Methods and algorithms for unsupervised learning of morphology

This is an accepted manuscript of a chapter published by Springer in Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8403 in 2014 available online: https://doi.org/10.1007/978-3-642-54906-9_15 The accepted version of the publication may differ from the final published version.This paper is a survey of methods and algorithms for unsupervised learning of morphology. We provide a description of the methods and algorithms used for morphological segmentation from a computational linguistics point of view. We survey morphological segmentation methods covering methods based on MDL (minimum description length), MLE (maximum likelihood estimation), MAP (maximum a posteriori), parametric and non-parametric Bayesian approaches. A review of the evaluation schemes for unsupervised morphological segmentation is also provided along with a summary of evaluation results on the Morpho Challenge evaluations.Published versio

Association of baseline inflammatory markers and the development of negative symptoms in individuals at clinical high risk for psychosis

Negative symptoms are common in individuals at clinical high-risk (CHR) for psychosis and are associated with worse functional outcomes. Inflammation may be one mechanism underlying negative symptoms. Inflammatory markers are altered in individuals at CHR and are associated with negative symptoms in patients with schizophrenia. We thus hypothesized that baseline inflammatory markers would predict the development of negative symptoms in individuals at CHR for psychosis. Thirty seven individuals from the North American Prodromal Longitudinal Study who met CHR criteria were included in the study. Inflammatory cytokines, including interferon (IFN)-λ, Interleukin (IL)-1β, IL-1 receptor antagonist (IL-1RA), IL-4, IL-6, IL-8, IL-10, and tumor necrosis factor (TNF) were measured at baseline. Negative symptoms as measured by the Scale of Prodromal Symptoms, were measured at baseline and six and twelve months. Associations between inflammatory markers and the trajectory of negative symptoms (slope) over the first year of follow-up, were assessed using linear regression models controlling for age, sex, race and depressive symptom severity (as assessed by the Calgary Depression Scale for Schizophrenia). Baseline TNF (beta = 0.361, p = 0.007) and IL-6 (beta = −0.306, p = 0.026) predicted negative symptoms slopes, along with depressive symptom severity at baseline (beta = −0.596, p = 0.000). These findings demonstrate that inflammatory cytokines may underlie the development of negative symptoms in some individuals at CHR for psychosis. TNF predicted the development of negative symptoms independent of baseline depression. Given the heterogeneity of the CHR population, the comorbidity of negative symptoms and depression in this population, and the particular challenges in treating negative symptoms, immune markers could represent potential biomarkers that underlie the development of negative symptoms, representing a potential treatment target

Acceptance and Use of E-Learning Based on Cloud Computing: The Role of Consumer Innovativeness

Cloud computing and E-learning are the inevitable trend of computational science in general, and information systems and technologies in specific.However, there are not many studies on the adoption of cloud-based E-learning systems. Moreover, while there are many papers on information system adoption as well as customer innovativeness, the innovativeness and adoption in the same model seems to be rare in the literature. The study combines the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and consumer innovativeness on the adoption of E-learning systems based on cloud computing. A survey was conducted among 282 cloud-based E-learning participants and analyzed by structural equation modeling (SEM). The findings indicate that the adoption of cloud-based E-learning is influenced by performance expectancy, social influence, hedonic motivation, and habit. Interestingly, although innovativeness is not significant to use intention, it has a positive effect on E-learning usage which is relatively new in Vietnam

On the origin and evolution of the material in 67P/Churyumov-Gerasimenko

International audiencePrimitive objects like comets hold important information on the material that formed our solar system. Several comets have been visited by spacecraft and many more have been observed through Earth- and space-based telescopes. Still our understanding remains limited. Molecular abundances in comets have been shown to be similar to interstellar ices and thus indicate that common processes and conditions were involved in their formation. The samples returned by the Stardust mission to comet Wild 2 showed that the bulk refractory material was processed by high temperatures in the vicinity of the early sun. The recent Rosetta mission acquired a wealth of new data on the composition of comet 67P/Churyumov-Gerasimenko (hereafter 67P/C-G) and complemented earlier observations of other comets. The isotopic, elemental, and molecular abundances of the volatile, semi-volatile, and refractory phases brought many new insights into the origin and processing of the incorporated material. The emerging picture after Rosetta is that at least part of the volatile material was formed before the solar system and that cometary nuclei agglomerated over a wide range of heliocentric distances, different from where they are found today. Deviations from bulk solar system abundances indicate that the material was not fully homogenized at the location of comet formation, despite the radial mixing implied by the Stardust results. Post-formation evolution of the material might play an important role, which further complicates the picture. This paper discusses these major findings of the Rosetta mission with respect to the origin of the material and puts them in the context of what we know from other comets and solar system objects

Physical Processes in Star Formation

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00693-8.Star formation is a complex multi-scale phenomenon that is of significant importance for astrophysics in general. Stars and star formation are key pillars in observational astronomy from local star forming regions in the Milky Way up to high-redshift galaxies. From a theoretical perspective, star formation and feedback processes (radiation, winds, and supernovae) play a pivotal role in advancing our understanding of the physical processes at work, both individually and of their interactions. In this review we will give an overview of the main processes that are important for the understanding of star formation. We start with an observationally motivated view on star formation from a global perspective and outline the general paradigm of the life-cycle of molecular clouds, in which star formation is the key process to close the cycle. After that we focus on the thermal and chemical aspects in star forming regions, discuss turbulence and magnetic fields as well as gravitational forces. Finally, we review the most important stellar feedback mechanisms.Peer reviewedFinal Accepted Versio

Quantitative laser-induced fluorescence: some recent developments in combustion diagnostics

Kohse-Höinghaus K. Quantitative laser-induced fluorescence: some recent developments in combustion diagnostics. Applied Physics, B. 1990;50(6):455-461.This report summarizes several recent applications of quantitative laser-induced fluorescence techniques for the determination of species concentrations and temperature in combustion processes. Several lines of further development are discusse