Approaching the non-linear Shannon limit

We review the recent progress of information theory in optical communications, and describe the current experimental results and associated advances in various individual technologies which increase the information capacity. We confirm the widely held belief that the reported capacities are approaching the fundamental limits imposed by signal-to-noise ratio and the distributed non-linearity of conventional optical fibres, resulting in the reduction in the growth rate of communication capacity. We also discuss the techniques which are promising to increase and/or approach the information capacity limit.

Caputo Derivatives in Viscoelasticity: A Non-Linear Finite-Deformation Theory for Tissue

Mathematics Subject Classification: 26A33, 74B20, 74D10, 74L15

Análise da força propulsora do motor de indução linear alimentado com imposição de corrente

This work intent to study the motive power provided by the plane linear induction motor, in a lock condition. It uses a method of imposition of the electric current to the stator via a frequency convertor PWM driven by a refed platform. The reading of the motive power was performed by a load cell using an electronic circuit for reading and conditioning of the signal. Aiming a complete analysis of the linear motor, it was performed a computational modeling that employs all relevant parameters to the study of the locked machine. At the end it was held a theoric-experimental confrontation that evaluated the effectiveness of the proposed method.

Simultaneous observation of current oscillations and porous film growth during anodization of InP

The observation of spontaneous oscillations in current during the anodization of InP in relatively high concentrations of KOH electrolytes is reported. Oscillations were observed under potential sweep and constant potential conditions. Well-defined oscillations are observed during linear potential sweeps of InP in 5 mol dm-3 KOH to potentials above ∼1.7 V (SCE) at scan rates in the range of 50 to 500 mV s-1. The oscillations observed exhibit an asymmetrical current versus potential profile, and the charge per cycle was found to increase linearly with potential. More complex oscillatory behavior was observed under constant potential conditions. Periodic damped oscillations are observed in high concentrations of electrolyte whereas undamped sinusoidal oscillations are observed in relatively lower concentrations. In both cases, the anodization of InP results in porous InP formation, and the current in the oscillatory region corresponds to the cyclical effective area changes due to pitting dissolution of the InP surface with the coincidental growth of a thick porous In2O3 film.

Relationships Between Current and Past Binge Drinking and Systolic Blood Pressure in Young Adults.

PURPOSE: Heavy episodic (i.e., "binge") drinking (i.e., ≥five drinks/occasion) is highly prevalent among young adults; those who binge do so four times per month on average, consuming nine drinks on average on each occasion. Although it is well established that chronic heavy drinking (≥two alcoholic beverages per day) increases the risk of hypertension, the relationship between binge drinking and blood pressure is not well described. Our aim was to describe the relationship between frequency of binge drinking, both current (at age 24 years) and past (at age 20 years), and systolic blood pressure (SBP) at age 24 years. METHODS: Participants (n = 756) from the longitudinal Nicotine Dependence in Teens study reported alcohol consumption at ages 20 and 24 years and had SBP measured at age 24 years. We examined the association between binge drinking and SBP using multiple linear regression, controlling for sex, race/ethnicity, education, monthly drinking in high school, cigarette smoking, and body mass index. RESULTS: Compared to nonbinge drinkers, SBP at age 24 years was 2.61 [.41, 4.82] mm Hg higher among current monthly bingers and 4.03 [1.35, 6.70] mm Hg higher among current weekly bingers. SBP at age 24 years was 2.90 [.54, 5.25] mm Hg higher among monthly bingers at age 20 years and 3.64 [.93, 6.35] mm Hg higher among weekly bingers at age 20 years, compared to nonbinge drinkers. CONCLUSIONS: Frequent binge drinking at ages 20 and 24 years is associated with higher SBP at age 24 years and may be implicated in the development of hypertension.

