13 research outputs found
SEAM: An Integrated Activation-Coupled Model of Sentence Processing and Eye Movements in Reading
Models of eye-movement control during reading, developed largely within
psychology, usually focus on visual, attentional, lexical, and motor processes
but neglect post-lexical language processing; by contrast, models of sentence
comprehension processes, developed largely within psycholinguistics, generally
focus only on post-lexical language processes. We present a model that combines
these two research threads, by integrating eye-movement control and sentence
processing. Developing such an integrated model is extremely challenging and
computationally demanding, but such an integration is an important step toward
complete mathematical models of natural language comprehension in reading. We
combine the SWIFT model of eye-movement control (Seelig et al., 2020,
doi:10.1016/j.jmp.2019.102313) with key components of the Lewis and Vasishth
sentence processing model (Lewis & Vasishth, 2005,
doi:10.1207/s15516709cog0000_25). This integration becomes possible, for the
first time, due in part to recent advances in successful parameter
identification in dynamical models, which allows us to investigate profile
log-likelihoods for individual model parameters. We present a fully implemented
proof-of-concept model demonstrating how such an integrated model can be
achieved; our approach includes Bayesian model inference with Markov Chain
Monte Carlo (MCMC) sampling as a key computational tool. The integrated model,
SEAM, can successfully reproduce eye movement patterns that arise due to
similarity-based interference in reading. To our knowledge, this is the
first-ever integration of a complete process model of eye-movement control with
linguistic dependency completion processes in sentence comprehension. In future
work, this proof of concept model will need to be evaluated using a
comprehensive set of benchmark data
BottomâUp Assembly of DNAâSilica Nanocomposites into MicrometerâSized Hollow Spheres
Although DNA nanotechnology has developed into a highly innovative and lively field of research at the interface between chemistry, materials science, and biotechnology, there is still a great need for methodological approaches for bridging the size regime of DNA nanostructures with that of micrometerâ and millimeterâsized units for practical applications. We report on novel hierarchically structured composite materials from silica nanoparticles and DNA polymers that can be obtained by selfâassembly through the clamped hybridization chain reaction. The nanocomposite materials can be assembled into thin layers within microfluidically generated waterâinâoil droplets to produce mechanically stabilized hollow spheres with uniform size distributions at high throughput rates. The fact that cells can be encapsulated in these microcontainers suggests that our concept not only contributes to the further development of supramolecular bottomâup manufacturing, but can also be exploited for applications in the life sciences
Outcome of acute respiratory distress syndrome in university and non-university hospitals in Germany
Overview of the MOSAiC expedition - Atmosphere
With the Arctic rapidly changing, the needs to observe, understand, and model the changes are essential. To support these needs, an annual cycle of observations of atmospheric properties, processes, and interactions were made while drifting with the sea ice across the central Arctic during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition from October 2019 to September 2020. An international team designed and implemented the comprehensive program to document and characterize all aspects of the Arctic atmospheric system in unprecedented detail, using a variety of approaches, and across multiple scales. These measurements were coordinated with other observational teams to explore cross-cutting and coupled interactions with the Arctic Ocean, sea ice, and ecosystem through a variety of physical and biogeochemical processes. This overview outlines the breadth and complexity of the atmospheric research program, which was organized into 4 subgroups: atmospheric state, clouds and precipitation, gases and aerosols, and energy budgets. Atmospheric variability over the annual cycle revealed important influences from a persistent large-scale winter circulation pattern, leading to some storms with pressure and winds that were outside the interquartile range of past conditions suggested by long-term reanalysis. Similarly, the MOSAiC location was warmer and wetter in summer than the reanalysis climatology, in part due to its close proximity to the sea ice edge. The comprehensiveness of the observational program for characterizing and analyzing atmospheric phenomena is demonstrated via a winter case study examining air mass transitions and a summer case study examining vertical atmospheric evolution. Overall, the MOSAiC atmospheric program successfully met its objectives and was the most comprehensive atmospheric measurement program to date conducted over the Arctic sea ice. The obtained data will support a broad range of coupled-system scientific research and provide an important foundation for advancing multiscale modeling capabilities in the Arctic