Testing for financial crashes using the Log Periodic Power Law model

Many papers claim that a Log Periodic Power Law (LPPL) model fitted to financial market bubbles that precede large market falls or 'crashes', contains parameters that are confined within certain ranges. Further, it is claimed that the underlying model is based on influence percolation and a martingale condition. This paper examines these claims and their validity for capturing large price falls in the Hang Seng stock market index over the period 1970 to 2008. The fitted LPPLs have parameter values within the ranges specified post hoc by Johansen and Sornette (2001) for only seven of these 11 crashes. Interestingly, the LPPL fit could have predicted the substantial fall in the Hang Seng index during the recent global downturn. Overall, the mechanism posited as underlying the LPPL model does not do so, and the data used to support the fit of the LPPL model to bubbles does so only partially. © 2013.

Size frequency distributions of the florid prion protein aggregates in variant Creutzfeldt-Jakob disease follow a power-law function

The objective was to test the hypothesis that the size frequency distributions of the prion protein (PrP) plaques in cases of variant Creutzfeldt-Jakob disease (vCJD) follow a power-law function. The design was a retrospective neuropathological study. The patients were 11 cases of clinically and neuropathologically verified vCJD. Size distributions of the diffuse and florid-type plaques were measured in several areas of the cerebral cortex and hippocampus from each case and a power-law function fitted to each distribution. The size distributions of the florid and diffuse plaques were fitted successfully by a powerlaw function in 100% and 42% of brain areas investigated respectively. Processes of aggregation/disaggregation may be more important than surface diffusion in the pathogenesis of the florid plaques. By contrast, surface diffusion may be a more significant factor in the development of the diffuse plaques. © Springer-Verlag Italia 2006.

Size frequency distribution of the β-amyloid (aβ) deposits in dementia with Lewy bodies with associated Alzheimer’s disease pathology

The objective is to study beta-amyloid (Abeta) deposition in dementia with Lewy bodies (DLB) with Alzheimer's disease (AD) pathology (DLB/AD). The size frequency distributions of the Abeta deposits were studied and fitted by log-normal and power-law models. Patients were ten clinically and pathologically diagnosed DLB/AD cases. Size distributions had a single peak and were positively skewed and similar to those described in AD and Down's syndrome. Size distributions had smaller means in DLB/AD than in AD. Log-normal and power-law models were fitted to the size distributions of the classic and diffuse deposits, respectively. Size distributions of Abeta deposits were similar in DLB/AD and AD. Size distributions of the diffuse deposits were fitted by a power-law model suggesting that aggregation/disaggregation of Abeta was the predominant factor, whereas the classic deposits were fitted by a log-normal distribution suggesting that surface diffusion was important in the pathogenesis of the classic deposits.

Size frequency distributions of β-amyloid (Aβ) deposits:a comparative study of four neurodegenerative disorders

Deposition of ß-amyloid (Aß ), a 'signature' pathological lesion of Alzheimer's disease (AD), is also characteristic of Down's syndrome (DS), and has been observed in dementia with Lewy bodies (DLB) and corticobasal degeneration (CBD). To determine whether the growth of Aß deposits was similar in these disorders, the size frequency distributions of the diffuse ('pre-amyloid'), primitive ('neuritic'), and classic ('dense-cored') A ß deposits were compared in AD, DS, DLB, and CBD. All size distributions had essentially the same shape, i.e., they were unimodal and positively skewed. Mean size of Aß deposits, however, varied between disorders. Mean diameters of the diffuse, primitive, and classic deposits were greatest in DS, DS and CBD, and DS, respectively, while the smallest deposits, on average, were recorded in DLB. Although the shape of the frequency distributions was approximately log-normal, the model underestimated the frequency of smaller deposits and overestimated the frequency of larger deposits in all disorders. A 'power-law' model fitted the size distributions of the primitive deposits in AD, DS, and DLB, and the diffuse deposits in AD. The data suggest: (1) similarities in size distributions of Aß deposits among disorders, (2) growth of deposits varies with subtype and disorder, (3) different factors are involved in the growth of the diffuse/primitive and classic deposits, and (4) log-normal and power-law models do not completely account for the size frequency distributions.

Breakage model development and application with CFD for predicting breakage of whey protein precipitate particles

Particle breakage due to fluid flow through various geometries can have a major influence on the performance of particle/fluid processes and on the product quality characteristics of particle/fluid products. In this study, whey protein precipitate dispersions were used as a case study to investigate the effect of flow intensity and exposure time on the breakage of these precipitate particles. Computational fluid dynamic (CFD) simulations were performed to evaluate the turbulent eddy dissipation rate (TED) and associated exposure time along various flow geometries. The focus of this work is on the predictive modelling of particle breakage in particle/fluid systems. A number of breakage models were developed to relate TED and exposure time to particle breakage. The suitability of these breakage models was evaluated for their ability to predict the experimentally determined breakage of the whey protein precipitate particles. A "power-law threshold" breakage model was found to provide a satisfactory capability for predicting the breakage of the whey protein precipitate particles. The whey protein precipitate dispersions were propelled through a number of different geometries such as bends, tees and elbows, and the model accurately predicted the mean particle size attained after flow through these geometries. © 2005 Elsevier Ltd. All rights reserved.