(Table S1) Age determination ofs ediment cores of the Azores Current System

In order to test the sensitivity of marine primary productivity in the midlatitude open ocean North Atlantic to changes in the Atlantic Meridional Overturning Circulation (AMOC), we investigated two spliced sediment cores from a site south of the Azores Islands at the northern rim of the North Atlantic subtropical gyre. For this purpose we analyzed coccolithophore assemblages, diatom abundances, alkenones and conducted X-ray fluorescence (XRF) core scanning. During times of reduced AMOC, especially during Heinrich event 1 (H1) and the Younger Dryas, we observe a strong increase in productivity as evidenced by high coccolith accumulation rates, high alkenone concentrations/accumulation rates, high Ba/Ti-ratios, high abundances of diatoms and low abundances ofF. profunda. The increased productivity is partly caused by a more southern position of the Azores Front (AzF), and hence by a less northward extension of the subtropical gyre, as deduced from high abundances of the temperate coccolithophore species G. muellerae and low abundances of subtropical species (Oolithotus spp., Umbellosphaera spp., Umbilicosphaeraspp.). However, to explain the full range of the observed productivity increase, other factors like increased westerly winds and advection of nutrient-rich surface waters have also to be considered. Because this pattern can also be observed in other sediment cores from the midlatitude North Atlantic, we propose that during times of reduced AMOC there has been a band of strongly increased productivity across the North Atlantic at the northern rim of the contracted subtropical gyre, which partly counteracts the decreased organic carbon pump in the high northern latitudes.

Hierarchical Reconstruction Method for Solving Ill-posed Linear Inverse Problems

We present a detailed analysis of the application of a multi-scale Hierarchical Reconstruction method for solving a family of ill-posed linear inverse problems. When the observations on the unknown quantity of interest and the observation operators are known, these inverse problems are concerned with the recovery of the unknown from its observations. Although the observation operators we consider are linear, they are inevitably ill-posed in various ways. We recall in this context the classical Tikhonov regularization method with a stabilizing function which targets the specific ill-posedness from the observation operators and preserves desired features of the unknown. Having studied the mechanism of the Tikhonov regularization, we propose a multi-scale generalization to the Tikhonov regularization method, so-called the Hierarchical Reconstruction (HR) method. First introduction of the HR method can be traced back to the Hierarchical Decomposition method in Image Processing. The HR method successively extracts information from the previous hierarchical residual to the current hierarchical term at a finer hierarchical scale. As the sum of all the hierarchical terms, the hierarchical sum from the HR method provides an reasonable approximate solution to the unknown, when the observation matrix satisfies certain conditions with specific stabilizing functions. When compared to the Tikhonov regularization method on solving the same inverse problems, the HR method is shown to be able to decrease the total number of iterations, reduce the approximation error, and offer self control of the approximation distance between the hierarchical sum and the unknown, thanks to using a ladder of finitely many hierarchical scales. We report numerical experiments supporting our claims on these advantages the HR method has over the Tikhonov regularization method.

Quantitative measurement using scanning thermal microscopy

This thesis reports on the development of quantitative measurement using micromachined scanning thermal microscopy (SThM) probes. These thermal probes employ a resistive element at their end, which can be used in passive or active modes. With the help of a review of SThM, the current issues and potentials associated with this technique are revealed. As a consequence of this understanding, several experimental and theoretical methods are discussed, which expand our understanding of these probes. The whole thesis can be summarized into three parts, one focusing on the thermal probe, one on probe-sample thermal interactions, and the third on heat transfer within the sample. In the first part, a series of experiments are demonstrated, aimed at characterizing the probe in its electrical and thermal properties, benefiting advanced probe design, and laying a fundamental base for quantifying the temperature of the probe. The second part focuses on two artifacts observed during the thermal scans – one induced by topography and the other by air conduction. Correspondingly, two devices, probing these artifacts, are developed. A topography-free sample, utilizing a pattern transfer technique, minimises topography-related artifacts that limited the reliability of SThM data; a controlled temperature ‘Johnson noise device’, with multiple-heater design, offers a uniform, accurate, temperature distribution. Analyzing results of scan from these samples provides data for studying the thermal interactions within the probe and the tip-sample interface. In the final part, the observation is presented that quantification of measurements depends not only on an accurate measurement tool, but also on a deep understanding of the heat transfer within the sample resulting from the nanoscopic contact. It is believed that work in this thesis contributes to SThM gaining wider application in the scientific community.

Investigating the use of LiDAR scanning as a method for the measurement of timber distortion features

Measuring the extent to which a piece of structural timber has distorted at a macroscopic scale is fundamental to assessing its viability as a structural component. From the sawmill to the construction site, as structural timber dries, distortion can render it unsuitable for its intended purposes. This rejection of unusable timber is a considerable source of waste to the timber industry and the wider construction sector. As such, ensuring accurate measurement of distortion is a key step in addressing ineffciencies within timber processing. Currently, the FRITS frame method is the established approach used to gain an understanding of timber surface profile. The method, while reliable, is dependent upon relatively few measurements taken across a limited area of the overall surface, with a great deal of interpolation required. Further, the process is unavoidably slow and cumbersome, the immobile scanning equipment limiting where and when measurements can be taken and constricting the process as a whole. This thesis seeks to introduce LiDAR scanning as a new, alternative approach to distortion feature measurement. In its infancy as a measurement technique within timber research, the practicalities of using LiDAR scanning as a measurement method are herein demonstrated, exploiting many of the advantages the technology has over current approaches. LiDAR scanning creates a much more comprehensive image of a timber surface, generating input data multiple magnitudes larger than that of the FRITS frame. Set-up and scanning time for LiDAR is also much quicker and more flexible than existing methods. With LiDAR scanning the measurement process is freed from many of the constraints of the FRITS frame and can be done in almost any environment. For this thesis, surface scans were carried out on seven Sitka spruce samples of dimensions 48.5x102x3000mm using both the FRITS frame and LiDAR scanner. The samples used presented marked levels of distortion and were relatively free from knots. A computational measurement model was created to extract feature measurements from the raw LiDAR data, enabling an assessment of each piece of timber to be carried out in accordance with existing standards. Assessment of distortion features focused primarily on the measurement of twist due to its strong prevalence in spruce and the considerable concern it generates within the construction industry. Additional measurements of surface inclination and bow were also made with each method to further establish LiDAR's credentials as a viable alternative. Overall, feature measurements as generated by the new LiDAR method compared well with those of the established FRITS method. From these investigations recommendations were made to address inadequacies within existing measurement standards, namely their reliance on generalised and interpretative descriptions of distortion. The potential for further uses of LiDAR scanning within timber researches was also discussed.

Al-based anodic oxide films structure observation using field emission gun scanning electron microscopy

In the present work, the anodic oxide films of Al, Al-Cu 4.5% and Al-Si 6.5% alloys are formed using direct and pulse current. In the case of Al-Cu and Al-Si alloys, the electrolyte used contains sulfuric acid and oxalic acid, meanwhile for Al the electrolyte contains sulfuric acid only. Al-Cu alloy was submitted to a heat treatment in order to decrease the effect of inter metallic phase theta upon the anodic film structure. Fractured samples were observed using a field emission gun scanning electron microscope JSM-6330F at (LME)/Brazilian Synchrotron Light Laboratory (LNLS), Campinas, SP, Brazil. The oxide film images enable evaluation of the pore size and form with a resolution similar to the transmission electron microscope (TEM) resolution. It is also observed that the anodizing process using pulse current produces an irregular structure of pore walls, and by direct cur-rent it is produced a rectilinear pore wall. (c) 2005 Elsevier B.V. All rights reserved.

Neuronal networks with gap junctions: A study of piece-wise linear planar neuron models

The presence of gap junction coupling among neurons of the central nervous systems has been appreciated for some time now. In recent years there has been an upsurge of interest from the mathematical community in understanding the contribution of these direct electrical connections between cells to large-scale brain rhythms. Here we analyze a class of exactly soluble single neuron models, capable of producing realistic action potential shapes, that can be used as the basis for understanding dynamics at the network level. This work focuses on planar piece-wise linear models that can mimic the firing response of several different cell types. Under constant current injection the periodic response and phase response curve (PRC) is calculated in closed form. A simple formula for the stability of a periodic orbit is found using Floquet theory. From the calculated PRC and the periodic orbit a phase interaction function is constructed that allows the investigation of phase-locked network states using the theory of weakly coupled oscillators. For large networks with global gap junction connectivity we develop a theory of strong coupling instabilities of the homogeneous, synchronous and splay state. For a piece-wise linear caricature of the Morris-Lecar model, with oscillations arising from a homoclinic bifurcation, we show that large amplitude oscillations in the mean membrane potential are organized around such unstable orbits.

Perpectiva linear paramétrica

Tese de Doutoramento em Arquitetura, com a especialização em Comunicação Visual, apresentada na Faculdade de Arquitetura da Universidade de Lisboa, para obtenção do grau de Doutor.

An improved stability criterion for time-delay power systems with electric vehicles and high voltage direct current power links

This paper presents an improved stability criterion for load frequency control (LFC) of time-delay power systems including AC/HVDC transmission links and EVs. By employing a novel refined Jensen-based inequality, an improved stability condition is derived in terms of feasible linear matrix inequalities (LMIs) which allow us to compute the maximal upper bounds of time-delay ensuring stability of the LFC scheme equipped with an embedded controller. Cases studies here are implemented for LFC scheme of a two-area power system, which is interconnected by parallel (AC/HVDC) links, with embedded proportional integral (PI) controller for discharged EVs. The relationships between the parameters of PI controller, supplementary control of HVDC links and delay margins of the LFC scheme are also discussed. As a consequence of facts, the results of delay margins can be used as a guideline to tune PI controller and set-up parameters for HVDC control.

Effects of increasing neuromuscular electrical stimulation current intensity on cortical sensorimotor network activation: a time domain fNIRS study

Neuroimaging studies have shown neuromuscular electrical stimulation (NMES)-evoked movements activate regions of the cortical sensorimotor network, including the primary sensorimotor cortex (SMC), premotor cortex (PMC), supplementary motor area (SMA), and secondary somatosensory area (S2), as well as regions of the prefrontal cortex (PFC) known to be involved in pain processing. The aim of this study, on nine healthy subjects, was to compare the cortical network activation profile and pain ratings during NMES of the right forearm wrist extensor muscles at increasing current intensities up to and slightly over the individual maximal tolerated intensity (MTI), and with reference to voluntary (VOL) wrist extension movements. By exploiting the capability of the multi-channel time domain functional near-infrared spectroscopy technique to relate depth information to the photon time-of-flight, the cortical and superficial oxygenated (O2Hb) and deoxygenated (HHb) hemoglobin concentrations were estimated. The O2Hb and HHb maps obtained using the General Linear Model (NIRS-SPM) analysis method, showed that the VOL and NMES-evoked movements significantly increased activation (i.e., increase in O2Hb and corresponding decrease in HHb) in the cortical layer of the contralateral sensorimotor network (SMC, PMC/SMA, and S2). However, the level and area of contralateral sensorimotor network (including PFC) activation was significantly greater for NMES than VOL. Furthermore, there was greater bilateral sensorimotor network activation with the high NMES current intensities which corresponded with increased pain ratings. In conclusion, our findings suggest that greater bilateral sensorimotor network activation profile with high NMES current intensities could be in part attributable to increased attentional/pain processing and to increased bilateral sensorimotor integration in these cortical regions.

A fast malware feature selection approach using a hybrid of multi-linear and stepwise binary logistic regression

Malware replicates itself and produces offspring with the same characteristics but different signatures by using code obfuscation techniques. Current generation anti-virus engines employ a signature-template type detection approach where malware can easily evade existing signatures in the database. This reduces the capability of current anti-virus engines in detecting malware. In this paper, we propose a stepwise binary logistic regression-based dimensionality reduction techniques for malware detection using application program interface (API) call statistics. Finding the most significant malware feature using traditional wrapper-based approaches takes an exponential complexity of the dimension (m) of the dataset with a brute-force search strategies and order of (m-1) complexity with a backward elimination filter heuristics. The novelty of the proposed approach is that it finds the worst case computational complexity which is less than order of (m-1). The proposed approach uses multi-linear regression and the p-value of each individual API feature for selection of the most uncorrelated and significant features in order to reduce the dimensionality of the large malware data and to ensure the absence of multi-collinearity. The stepwise logistic regression approach is then employed to test the significance of the individual malware feature based on their corresponding Wald statistic and to construct the binary decision the model. When the selected most significant APIs are used in a decision rule generation systems, this approach not only reduces the tree size but also improves classification performance. Exhaustive experiments on a large malware data set show that the proposed approach clearly exceeds the existing standard decision rule, support vector machine-based template approach with complete data and provides a better statistical fitness.