Life-span Extension With Reduced Somatotrophic Signaling: Moderation of Aging Effect by Signal Type, Sex, and Experimental Cohort.

Reduced somatotrophic signaling through the growth hormone (GH) and insulin-like growth factor pathways (IGF1) can delay aging, although the degree of life-extension varies markedly across studies. By collating data from previous studies and using meta-analysis, we tested whether factors including sex, hormonal manipulation, body weight change and control baseline mortality quantitatively predict relative lifeextension. Manipulations of GH signaling (including pituitary and direct GH deficiencies) generate significantly greater extension in median life span than IGF1 manipulations (including IGF1 production, reception, and bioactivity), producing a consistent shift in mortality risk of mutant mice. Reduced Insulin receptor substrate (IRS) expression produces more similar life-extension to reduced GH, although effects are more heterogeneous and appear to influence the demography of mortality differently. Life-extension with reduced IGF1 signaling, but neither GH nor IRS signaling, increases life span significantly more in females than males, and in cohorts where control survival is short. Our results thus suggest that reduced GH signaling has physiological benefits to survival outside of its actions on circulating IGF1. In addition to these biological moderators, we found an overrepresentation of small sample sized studies that report large improvements in survival, indicating potential publication bias. We discuss how this could potentially confound current conclusions from published work, and how this warrants further study replication

Comparative idiosyncrasies in life extension by reduced mTOR signalling and its distinctiveness from dietary restriction.

Reduced mechanistic target of rapamycin (mTOR) signalling extends lifespan in yeast, nematodes, fruit flies and mice, highlighting a physiological pathway that could modulate aging in evolutionarily divergent organisms. This signalling system is also hypothesized to play a central role in lifespan extension via dietary restriction. By collating data from 48 available published studies examining lifespan with reduced mTOR signalling, we show that reduced mTOR signalling provides similar increases in median lifespan across species, with genetic mTOR manipulations consistently providing greater life extension than pharmacological treatment with rapamycin. In contrast to the consistency in changes in median lifespan, however, the demographic causes for life extension are highly species specific. Reduced mTOR signalling extends lifespan in nematodes by strongly reducing the degree to which mortality rates increase with age (aging rate). By contrast, life extension in mice and yeast occurs largely by pushing back the onset of aging, but not altering the shape of the mortality curve once aging starts. Importantly, in mice, the altered pattern of mortality induced by reduced mTOR signalling is different to that induced by dietary restriction, which reduces the rate of aging. Effects of mTOR signalling were also sex dependent, but only within mice, and not within flies, thus again species specific. An alleviation of age-associated mortality is not a shared feature of reduced mTOR signalling across model organisms and does not replicate the established age-related survival benefits of dietary restriction

Local pairing of Feynman histories in many-body Floquet models

We study many-body quantum dynamics using Floquet quantum circuits in one space dimension as simple examples of systems with local interactions that support ergodic phases. Physical properties can be expressed in terms of multiple sums over Feynman histories, which for these models are paths or many-body orbits in Fock space. A natural simplification of such sums is the diagonal approximation, where the only terms that are retained are ones in which each path is paired with a partner that carries the complex conjugate weight. We identify the regime in which the diagonal approximation holds, and the nature of the leading corrections to it. We focus on the behaviour of the spectral form factor (SFF) and of matrix elements of local operators, averaged over an ensemble of random circuits, making comparisons with the predictions of random matrix theory (RMT) and the eigenstate thermalisation hypothesis (ETH). We show that properties are dominated at long times by contributions to orbit sums in which each orbit is paired locally with a conjugate, as in the diagonal approximation, but that in large systems these contributions consist of many spatial domains, with distinct local pairings in neighbouring domains. The existence of these domains is reflected in deviations of the SFF from RMT predictions, and of matrix element correlations from ETH predictions; deviations of both kinds diverge with system size. We demonstrate that our physical picture of orbit-pairing domains has a precise correspondence in the spectral properties of a transfer matrix that acts in the space direction to generate the ensemble-averaged SFF. In addition, we find that domains of a second type control non-Gaussian fluctuations of the SFF. These domains are separated by walls which are related to the entanglement membrane, known to characterise the scrambling of quantum information.Comment: 22+7 page

Many-body delocalisation as symmetry breaking

We present a framework in which the transition between a many-body localised (MBL) phase and an ergodic one is symmetry breaking. We consider random Floquet spin chains, expressing their averaged spectral form factor (SFF) as a function of time in terms of a transfer matrix that acts in the space direction. The SFF is determined by the leading eigenvalues of this transfer matrix. In the MBL phase the leading eigenvalue is unique, as in a symmetry-unbroken phase, while in the ergodic phase and at late times the leading eigenvalues are asymptotically degenerate, as in a system with degenerate symmetry-breaking phases. We identify the broken symmetry of the transfer matrix, introduce a local order parameter for the transition, and show that the associated correlation functions are long-ranged only in the ergodic phase.Comment: 5+5 page