Fluctuation-driven traffic congestion in a scale-free model of the Internet

In studies of complex heterogeneous networks, particularly of the Internet, significant attention was paid to analysing network failures caused by hardware faults or overload. There network reaction was modelled as rerouting of traffic away from failed or congested elements. Here we model network reaction to congestion on much shorter time scales when the input traffic rate through congested routes is reduced. As an example we consider the Internet where local mismatch between demand and capacity results in traffic losses. We describe the onset of congestion as a phase transition characterised by strong, albeit relatively short-lived, fluctuations of losses caused by noise in input traffic and exacerbated by the heterogeneous nature of the network manifested in a power-law load distribution. The fluctuations may result in the network strongly overreacting to the first signs of congestion by significantly reducing input traffic along the communication paths where congestion is utterly negligible. © 2013 IEEE.

Modelling the growth of prion protein aggregates in the brain in variant Creutzfeldt-Jakob disease

Deposition of insoluble prion protein (PrP) in the brain in the form of protein aggregates or deposits is characteristic of the ‘transmissible spongiform encephalopathies’ (TSEs). Understanding the growth and development of these PrP aggregates is important both in attempting to the elucidate of the pathogenesis of prion disease and in the development of treatments designed to prevent or inhibit the spread of prion pathology within the brain. Aggregation and disaggregation of proteins and the diffusion of substances into the developing aggregates (surface diffusion) are important factors in the development of protein aggregates. Mathematical models suggest that if aggregation/disaggregation or surface diffusion is the predominant factor, the size frequency distribution of the resulting protein aggregates in the brain should be described by either a power-law or a log-normal model respectively. This study tested this hypothesis for two different types of PrP deposit, viz., the diffuse and florid-type PrP deposits in patients with variant Creutzfeldt-Jakob disease (vCJD). The size distributions of the florid and diffuse plaques were fitted by a power-law function in 100% and 42% of brain areas studied respectively. By contrast, the size distributions of both types of plaque deviated significantly from a log-normal model in all brain areas. Hence, protein aggregation and disaggregation may be the predominant factor in the development of the florid plaques. A more complex combination of factors appears to be involved in the pathogenesis of the diffuse plaques. These results may be useful in the design of treatments to inhibit the development of protein aggregates in vCJD.

Modelling growth of prion protein aggregates in the brain in variant Creutzfeldt-Jakob disease

Deposition of insoluble prion protein (PrP) in the brain in the form of protein aggregates or deposits is characteristic of the ‘transmissible spongiform encephalopathies’ (TSEs). Understanding the growth and development of PrP aggregates is important both in attempting to elucidate the pathogenesis of prion disease and in the development of treatments designed to inhibit the spread of prion pathology within the brain. Aggregation and disaggregation of proteins and the diffusion of substances into the developing aggregates (surface diffusion) are important factors in the development of protein deposits. Mathematical models suggest that if either aggregation/disaggregation or surface diffusion is the predominant factor, then the size frequency distribution of the resulting protein aggregates will be described by either a power-law or a log-normal model respectively. This study tested this hypothesis for two different populations of PrP deposit, viz., the diffuse and florid-type PrP deposits characteristic of patients with variant Creutzfeldt-Jakob disease (vCJD). The size distributions of the florid and diffuse deposits were fitted by a power-law function in 100% and 42% of brain areas studied respectively. By contrast, the size distributions of both types of aggregate deviated significantly from a log-normal model in all areas. Hence, protein aggregation and disaggregation may be the predominant factor in the development of the florid deposits. A more complex combination of factors appears to be involved in the pathogenesis of the diffuse deposits. These results may be useful in the design of treatments to inhibit the development of PrP aggregates in vCJD.

Damage analysis of bridge structures using vibrational techniques

Much research is currently centred on the detection of damage in structures using vibrational data. The work presented here examined several areas of interest in support of a practical technique for identifying and locating damage within bridge structures using apparent changes in their vibrational response to known excitation. The proposed goals of such a technique included the need for the measurement system to be operated on site by a minimum number of staff and that the procedure should be as non-invasive to the bridge traffic-flow as possible. Initially the research investigated changes in the vibrational bending characteristics of two series of large-scale model bridge-beams in the laboratory and these included ordinary-reinforced and post-tensioned, prestressed designs. Each beam was progressively damaged at predetermined positions and its vibrational response to impact excitation was analysed. For the load-regime utilised the results suggested that the infuced damage manifested itself as a function of the span of a beam rather than a localised area. A power-law relating apparent damage with the applied loading and prestress levels was then proposed, together with a qualitative vibrational measure of structural damage. In parallel with the laboratory experiments a series of tests were undertaken at the sites of a number of highway bridges. The bridges selected had differing types of construction and geometric design including composite-concrete, concrete slab-and-beam, concrete-slab with supporting steel-troughing constructions together with regular-rectangular, skewed and heavily-skewed geometries. Initial investigations were made of the feasibility and reliability of various methods of structure excitation including traffic and impulse methods. It was found that localised impact using a sledge-hammer was ideal for the purposes of this work and that a cartridge `bolt-gun' could be used in some specific cases.

