Clustering and periodicity of neurofibrillary tangles in the upper and lower cortical laminae in Alzheimer's disease

In Alzheimer's disease (AD), neurofibrillary tangles (NFT) occur within neurons in both the upper and lower cortical laminae. Using a statistical method that estimates the size and spacing of NFT clusters along the cortex parallel to the pia mater, two hypotheses were tested: 1) that the cluster size and distribution of the NFT in gyri of the temporal lobe reflect degeneration of the feedforward (FF) and feedback (FB) cortico-cortical pathways, and 2) that there is a spatial relationship between the clusters of NFT in the upper and lower laminae. In 16 temporal lobe gyri from 10 cases of sporadic AD, NFT were present in both the upper and lower laminae in 11/16 (69%) gyri and in either the upper or lower laminae in 5/16 (31%) gyri. Clustering of the NFT was observed in all gyri. A significant peak-to-peak distance was observed in the upper laminae in 13/15 (87%) gyri and in the lower laminae in 8/ 12 (67%) gyri, suggesting a regularly repeating pattern of NFT clusters along the cortex. The regularly distributed clusters of NFT were between 500 and 800 μm in size, the estimated size of the cells of origin of the FF and FB cortico-cortical projections, in the upper laminae of 6/13 (46%) gyri and in the lower laminae of 2/8 (25%) gyri. Clusters of NFT in the upper laminae were spatially correlated (in phase) with those in the lower laminae in 5/16 (31%) gyri. The clustering patterns of the NFT are consistent with their formation in relation to the FF and FB cortico-cortical pathways. In most gyri, NFT clusters appeared to develop independently in the upper and lower laminae.

Fluctuation-induced traffic congestion in heterogeneous networks

In studies of complex heterogeneous networks, particularly of the Internet, significant attention was paid to analyzing network failures caused by hardware faults or overload, where the network reaction was modeled as rerouting of traffic away from failed or congested elements. Here we model another type of the network reaction to congestion - a sharp reduction of the input traffic rate through congested routes which occurs on much shorter time scales. We consider the onset of congestion in the Internet where local mismatch between demand and capacity results in traffic losses and show that it can be described as a phase transition characterized by strong non-Gaussian loss fluctuations at a mesoscopic time scale. The fluctuations, caused by noise in input traffic, are exacerbated by the heterogeneous nature of the network manifested in a scale-free load distribution. They 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. © Copyright EPLA, 2012.

Stochasticity, periodicity and localized light structures in partially mode-locked fibre lasers

Physical systems with co-existence and interplay of processes featuring distinct spatio-temporal scales are found in various research areas ranging from studies of brain activity to astrophysics. The complexity of such systems makes their theoretical and experimental analysis technically and conceptually challenging. Here, we discovered that while radiation of partially mode-locked fibre lasers is stochastic and intermittent on a short time scale, it exhibits non-trivial periodicity and long-scale correlations over slow evolution from one round-trip to another. A new technique for evolution mapping of intensity autocorrelation function has enabled us to reveal a variety of localized spatio-temporal structures and to experimentally study their symbiotic co-existence with stochastic radiation. Real-time characterization of dynamical spatio-temporal regimes of laser operation is set to bring new insights into rich underlying nonlinear physics of practical active- and passive-cavity photonic systems.

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.

Off-equilibrium fluctuation-dissipation relations in the 3d Ising spin glass in a magnetic field

We study the fluctuation-dissipation relations for a three dimensional Ising spin glass in a magnetic field both in the high temperature phase as well as in the low temperature one. In the region of times simulated we have found that our results support a picture of the low temperature phase with broken replica symmetry, but a droplet behavior cannot be completely excluded.

