How are emergent constraints quantifying uncertainty and what do they leave behind?

The use of emergent constraints to quantify uncertainty for key policy relevant quantities such as Equilibrium Climate Sensitivity (ECS) has become increasingly widespread in recent years. Many researchers, however, claim that emergent constraints are inappropriate or even under-report uncertainty. In this paper we contribute to this discussion by examining the emergent constraints methodology in terms of its underpinning statistical assumptions. We argue that the existing frameworks are based on indefensible assumptions, then show how weakening them leads to a more transparent Bayesian framework wherein hitherto ignored sources of uncertainty, such as how reality might differ from models, can be quantified. We present a guided framework for the quantification of additional uncertainties that is linked to the confidence we can have in the underpinning physical arguments for using linear constraints. We provide a software tool for implementing our general framework for emergent constraints and use it to illustrate the framework on a number of recent emergent constraints for ECS. We find that the robustness of any constraint to additional uncertainties depends strongly on the confidence we can have in the underpinning physics, allowing a future framing of the debate over the validity of a particular constraint around the underlying physical arguments, rather than statistical assumptions

Controlled partial embedding of carbon nanotubes within flexible transparent layers

Applications of carbon nanotubes (CNTs) like field emission displays, super-capacitors, and cell growth scaffolds can benefit from controllable embedding of the CNTs in a material such that the CNTs are anchored and protrude a desired length. We demonstrate a simple method for anchoring densely packed, vertically aligned arrays of CNTs into silicone layers using spin-coating, CNT insertion, curing, and growth substrate removal. CNT arrays of 51 and 120 µm in height are anchored into silicone layers of thickness 26 and 36 µm, respectively. Scanning electron microscopy (SEM) and optical microscopy are used to characterize the sample morphology, a 5.5 m s^-1 impinging water jet is used to apply shear stress, and a tensile test shows that the silicone layer detaches from the substrate before the CNTs are ripped from the layer. The CNTs are thus well anchored in the silicone layers. The spin-coating process gives control over layer thickness, and the method should have general applicability to various nanostructures and anchoring materials

A Bayesian framework for verification and recalibration of ensemble forecasts: How uncertain is NAO predictability?

Predictability estimates of ensemble prediction systems are uncertain due to limited numbers of past forecasts and observations. To account for such uncertainty, this paper proposes a Bayesian inferential framework that provides a simple 6-parameter representation of ensemble forecasting systems and the corresponding observations. The framework is probabilistic, and thus allows for quantifying uncertainty in predictability measures such as correlation skill and signal-to-noise ratios. It also provides a natural way to produce recalibrated probabilistic predictions from uncalibrated ensembles forecasts. The framework is used to address important questions concerning the skill of winter hindcasts of the North Atlantic Oscillation for 1992-2011 issued by the Met Office GloSea5 climate prediction system. Although there is much uncertainty in the correlation between ensemble mean and observations, there is strong evidence of skill: the 95% credible interval of the correlation coefficient of [0.19,0.68] does not overlap zero. There is also strong evidence that the forecasts are not exchangeable with the observations: With over 99% certainty, the signal-to-noise ratio of the forecasts is smaller than the signal-to-noise ratio of the observations, which suggests that raw forecasts should not be taken as representative scenarios of the observations. Forecast recalibration is thus required, which can be coherently addressed within the proposed framework.Comment: 36 pages, 10 figure

How directed is a directed network?

The trophic levels of nodes in directed networks can reveal their functional properties. Moreover, the trophic coherence of a network, defined in terms of trophic levels, is related to properties such as cycle structure, stability and percolation. The standard definition of trophic levels, however, borrowed from ecology, suffers from drawbacks such as requiring basal nodes, which limit its applicability. Here we propose simple improved definitions of trophic levels and coherence that can be computed on any directed network. We demonstrate how the method can identify node function in examples including ecosystems, supply chain networks, gene expression and global language networks. We also explore how trophic levels and coherence relate to other topological properties, such as non-normality and cycle structure, and show that our method reveals the extent to which the edges in a directed network are aligned in a global direction

c-Src drives intestinal regeneration and transformation

The non‐receptor tyrosine kinase c‐Src, hereafter referred to as Src, is overexpressed or activated in multiple human malignancies. There has been much speculation about the functional role of Src in colorectal cancer (CRC), with Src amplification and potential activating mutations in up to 20% of the human tumours, although this has never been addressed due to multiple redundant family members. Here, we have used the adult <i>Drosophila</i> and mouse intestinal epithelium as paradigms to define a role for Src during tissue homeostasis, damage‐induced regeneration and hyperplasia. Through genetic gain and loss of function experiments, we demonstrate that Src is necessary and sufficient to drive intestinal stem cell (ISC) proliferation during tissue self‐renewal, regeneration and tumourigenesis. Surprisingly, Src plays a non‐redundant role in the mouse intestine, which cannot be substituted by the other family kinases Fyn and Yes. Mechanistically, we show that Src drives ISC proliferation through upregulation of EGFR and activation of Ras/MAPK and Stat3 signalling. Therefore, we demonstrate a novel essential role for Src in intestinal stem/progenitor cell proliferation and tumourigenesis initiation <i>in vivo.</i&gt

Inherent-opening-controlled pattern formation in carbon nanotube arrays

We have introduced inherent openings into densely packed carbon nanotube arrays to study self-organized pattern formation when the arrays undergo a wetting–dewetting treatment from nanotube tips. These inherent openings, made of circular or elongated hollows in nanotube mats, serve as dewetting centres, from where liquid recedes from. As the dewetting centres initiate dry zones and the dry zones expand, surrounding nanotubes are pulled away from the dewetting centres by liquid surface tension. Among short nanotubes, the self-organized patterns are consistent with the shape of the inherent openings, i.e. slender openings lead to elongated trench-like structures, and circular holes result in relatively round nest-like arrangements. Nanotubes in a relatively high mat are more connected, like in an elastic body, than those in a short mat. Small cracks often initialize themselves in a relatively high mat, along two or more adjacent round openings; each of the cracks evolves into a trench as liquid dries up. Self-organized pattern control with inherent openings needs to initiate the dewetting process above the nanotube tips. If there is no liquid on top, inherent openings barely enlarge themselves after the wetting–dewetting treatment

Association of Peripheral Membrane Proteins with Membranes: Free Energy of Binding of GRP1 PH Domain with Phosphatidylinositol Phosphate-Containing Model Bilayers

Understanding the energetics of peripheral protein-membrane interactions is important to many areas of biophysical chemistry and cell biology. Estimating free-energy landscapes by molecular dynamics (MD) simulation is challenging for such systems, especially when membrane recognition involves complex lipids, e.g., phosphatidylinositol phosphates (PIPs). We combined coarse-grained MD simulations with umbrella sampling to quantify the binding of the well-explored GRP1 pleckstrin homology (PH) domain to model membranes containing PIP molecules. The experimentally observed preference of GRP1-PH for PIP3 over PIP2 was reproduced. Mutation of a key residue (K273A) within the canonical PIP-binding site significantly reduced the free energy of PIP binding. The presence of a noncanonical PIP-interaction site, observed experimentally in other PH domains but not previously in GRP1-PH, was also revealed. These studies demonstrate how combining coarse-grained simulations and umbrella sampling can unmask the molecular basis of the energetics of interactions between peripheral membrane proteins and complex cellular membranes