Temporal correlations of local network losses

We introduce a continuum model describing data losses in a single node of a packet-switched network (like the Internet) which preserves the discrete nature of the data loss process. By construction, the model has critical behavior with a sharp transition from exponentially small to finite losses with increasing data arrival rate. We show that such a model exhibits strong fluctuations in the loss rate at the critical point and non-Markovian power-law correlations in time, in spite of the Markovian character of the data arrival process. The continuum model allows for rather general incoming data packet distributions and can be naturally generalized to consider the buffer server idleness statistics.

Income and poverty in a developing economy

We present a stochastic agent-based model for the distribution of personal incomes in a developing economy. We start with the assumption that incomes are determined both by individual labour and by stochastic effects of trading and investment. The income from personal effort alone is distributed about a mean, while the income from trade, which may be positive or negative, is proportional to the trader's income. These assumptions lead to a Langevin model with multiplicative noise, from which we derive a Fokker-Planck (FP) equation for the income probability density function (IPDF) and its variation in time. We find that high earners have a power law income distribution while the low-income groups have a Levy IPDF. Comparing our analysis with the Indian survey data (obtained from the world bank website: http://go.worldbank.org/SWGZB45DN0) taken over many years we obtain a near-perfect data collapse onto our model's equilibrium IPDF. Using survey data to relate the IPDF to actual food consumption we define a poverty index (Sen A. K., Econometrica., 44 (1976) 219; Kakwani N. C., Econometrica, 48 (1980) 437), which is consistent with traditional indices, but independent of an arbitrarily chosen "poverty line" and therefore less susceptible to manipulation. Copyright © EPLA, 2010.

Random walks in local dynamics of network losses

We suggest a model for data losses in a single node (memory buffer) of a packet-switched network (like the Internet) which reduces to one-dimensional discrete random walks with unusual boundary conditions. By construction, the model has critical behavior with a sharp transition from exponentially small to finite losses with increasing data arrival rate. We show that for a finite-capacity buffer at the critical point the loss rate exhibits strong fluctuations and non-Markovian power-law correlations in time, in spite of the Markovian character of the data arrival process.

Contact time periods in immunological synapse

This paper resolves the long standing debate as to the proper time scale τ of the onset of the immunological synapse bond, the noncovalent chemical bond defining the immune pathways involving T cells and antigen presenting cells. Results from our model calculations show τ to be of the order of seconds instead of minutes. Close to the linearly stable regime, we show that in between the two critical spatial thresholds defined by the integrin:ligand pair (Δ2∼ 40-45 nm) and the T-cell receptor TCR:peptide-major-histocompatibility-complex pMHC bond (Δ1∼ 14-15 nm), τ grows monotonically with increasing coreceptor bond length separation δ (= Δ2-Δ1∼ 26-30 nm) while τ decays with Δ1 for fixed Δ2. The nonuniversal δ-dependent power-law structure of the probability density function further explains why only the TCR:pMHC bond is a likely candidate to form a stable synapse.

Modeling of the spectrum in a random distributed feedback fiber laser within the power balance modes

The simplest model for a description of the random distributed feedback (RDFB) Raman fiber laser is a power balance model describing the evolution of the intensities of the waves over the fiber length. The model predicts well the power performances of the RDFB fiber laser including the generation threshold, the output power and pump and generation wave intensity distributions along the fiber. In the present work, we extend the power balance model and modify equations in such a way that they describe now frequency dependent spectral power density instead of integral over the spectrum intensities. We calculate the generation spectrum by using the depleted pump wave longitudinal distribution derived from the conventional power balance model. We found the spectral balance model to be sufficient to account for the spectral narrowing in the RDFB laser above the threshold of the generation. © 2014 SPIE.

Grid-texture mechanisms in human vision:contrast detection of regular sparse micro-patterns requires specialist templates

Previous work has shown that human vision performs spatial integration of luminance contrast energy, where signals are squared and summed (with internal noise) over area at detection threshold. We tested that model here in an experiment using arrays of micro-pattern textures that varied in overall stimulus area and sparseness of their target elements, where the contrast of each element was normalised for sensitivity across the visual field. We found a power-law improvement in performance with stimulus area, and a decrease in sensitivity with sparseness. While the contrast integrator model performed well when target elements constituted 50–100% of the target area (replicating previous results), observers outperformed the model when texture elements were sparser than this. This result required the inclusion of further templates in our model, selective for grids of various regular texture densities. By assuming a MAX operation across these noisy mechanisms the model also accounted for the increase in the slope of the psychometric function that occurred as texture density decreased. Thus, for the first time, mechanisms that are selective for texture density have been revealed at contrast detection threshold. We suggest that these mechanisms have a role to play in the perception of visual textures.