and to elucidate the postoperative plastic remodeling associated with surgery for extra-insular epilepsy. While these analyses added to our understanding of several localization-related epilepsies, none specifically studied IE. In this thesis, we exploit structural MRI techniques to, first, depict the alterations of cortical thickness and white matter connectivity in IE and, second, define the progressive rearrangements that follow insular surgery for epilepsy.
The first two studies of the current thesis showed that IE is associated with a primarily ipsilateral pattern of cortical thinning and hyperconnectivity that mainly involves insular subregions and insula-connected regions. Interestingly, the topology of these changes corresponded, at least in part, to the epileptic network of IE. Furthermore, the third study aimed to describe, via a meta-analysis, the postoperative outcome of patients undergoing surgery for IE. Among other findings, the analysis revealed that insular surgery was effective (66.7% seizure freedom rate) but was associated with a significant risk of neurological complications (42.5%) which, in most cases, were transient (78.7% of all complications) and recovered fully within three months (91.6% of transient complications). Finally, the fourth study showed that surgery for IE was followed by a diffuse pattern of bilateral structural connectivity changes. Notably, connections exhibiting an increase in connectivity were specifically located near the surgical cavity and in the contralateral healthy hemisphere. In addition, the majority of the structural strengthening occurred in the first six months following surgery, a time course that is consistent with the short delay during which most of the postoperative functional recovery was observed in our meta-analysis.
Our results suggest that the morphological alterations in IE may reflect its underlying epileptic network. The topology of these changes may constitute a structural biomarker that could help diagnose IE more readily and, concomitantly, potentially enable a more targeted and more effective surgical treatment. Moreover, the postoperative increases in connectivity may be compatible with compensatory neuroplastic responses, a process that arose to recoup the functions of the injured insular cortex. Our findings have therefore contributed to the characterization of the driving process that supports the striking functional recovery seen following surgery for IE. On a larger scale, our work provides insights into the potential of structural MRI to assist in the diagnosis of focal epilepsy and to describe plastic changes following neurosurgical resections
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Methods for non-proportional hazards in clinical trials: A systematic review
For the analysis of time-to-event data, frequently used methods such as the
log-rank test or the Cox proportional hazards model are based on the
proportional hazards assumption, which is often debatable. Although a wide
range of parametric and non-parametric methods for non-proportional hazards
(NPH) has been proposed, there is no consensus on the best approaches. To close
this gap, we conducted a systematic literature search to identify statistical
methods and software appropriate under NPH. Our literature search identified
907 abstracts, out of which we included 211 articles, mostly methodological
ones. Review articles and applications were less frequently identified. The
articles discuss effect measures, effect estimation and regression approaches,
hypothesis tests, and sample size calculation approaches, which are often
tailored to specific NPH situations. Using a unified notation, we provide an
overview of methods available. Furthermore, we derive some guidance from the
identified articles. We summarized the contents from the literature review in a
concise way in the main text and provide more detailed explanations in the
supplement (page 29)
Specificity of the innate immune responses to different classes of non-tuberculous mycobacteria
Mycobacterium avium is the most common nontuberculous mycobacterium (NTM) species causing infectious disease. Here, we characterized a M. avium infection model in zebrafish larvae, and compared it to M. marinum infection, a model of tuberculosis. M. avium bacteria are efficiently phagocytosed and frequently induce granuloma-like structures in zebrafish larvae. Although macrophages can respond to both mycobacterial infections, their migration speed is faster in infections caused by M. marinum. Tlr2 is conservatively involved in most aspects of the defense against both mycobacterial infections. However, Tlr2 has a function in the migration speed of macrophages and neutrophils to infection sites with M. marinum that is not observed with M. avium. Using RNAseq analysis, we found a distinct transcriptome response in cytokine-cytokine receptor interaction for M. avium and M. marinum infection. In addition, we found differences in gene expression in metabolic pathways, phagosome formation, matrix remodeling, and apoptosis in response to these mycobacterial infections. In conclusion, we characterized a new M. avium infection model in zebrafish that can be further used in studying pathological mechanisms for NTM-caused diseases
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