Ground and Electronic Excited States from Pairing Matrix Fluctuation and Particle-Particle Random Phase Approximation

The accurate description of ground and electronic excited states is an important and challenging topic in quantum chemistry. The pairing matrix fluctuation, as a counterpart of the density fluctuation, is applied to this topic. From the pairing matrix fluctuation, the exact electron correlation energy as well as two electron addition/removal energies can be extracted. Therefore, both ground state and excited states energies can be obtained and they are in principle exact with a complete knowledge of the pairing matrix fluctuation. In practice, considering the exact pairing matrix fluctuation is unknown, we adopt its simple approximation --- the particle-particle random phase approximation (pp-RPA) --- for ground and excited states calculations. The algorithms for accelerating the pp-RPA calculation, including spin separation, spin adaptation, as well as an iterative Davidson method, are developed. For ground states correlation descriptions, the results obtained from pp-RPA are usually comparable to and can be more accurate than those from traditional particle-hole random phase approximation (ph-RPA). For excited states, the pp-RPA is able to describe double, Rydberg, and charge transfer excitations, which are challenging for conventional time-dependent density functional theory (TDDFT). Although the pp-RPA intrinsically cannot describe those excitations excited from the orbitals below the highest occupied molecular orbital (HOMO), its performances on those single excitations that can be captured are comparable to TDDFT. The pp-RPA for excitation calculation is further applied to challenging diradical problems and is used to unveil the nature of the ground and electronic excited states of higher acenes. The pp-RPA and the corresponding Tamm-Dancoff approximation (pp-TDA) are also applied to conical intersections, an important concept in nonadiabatic dynamics. Their good description of the double-cone feature of conical intersections is in sharp contrast to the failure of TDDFT. All in all, the pairing matrix fluctuation opens up new channel of thinking for quantum chemistry, and the pp-RPA is a promising method in describing ground and electronic excited states.

Does estrogen fluctuation throughout the menstrual cycle impact flow-mediated dilation during exercise in healthy premenopausal women?

The endothelium is the inner most layer of cells that lines all arteries. A primary function of endothelial cells is to regulate responses to increased blood flow and the resulting frictional forces or shear stress by producing factors such as nitric oxide that mediate arterial dilation (flow mediated dilation (FMD)). Menstrual cycle variations in estrogen (E2) have been shown to influence brachial artery (BA) FMD in response to transient increases in shear stress brought about by the release of a brief forearm occlusion (reactive hyperemia (RH)). FMD can also be assessed in response to a sustained shear stress stimulus such as that created with handgrip exercise (HGEX), and studies have shown that RH- and HGEX stimulated FMD provide unique information regarding endothelial function. However, the impact of menstrual phase on HGEX-FMD is unknown. Therefore, the purpose of this study was to determine the impact of cyclical changes in E2 levels on HGEX-FMD over two discrete phases of the menstrual cycle. FMD was assessed via ultrasound. 12 subjects (21 ± 2yrs) completed two experimental visits: (1) low estrogen phase (early follicular) and (2) High estrogen phase (late follicular). In each visit both RH- and HGEX-FMD (6 min handgrip exercise) were assessed. Results are mean ± SD. E2 increased from the low to the high estrogen phase of the menstrual cycle (low: 34 ± 8, high: 161 ± 113pg/mL, p = 0.004). There was no change in mean FMD between phases (RH-FMD: 7.7 ± 4.3% vs. 6.4 ± 3.1%, p = 0.139; HGEX-FMD: 4.8 ± 2.8% vs. 4.8 ± 2.3%, p = 0.979). The observation that both RH- and HGEX-FMD did not differ between phases indicates that menstrual cycle fluctuations in estrogen may not universally impact endothelial function in young, healthy premenopausal women. Further research is needed to improve our understanding of the mechanisms that underlie variability in the impact of menstrual phase on both transient and sustained FMD responses.

The proof of Kontsevich's periodicity conjecture on noncommutative birational transformations

For an arbitrary associative unital ring RR, let J1J1 and J2J2 be the following noncommutative, birational, partly defined involutions on the set M3(R)M3(R) of 3×33×3 matrices over RR: J1(M)=M−1J1(M)=M−1 (the usual matrix inverse) and J2(M)jk=(Mkj)−1J2(M)jk=(Mkj)−1 (the transpose of the Hadamard inverse).