Automatic Multi-Class Collective Motion Recognition Using a Decision Forest Extracted from Neural Networks

This paper presents an approach to machine recognition of multiple classes of collective motion behaviours. Previous work has demonstrated that it is possible to distinguish structured collective motion from random, unstructured motion. However, it has proved difficult to use such techniques for automatically recognising specific collective motion variants such as moving in a line versus moving in a group. To enable a knowledge base to recognise multiple classes of collective motion, this paper proposes a decision forest approach. The proposed approach extracts machine-understandable knowledge from a neural network trained to automatically recognise collective motions. The main advantage of this approach is that besides being automatic, it is fast, accurate and easy to use. We show that our deep neural network achieves 90.30% accuracy for multi-class labelling of collective motion behaviours, which is more accurate than shallow neural networks for this problem. Furthermore, a knowledge base extracted using the decision forest on the deep neural network can recognise the class of random behaviour and the eight classes of collective motion behaviours with 88.81% accuracy in just 0.03 seconds, which is only 1.49% less accurate than the original deep neural network, but over 100 times faster

Macroeconometric Modelling with a Global Perspective

This paper provides a synthesis and further development of a global modelling approach introduced in Pesaran, Schuermann and Weiner (2004), where country specific models in the form of VARX* structures are estimated relating a vector of domestic variables to their foreign counterparts and then consistently combined to form a Global VAR (GVAR). It is shown that VARX* models can be derived as the solution to a dynamic stochastic general equilibrium (DSGE) model where over-identifying long-run theoretical relations can be tested and imposed if acceptable. Similarly, short-run over-identifying theoretical restrictions can be tested and imposed if accepted. The assumption of the weak exogeneity of the foreign variables for the long-run parameters can be tested, where foreign variables can be interpreted as proxies for global factors. Rather than using deviations from ad hoc statistical trends, the equilibrium values of the variables reflecting the long-run theory embodied in the model can be calculated

How should we turn data into decisions in AgriFood?

The AgriFood supply chain is under significant pressures related to food security, climate change, and consumer demands for affordable and higher quality food. Various technologies are already deployed producing a large amount of data, which can be utilised to guide decision-making to improve productivity, reduce wastage, and increase traceability across the AgriFood supply chain. Several examples of the use of data are given, including improving efficiency in livestock production, supporting automation and use of robotics in crop production, increasing food safety and evidencing its provenance. The opportunities and ways forward were discussed at a workshop in November 2017, run by the Society of Chemical Industry and the Knowledge Transfer Network in the UK. This paper presents a summary of the key messages from the presentations and focus-group discussions during this event, as interpreted by the authors. A number of challenges in digitalisation of the AgriFood supply chain are discussed, such as low inter-operability of different data sets, silo mentality, low willingness to share data and a significant skills gap. Various approaches are presented that could help to unlock the benefits of using data, from practical support to producers and addressing skills gaps, to industrial leadership and the role of government departments and regulatory bodies in leading by example. Looking forward, data are already revolutionising the AgriFood supply chain, however, the benefits will remain piecemeal until the leaders of today are able to bring together the disparate groups into a cohesive whole

Direct characterisation of tuneable few-femtosecond dispersive-wave pulses in the deep UV

Dispersive wave emission (DWE) in gas-filled hollow-core dielectric waveguides is a promising source of tuneable coherent and broadband radiation, but so far the generation of few-femtosecond pulses using this technique has not been demonstrated. Using in-vacuum frequency-resolved optical gating, we directly characterise tuneable 3fs pulses in the deep ultraviolet generated via DWE. Through numerical simulations, we identify that the use of a pressure gradient in the waveguide is critical for the generation of short pulses.Comment: 5 pages, 4 figure

The importance of soil and vegetation characteristics for establishing ground nesting bee aggregations

Most bee species are ground-nesters, yet knowledge on the nesting behaviour of this diverse group remains sparse. Evidence on the effectiveness of ground-nesting bee species as crop pollinators is growing, but there is limited information on their nesting habits and preferences and how to manage habitats to enhance populations on farms. In this study, artificially prepared plots of bare soil were constructed with the aim to attract ground-nesting bees to nest in a commercial orchard in Kent, UK. Nine soil parameters were measured to determine their preferred soil properties: hydraulic conductivity, soil compaction, soil moisture, soil temperature, soil stoniness, soil organic matter, soil root biomass, soil texture and vegetation cover. Eighteen non-parasitic ground-nesting bee species (7 Andrena, 9 Lasioglossum, 1 Halictus and 1 Colletes spp.) were recorded in the study plots. Soil stoniness and soil temperature at 10cm depth were positively correlated, and vegetation cover and hydraulic conductivity were negatively correlated with the number of ground-nesting bees on the plots. We show that artificially created habitats can be exploited for nesting by several ground-nesting bee species. This study’s findings can inform management practices to enhance ground-nesting bee populations in agricultural and urban areas