RIEMANN ZETA ZEROS AND PRIME NUMBER SPECTRA IN QUANTUM FIELD THEORY

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Teorema de Riemann-Roch, morfismos de Frobenius e a hipótese de Riemann

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Conjectures and theorems in the theory of entire functions

Motivated by the recent solution of Karlin's conjecture, properties of functions in the Laguerre-Polya class are investigated. The main result of this paper establishes new moment inequalities fur a class of entire functions represented by Fourier transforms. The paper concludes with several conjectures and open problems involving the Laguerre-Polya class and the Riemann xi -function.

Higher order turän inequalities

The celebrated Turân inequalities P 2 n(x)-P n-x(x)P n+1(x) ≥ 0, x ε[-1,1], n ≥ 1, where P n(x) denotes the Legendre polynomial of degree n, are extended to inequalities for sums of products of four classical orthogonal polynomials. The proof is based on an extension of the inequalities γ 2 n - γ n-1γ n+1 ≥ 0, n ≥ 1, which hold for the Maclaurin coefficients of the real entire function ψ in the Laguerre-Pölya class, ψ(x) = ∑ ∞ n=0 γ nx n / n!. ©1998 American Mathematical Society.

On Li’s Coefficients for Some Classes of L-Functions

AMS Subj. Classification: 11M41, 11M26, 11S40

Class Number Two for Real Quadratic Fields of Richaud-Degert Type

2000 Mathematics Subject Classification: Primary: 11D09, 11A55, 11C08, 11R11, 11R29; Secondary: 11R65, 11S40; 11R09.

Riemann's Hypothesis

Riemann’s memoir is devoted to the function π(x) defined as the number of prime numbers less or equal to the real and positive number x. This is really the fact, but the “main role” in it is played by the already mentioned zeta-function.

Hermite Polynomials and the Zero-Distribution of Riemann's Zeta Function

AMS Subject Classification 2010: 11M26, 33C45, 42A38.

A multi-hypothesis topological SLAM approach for loop closing on edge-ordered graphs

We present a method for topological SLAM that specifically targets loop closing for edge-ordered graphs. Instead of using a heuristic approach to accept or reject loop closing, we propose a probabilistically grounded multi-hypothesis technique that relies on the incremental construction of a map/state hypothesis tree. Loop closing is introduced automatically within the tree expansion, and likely hypotheses are chosen based on their posterior probability after a sequence of sensor measurements. Careful pruning of the hypothesis tree keeps the growing number of hypotheses under control and a recursive formulation reduces storage and computational costs. Experiments are used to validate the approach.

Test of the enemy release hypothesis: the native magpie moth prefers a native fireweed (Senecio pinnatifolius) to its introduced congener (S.Madagascariensis)

Abstract The enemy release hypothesis predicts that native herbivores will either prefer or cause more damage to native than introduced plant species. We tested this using preference and performance experiments in the laboratory and surveys of leaf damage caused by the magpie moth Nyctemera amica on a co-occuring native and introduced species of fireweed (Senecio) in eastern Australia. In the laboratory, ovipositing females and feeding larvae preferred the native S. pinnatifolius over the introduced S. madagascariensis. Larvae performed equally well on foliage of S. pinnatifolius and S. madagascariensis: pupal weights did not differ between insects reared on the two species, but growth rates were significantly faster on S. pinnatifolius. In the field, foliage damage was significantly greater on native S. pinnatifolius than introduced S. madagascariensis. These results support the enemy release hypothesis, and suggest that the failure of native consumers to switch to introduced species contributes to their invasive success. Both plant species experienced reduced, rather than increased, levels of herbivory when growing in mixed populations, as opposed to pure stands in the field; thus, there was no evidence that apparent competition occurred.

Age-related maculopathy : linking aetiology and pathophysiological changes to the ischaemia hypothesis

Age-related maculopathy (ARM) has remained a challenging topic with respect to its aetiology, pathomechanisms, early detection and treatment since the late 19th century when it was first described as its own entity. ARM was previously considered an inflammatory disease, a degenerative disease, a tumor and as the result of choroidal hemodynamic disturbances and ischaemia. The latter processes have been repeatedly suggested to have a key role in its development and progression. In vivo experiments under hypoxic conditions could be models for the ischaemic deficits in ARM. Recent research has also linked ARM with gene polymorphisms. It is however unclear what triggers a person's gene susceptibility. In this manuscript, a linking hypothesis between aetiological factors including ischaemia and genetics and the development of early clinicopathological changes in ARM is proposed. New clinical psychophysical and electrophysiological tests are introduced that can detect ARM at an early stage. Models of early ARM based upon hemodynamic, photoreceptor and post-receptoral deficits are described and the mechanisms by which ischaemia may be involved as a final common pathway are considered. In neovascular age-related macular degeneration (neovascular AMD), ischaemia is thought to promote release of vascular endothelial growth factor (VEGF) which induces chorioretinal neovascularisation. VEGF is critical in the maintenance of the healthy choriocapillaris. In the final section of the manuscript the documentation of the effect of new anti-VEGF treatments on retinal function in neovascular AMD is critically viewed.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

The ultra-low friction of the articular surface is pH-dependent and is built on a hydrophobic underlay including a hypothesis on joint lubrication mechanism

In this study, the influence of pH on interfacial energy distributed over the phospholipids-bilayer surface model and the effect of hydrophobicity on coefficient of friction (f) were investigated by using microelectrophoresis. An important clinical implication of deficiency in hydrophobicity is the loss of phospholipids that is readily observed in osteoarthritis joints. This paper establishes the influence of pH on interfacial energy upon an increase f, which might be associated with a decrease of hydrophobicity of the articular surface.