We prove the surprising conjecture by Kontsevich that (J2∘J1)3(J2∘J1)3 is the identity map modulo the DiagL×DiagRDiagL×DiagR action (D1,D2)(M)=D−11MD2(D1,D2)(M)=D1−1MD2 of pairs of invertible diagonal matrices. That is, we show that, for each MM in the domain where (J2∘J1)3(J2∘J1)3 is defined, there are invertible diagonal 3×33×3 matrices D1=D1(M)D1=D1(M) and D2=D2(M)D2=D2(M) such that (J2∘J1)3(M)=D−11MD2(J2∘J1)3(M)=D1−1MD2.

Système de prédiction des pays vulnérables aux conséquences de la fluctuation de la production du maïs américain dû à un aléa climatique

Au travers de cette étude, nous proposons de mettre en place un système d’information géographique (SIG) prédictif afin d’obtenir le classement des pays vulnérables à la brusque variation des prix du maïs. L'élément déclencheur de cette variation sera un aléa climatique sur la zone de culture américaine, premier pays producteur. Afin d'analyser les conséquences d'une catastrophe naturelle, il fut nécessaire de construire un indice final de vulnérabilité par le regroupement de plusieurs thématiques (agricole, économique et socio politique). Les données des différentes thématiques ainsi que les résultats sont intégrés dans une base de données à référence spatiale pour permettre la restitution des résultats dans un SIG web.

Adipocyte size fluctuation, mechano-active lipid droplets and caveolae

International audience

Fluctuation and vertical distribution of a population of brown root stink bug Scaptocoris castanea (Hemiptera: Cydnidae) in the soil profile in Mato Grosso do Sul State, Brazil.

2016

Population fluctuation of Empoasca sp. (Hemiptera: cicadellidae) in a physic nut crop in Mato Grosso do Sul.

2016

AITPM Email Newsletter Volume 0907, July 2009 : President's Message

President’s Message AITPM President’s Message, July 2009 Hello fellow AITPM members, It’s now very early July so many Australians are going to experience a range of new, or increases in, fees, charges, and perhaps taxes by State and local governments. For example, Queenslanders are to be hit at the petrol pump, no longer living with the luxury of the State’s previous 8c per litre fuel subsidy, bringing general motorists’ fuel costs into line with the other States. A consolation is that they now don’t have to live with the real or perceived “price gouging” that has appeared in the past to make Queensland prices much closer than 8c to those in other States. Environmental lobbyists argue that this Government’s decision brings public transport costs closer to parity with private transport. However, my sense from sloppy petrol price elasticities is that the State’s motorists will get used to the reversal of what was a reverse tax pretty quickly, an amount which can be less than day-of-the week fluctuation. On the other hand, withholding this State revenue may help in some way the funding of the several major public transport infrastructure projects in progress; not to mention some of the cost of running the Transit Authority’s expanding service commitments. Other policy actions, such as a Federal Government review of taxation on employees’ package vehicles, which might discourage rather than encourage excess kilometres travelled, may have a greater environmental benefit. Of course, a downside is that many vehicles used so are Australian built, and discouraging fleet turnover may damage an industry which faces ever increasing uncertainty, and particularly at the present, is in need of some care and attention. I for one hope to this end that the new 4 cylinder (1.8L petrol or 2L diesel) so called “true Holden” Cruze and Toyota’s pending Camry Hybrid are both roaring successes, and will be taken up in droves as fleet and employee use vehicles. I’m not sure what drive-trains Ford and Holden plan to drop into their next full sized models but even if they’re not Australian sourced, let’s hope they coordinate the requisite performance expected by the “Aussie Battler” with suitable green credentials. I am also encouraged to see that already many Government fleet vehicles are smaller in size, but still fit for purpose. For instance, my local police station uses the Camry based Aurion as a district car. I close again in reminding everyone that AITPM’s flagship event, the 2009 AITPM National Conference, Traffic Beyond Tomorrow, is being held in Adelaide from 5 to 7 August. www.aitpm.com has all of the details about how to register, sponsor a booth, session, etc. Best regards all, Jon Bunker

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.

Power management and power flow control with back-to-back converters in a utility connected microgrid

This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.