Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Spatio-temporal dependencies in functional connectivity in rodent cortical cultures

Models of functional connectivity in cortical cultures on multi-electrodes arrays may aid in understanding how cognitive pathways form and improve techniques that aim to interface with neuronal systems. To enable research on such models, this study uses both data- and model-driven approaches to determine what dependencies are present in and between functional connectivity networks derived from bursts of extracellularly recorded activity. Properties of excitation in bursts were analysed using correlative techniques to assess the degree of linear dependence and then two parallel techniques were used to assess functional connectivity. Three models presenting increasing levels of spatio-temporal dependency were used to capture the dynamics of individual functional connections and their consistencies were verified using surrogate data. By comparing network-wide properties between model generated networks and functional networks from data, complex interdependencies were revealed. This indicates the persistent co-activation of neuronal pathways in spontaneous bursts, as can be found in whole brain structures.

'Quasi'-norm of an arithmetical convolution operator and the order of the Riemann zeta function

In this paper we study Dirichlet convolution with a given arithmetical function f as a linear mapping 'f that sends a sequence (an) to (bn) where bn = Pdjn f(d)an=d. We investigate when this is a bounded operator on l2 and ¯nd the operator norm. Of particular interest is the case f(n) = n¡® for its connection to the Riemann zeta function on the line 1, 'f is bounded with k'f k = ³(®). For the unbounded case, we show that 'f : M2 ! M2 where M2 is the subset of l2 of multiplicative sequences, for many f 2 M2. Consequently, we study the `quasi'-norm sup kak = T a 2M2 k'fak kak for large T, which measures the `size' of 'f on M2. For the f(n) = n¡® case, we show this quasi-norm has a striking resemblance to the conjectured maximal order of j³(® + iT )j for ® > 12 .

First order k-th moment finite element analysis of nonlinear operator equations with stochastic data

We develop and analyze a class of efficient Galerkin approximation methods for uncertainty quantification of nonlinear operator equations. The algorithms are based on sparse Galerkin discretizations of tensorized linearizations at nominal parameters. Specifically, we consider abstract, nonlinear, parametric operator equations J(\alpha ,u)=0 for random input \alpha (\omega ) with almost sure realizations in a neighborhood of a nominal input parameter \alpha _0. Under some structural assumptions on the parameter dependence, we prove existence and uniqueness of a random solution, u(\omega ) = S(\alpha (\omega )). We derive a multilinear, tensorized operator equation for the deterministic computation of k-th order statistical moments of the random solution's fluctuations u(\omega ) - S(\alpha _0). We introduce and analyse sparse tensor Galerkin discretization schemes for the efficient, deterministic computation of the k-th statistical moment equation. We prove a shift theorem for the k-point correlation equation in anisotropic smoothness scales and deduce that sparse tensor Galerkin discretizations of this equation converge in accuracy vs. complexity which equals, up to logarithmic terms, that of the Galerkin discretization of a single instance of the mean field problem. We illustrate the abstract theory for nonstationary diffusion problems in random domains.

Abnormal functional activation and maturation of fronto-striato-temporal and cerebellar regions during sustained attention in autism spectrum disorder

Objective Sustained attention problems are common in people with autism spectrum disorder (ASD) and may have significant implications for the diagnosis and management of ASD and associated comorbidities. Furthermore, ASD has been associated with atypical structural brain development. The authors used functional MRI to investigate the functional brain maturation of attention between childhood and adulthood in people with ASD. Method Using a parametrically modulated sustained attention/vigilance task, the authors examined brain activation and its linear correlation with age between childhood and adulthood in 46 healthy male adolescents and adults (ages 11–35 years) with ASD and 44 age- and IQ-matched typically developing comparison subjects. Results Relative to the comparison group, the ASD group had significantly poorer task performance and significantly lower activation in inferior prefrontal cortical, medial prefrontal cortical, striato-thalamic, and lateral cerebellar regions. A conjunction analysis of this analysis with group differences in brain-age correlations showed that the comparison group, but not the ASD group, had significantly progressively increased activation with age in these regions between childhood and adulthood, suggesting abnormal functional brain maturation in ASD. Several regions that showed both abnormal activation and functional maturation were associated with poorer task performance and clinical measures of ASD and inattention. Conclusions The results provide first evidence that abnormalities in sustained attention networks in individuals with ASD are associated with underlying abnormalities in the functional brain maturation of these networks between late childhood and adulthood.

Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.

Histological and functional renal alterations caused by Bothrops alternatus snake venom: Expression and activity of Na(+)/K(+)-ATPase

Background: Acute renal failure is a serious complication of human envenoming by Bothrops snakes. The ion pump Na(+)/K(+)-ATPase has an important role in renal tubule function, where it modulates sodium reabsorption and homeostasis of the extracellular compartment. Here, we investigated the morphological and functional renal alterations and changes in Na(+)/K(+)-ATPase expression and activity in rats injected with Bothrops alternatus snake venom. Methods: Male Wistar rats were injected with venom (0.8 mg/kg, iv.) and renal function was assessed 6.24, 48 and 72 h and 7 days post-venom. The rats were then killed and renal Na(+)/K(+)-ATPase activity was assayed based on phosphate release from ATP; gene and protein expressions were assessed by real time PCR and immunofluorescence microscopy, respectively. Results: Venom caused lobulation of the capillary tufts, dilation of Bowman`s capsular space. F-actin disruption in Bowman`s capsule and renal tubule brush border, and deposition of collagen around glomeruli and proximal tubules that persisted seven days after envenoming. Enhanced sodium and potassium excretion, reduced proximal sodium reabsorption, and proteinuria were observed 6 h post-venom, followed by a transient decrease in the glomerular filtration rate. Gene and protein expressions of the Na(+)/K(+)-ATPase alpha(1) subunit were increased 6 h post-venom, whereas Na(+)/K(+)-ATPase activity increased 6 h and 24 h post-venom. Conclusions: Bothrops alternatus venom caused marked morphological and functional renal alterations with enhanced Na(+)/K(+)-ATPase expression and activity in the early phase of renal damage. General significance: Enhanced Na(+)/K(+)-ATPase activity in the early hours after envenoming may attenuate the renal dysfunction associated with venom-induced damage. (C) 2011 Elsevier B.V. All rights reserved.

Functional Mn-Mg-k cation complexes in GaN featured by Raman spectroscopy

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

Controllability and stabilizability of linear time-varying distributed hereditary control systems

This paper is concerned with the controllability and stabilizability problem for control systems described by a time-varyinglinear abstract differential equation with distributed delay in the state variables. An approximate controllability propertyis established, and for periodic systems, the stabilization problem is studied. Assuming that the semigroup of operatorsassociated with the uncontrolled and non delayed equation is compact, and using the characterization of the asymptoticstability in terms of the spectrum of the monodromy operator of the uncontrolled system, it is shown that the approximatecontrollability property is a sufficient condition for the existence of a periodic feedback control law that stabilizes thesystem. The result is extended to include some systems which are asymptotically periodic. Copyright © 2014 John Wiley &Sons, Ltd.

Looking over Toxin-K+ Channel Interactions. Clues from the Structural and Functional Characterization of alpha-KTx Toxin Tc32, a Kv1.3 Channel Blocker

alpha-KTx toxin Tc32, from the Amazonian scorpion Tityus cambridgei, lacks the dyad motif; including Lys27, characteristic of the family and generally associated with channel blockage. The toxin has been cloned and expressed for the first time. Electrophysiological experiments, by showing that the recombinant form blocks Kv1.3 channels of olfactory bulb periglomerular cells like the natural Tc32 toxin, when tested on the Kv1.3 channel of human T lymphocytes, confirmed it is in an active fold. The nuclear magnetic resonance-derived structure revealed it exhibits an alpha/beta scaffold typical of the members of the alpha-KTx family. TdK2 and TdK3, all belonging to the same alpha-KTx 18 subfamily, share significant sequence identity with Tc32 but diverse selectivity and affinity for Kv1.3 and Kv1.1 channels. To gain insight into the structural features that may justify those differences, we used the recombinant Tc32 nuclear magnetic resonance-derived structure to model the other two toxins, for which no experimental structure is available. Their interaction with Kv1.3 and Kv1.1 has been investigated by means of docking simulations. The results suggest that differences in the electrostatic features of the toxins and channels, in their contact surfaces, and in their total dipole moment orientations govern the affinity and selectivity of toxins. In addition, we found that, regardless of whether the dyad motif is present, it is always a Lys side chain that physically blocks the channels, irrespective of its position in the toxin sequence.

Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Chemical transformations of the pyrene K-region for functional materials

In dieser Arbeit wurde eine neue Methode zur asymmetrischen Substitution der K-Regionen von Pyren entwickelt, auf welcher das Design und die Synthese von neuartigen, Pyren-basierten funktionalen Materialien beruht. Eine Vielzahl von Substitutionsmustern konnte erfolgreich realisiert werden um die Eigenschaften entsprechend dem Verwendungszweck anzupassen. Der polyzyklische aromatische Kohlenwasserstoff (PAK) Pyren setzt sich aus vier Benzolringen in Form einer planaren Raute mit zwei gegenüberliegenden K-Regionen zusammen. Der synthetische Schlüsselschritt dieser Arbeit ist die chemische Transformation der einen K-Region zu einem α-Diketon und der darauffolgenden selektiven Bromierung der zweiten K-Region. Dieser asymmetrisch funktionalisierte Baustein zeichnet sich durch zwei funktionelle Gruppen mit orthogonaler Reaktivität aus und erweitert dadurch das Arsenal der etablierten Pyren Chemie um eine vielseitig einsetzbare Methode. Aufbauend auf diesem synthetischen Zugang wurden fünf wesentliche Konzepte auf dem Weg zu neuen, von Pyren abgeleiteten Materialen verfolgt: (i) Asymmterische Substitution mit elektronenziehenden versus -schiebenden Gruppen. (ii) Darstellung von Pyrenocyaninen durch Anbindung von Pyren mit einer der K-Regionen an das Phthalocyanin Gerüst zur Ausdehnung des π-Systems. (iii) Einführung von Thiophen an die K-Region um halbleitende Eigenschaften zu erhalten. (iv) Symmetrische Annullierung von PAKs wie Benzodithiophen und Phenanthren an beide K Regionen für cove-reiche und dadurch nicht-planare Strukturen. (v) Verwendung des K-Region-funktionalisierten Pyrens als Synthesebaustein für das Peri-Pentacen. Neben der Synthese wurde die Selbstorganisation in der Festphase und an der flüssig/fest Grenzfläche mittels zweidimensionaler Weitwinkel-Röntgenstreuung (2D WAXS) bzw. Rastertunnelmikroskopie (STM) untersucht. Die halbleitenden Eigenschaften wurden in organischen Feld-Effekt Transistoren (OFETs) charakterisiert.

A linear O(N) model: a functional renormalization group approach for flat and curved space

In questa tesi sono state applicate le tecniche del gruppo di rinormalizzazione funzionale allo studio della teoria quantistica di campo scalare con simmetria O(N) sia in uno spaziotempo piatto (Euclideo) che nel caso di accoppiamento ad un campo gravitazionale nel paradigma dell'asymptotic safety. Nel primo capitolo vengono esposti in breve alcuni concetti basilari della teoria dei campi in uno spazio euclideo a dimensione arbitraria. Nel secondo capitolo si discute estensivamente il metodo di rinormalizzazione funzionale ideato da Wetterich e si fornisce un primo semplice esempio di applicazione, il modello scalare. Nel terzo capitolo è stato studiato in dettaglio il modello O(N) in uno spaziotempo piatto, ricavando analiticamente le equazioni di evoluzione delle quantità rilevanti del modello. Quindi ci si è specializzati sul caso N infinito. Nel quarto capitolo viene iniziata l'analisi delle equazioni di punto fisso nel limite N infinito, a partire dal caso di dimensione anomala nulla e rinormalizzazione della funzione d'onda costante (approssimazione LPA), già studiato in letteratura. Viene poi considerato il caso NLO nella derivative expansion. Nel quinto capitolo si è introdotto l'accoppiamento non minimale con un campo gravitazionale, la cui natura quantistica è considerata a livello di QFT secondo il paradigma di rinormalizzabilità dell'asymptotic safety. Per questo modello si sono ricavate le equazioni di punto fisso per le principali osservabili e se ne è studiato il comportamento per diversi valori di N.