A brief history of long memory: Hurst, Mandelbrot and the road to ARFIMA

Long memory plays an important role in many fields by determining the behaviour and predictability of systems; for instance, climate, hydrology, finance, networks and DNA sequencing. In particular, it is important to test if a process is exhibiting long memory since that impacts the accuracy and confidence with which one may predict future events on the basis of a small amount of historical data. A major force in the development and study of long memory was the late Benoit B. Mandelbrot. Here we discuss the original motivation of the development of long memory and Mandelbrot's influence on this fascinating field. We will also elucidate the sometimes contrasting approaches to long memory in different scientific communitiesComment: 40 page

The Nervous System And Cancers Of The Head And Neck

The anatomy of the head and neck is closely associated with the nervous system which plays an important role in the prognosis of head and neck cancer (HNC). However, the molecular interactions between these compartments and HNC remain poorly understood. We present a novel big data approach utilizing clinical data, sequencing, and machine learning to identify and validate potential molecular pathways by which the nervous system affects the development and progression of HNC. Our studies demonstrate across multiple datasets that perineural invasion (PNI) frequently occurs in HPV+ HNC. Furthermore, we show novel activating and missense mutations and pathways that may play important roles in the progression of HNC. We hypothesized that HPV+ cancers might be driven by different neurotrophic-associated genes and programs. We observed that neuroendocrine and neurotrophin signaling through the nerve growth factor receptor (NGFR) can be observed in differentiating HPV+ versus HPV- and PNI+ versus PNI- HNC. These observations may provide significant therapeutic targets for HNC

Systematic inference of the long-range dependence and heavy-tail distribution parameters of ARFIMA models

Long-Range Dependence (LRD) and heavy-tailed distributions are ubiquitous in natural and socio-economic data. Such data can be self-similar whereby both LRD and heavy-tailed distributions contribute to the self-similarity as measured by the Hurst exponent. Some methods widely used in the physical sciences separately estimate these two parameters, which can lead to estimation bias. Those which do simultaneous estimation are based on frequentist methods such as Whittle’s approximate maximum likelihood estimator. Here we present a new and systematic Bayesian framework for the simultaneous inference of the LRD and heavy-tailed distribution parameters of a parametric ARFIMA model with non-Gaussian innovations. As innovations we use the α-stable and t-distributions which have power law tails. Our algorithm also provides parameter uncertainty estimates. We test our algorithm using synthetic data, and also data from the Geostationary Operational Environmental Satellite system (GOES) solar X-ray time series. These tests show that our algorithm is able to accurately and robustly estimate the LRD and heavy-tailed distribution parameters

Agglomeration Dynamics of 1D Materials: Gas-Phase Collision Rates of Nanotubes and Nanorods.

The agglomeration and self-assembly of gas-phase 1D materials in anthropogenic and natural systems dictate their resulting nanoscale morphology, multiscale hierarchy, and ultimate macroscale properties. Brownian motion induces collisions, upon which 1D materials often restructure to form bundles and can lead to aerogels. Herein, the first results of collision rates for 1D nanomaterials undergoing thermal transport are presented. The Langevin dynamic simulations of nanotube rotation and translation demonstrate that the collision kernels for rigid nanotubes or nanorods are ≈10 times greater than spherical systems. Resulting reduced order equations allow straightforward calculation of the physical parameters to determine the collision kernel for straight and curved 1D materials from 102 to 106 nm length. The collision kernels of curved 1D structures increase ≈1.3 times for long (>102 nm), and ≈5 times for short (≈102 nm) relative to rigid materials. Applications of collision frequencies allow the first kinetic analysis of aerogel self-assembly from gas-phase carbon nanotubes (CNTs). The timescales for CNT collision and bundle formation (0.3-42 s) agree with empirical residence times in CNT reactors (3-15 s). These results provide insights into the CNT length, number, and timescales required for aerogel formation, which bolsters our understanding of mass-produced 1D aerogel materials.EPSRC: EP/M015211/

Alley coppice—a new system with ancient roots

International audience& Context Current production from natural forests will not satisfy future world demand for timber and fuel wood, and new land management options are required. & Aims We explore an innovative production system that combines the production of short rotation coppice in wide alleys with the production of high-value trees on narrow strips of land; it is an alternative form of alley cropping which we propose to call 'alley coppice'. The aim is to describe this alley coppice system and to illustrate its potential for produc-ing two diverse products, namely high-value timber and ener-gy wood on the same land unit. & Methods Based on a comprehensive literature review, we compare the advantages and disadvantages of the alley cop-pice system and contrast the features with well-known existing or past systems of biomass and wood production. & Results We describe and discuss the basic aspects of alley coppice, its design and dynamics, the processes of competi-tion and facilitation, issues of ecology, and areas that are open for future research. & Conclusion Based on existing knowledge, a solid founda-tion for the implementation of alley coppice on suitable land is presented, and the high potential of this system could be shown

