Analysis of a bistable climate toy model with physics-based machine learning methods

We propose a comprehensive framework able to address both the predictability of the first and of the second kind for high-dimensional chaotic models. For this purpose, we analyse the properties of a newly introduced multistable climate toy model constructed by coupling the Lorenz ’96 model with a zero-dimensional energy balance model. First, the attractors of the system are identified with Monte Carlo Basin Bifurcation Analysis. Additionally, we are able to detect the Melancholia state separating the two attractors. Then, Neural Ordinary Differential Equations are applied to predict the future state of the system in both of the identified attractors

Self-directed learning and absorptive capacity: the mediating role of trust and human capital

This chapter aims to provide a better understanding of how self-directed learning effects absorptive capacity by examining the influence of two mediators: specifically, affective trust in colleagues and human capital development climate. By using a sample of 181 participants from the creative industries sector, a sequential mediation via a three-step causal chain was conducted. This chapter contributes to human resource development and strategic management literature in showing that self-directed learning does not only have a strong effect on the organisational capability, but it also has an impact at the group-level dynamics involving trust and organisational-level climate. These findings show that organisations need to design jobs that allow discretion and autonomy from staff to shape their own learning and to cultivate an environment that recognises and rewards learning

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

© 2014 Elsevier Inc. Recent genomic analyses of pathologically defined tumor types identify 'within-a-tissue' disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-oforigin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pancancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies