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Trajectory inference methods have emerged as a novel class of single-cell bioinformatics tools to study cellular dynamics at unprecedented resolution. Initial development focused on adapting methods based on clustering or graph traversal, but recent advanc ...
The complexity of the human brain makes its understanding one of the biggest challenges that science is currently confronting. Due to its complexity, the brain has been studied at many different levels and from many disciplines and points of view, using a ...
In this paper, we will present an update for the previously developed CCFatigue computational tool. This tool has been built around several analysis methods for fatigue life predictions of composite materials and includes modules that allow analysis over c ...
Evaluating a three-dimensional lake model requires large datasets of many variables, including velocity fields, that are seldom available. Here we discuss how to assess the performance of a model at multiple scales (in time and space) with data from standa ...
Humans effortlessly solve push tasks in everyday life but unlocking these capabilities remains a research challenge in robotics. Physical models are often inaccurate or unattainable. State-of-the-art data-driven approaches learn to compensate for these ina ...
Vegetation plays a fundamental role in riverine environments, by affecting both hydrodynamics and morphodynamics. At the same time, flow velocity and sediment scouring influence the decay of plants by uprooting. The balance among such interactions defines ...
The RAPTOR suite of codes combines real-time model-based predictions of the plasma state with the available diagnostic measurements. Following the work on TCV and ASDEX-Upgrade, this paper presents the implementation of the RAPTOR suite for JET. This suite ...
We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...
University chemical laboratories, contrary to common perception, are dangerous working environments. Unlike industry, where most processes are standardized, in academia, they are modified so frequently that in-depth and detailed risk assessment becomes unf ...
Data cleaning has become an indispensable part of data analysis due to the increasing amount of dirty data. Data scientists spend most of their time preparing dirty data before it can be used for data analysis. Existing solutions that attempt to automate t ...