Irreversible transformation of ferromagnetic ordered stripe domains in single-shot IR pump - resonant X-ray scattering probe experiments

The evolution of a magnetic domain structure upon excitation by an intense, femtosecond Infra-Red (IR) laser pulse has been investigated using single-shot based time-resolved resonant X-ray scattering at the X-ray Free Electron laser LCLS. A well-ordered stripe domain pattern as present in a thin CoPd alloy film has been used as prototype magnetic domain structure for this study. The fluence of the IR laser pump pulse was sufficient to lead to an almost complete quenching of the magnetization within the ultrafast demagnetization process taking place within the first few hundreds of femtoseconds following the IR laser pump pulse excitation. On longer time scales this excitation gave rise to subsequent irreversible transformations of the magnetic domain structure. Under our specific experimental conditions, it took about 2 nanoseconds before the magnetization started to recover. After about 5 nanoseconds the previously ordered stripe domain structure had evolved into a disordered labyrinth domain structure. Surprisingly, we observe after about 7 nanoseconds the occurrence of a partially ordered stripe domain structure reoriented into a novel direction. It is this domain structure in which the sample's magnetization stabilizes as revealed by scattering patterns recorded long after the initial pump-probe cycle. Using micro-magnetic simulations we can explain this observation based on changes of the magnetic anisotropy going along with heat dissipation in the film.Comment: 16 pages, 6 figure

Fluid dynamics and slope stability offshore W-Spitsbergen: Effect of bottom water warming on gas hydrates and slope stability - Cruise No. MSM21/4 - August 12 - September 11, 2012 - Reykjavik (Iceland) - Emden (Germany)

The main goal of MSM21/4 was the study of gas hydrate system off Svalbard. We addressed this through a comprehensive scientific programme comprising dives with the manned submersible JAGO, seismic and heat flow measurements, sediment coring, water column biogeochemistry and bathymetric mapping. At the interception of the Knipovich Ridge and the continental margin of Svalbard we collected seismic data and four heat flow measurements. These measurements revealed that the extent of hydrates is significantly larger than previously thought and that the gas hydrate system is influenced by heat from the oceanic spreading centre, which may promote thermogenic methane production and thus explain the large extent of hydrates. At the landward termination of the hydrate stability zone we investigated the mechanisms that lead to degassing by taking sediment cores, sampling of carbonates during dives, and measuring the methane turn-over rates in the water column. It turned out that the observed gas seepage must have been ongoing for a long time and that decadal scale warming is an unlikely explanation for the observed seeps. Instead seasonal variations in water temperatures seem to control episodic hydrate formation and dissociation explaining the location of the observed seeps. The water column above the gas flares is rich in methane and methanotrophic microorganisms turning over most of the methane that escapes from the sea floor. We also surveyed large, until then uncharted parts of the margin in the northern part of the gas hydrate province. Here, we discovered an almost 40 km wide submarine landslide complex. This slide is unusual in the sense that it is not located at the mouth of a cross shelf trough such as other submarine landslides on the glaciated continental margins around the North Atlantic. Thus, the most widely accepted explanation for the origin of such slides, i.e. overpressure development due to deposition of glacial sediments on top of water rich contourites, is not applicable. Instead we find gas-hydrate-related bottom simulating reflectors underneath the headwalls of this slide complex, possibly indicating that subsurface fluid migration plays a major role in its genesis

Identification of agroforestry systems and practices to model

This report is an output from work-package 6 which contributes to the third objective. Work-package 6 focuses on the field- and farm-scale evaluation of innovation research that have arisen from about 40 agroforestry stakeholder groups created across Europe. Some research, for example tree protection options, are best determined by technical evaluations in the field. However some research questions require a modelling approach to predict, for example, the financial and economic impact of a new practice over a number of years. This report seeks to identify those agroforestry systems and practices which could be usefully assessed using biophysical agroforestry models such as Yield-SAFE (van der Werf et al., 2007) and Hi-sAFe (Talbot, 2011), or bio-economic models such as Farm-SAFE (Graves et al., 2011)