Enzymatic phosphorylation of hair keratin enhances fast adsorption of cationic moieties

The current study describes the in vitro phosphorylation of a human hair keratin, using protein kinase for the first time. Phosphorylation of keratin was demonstrated by 31P NMR (Nuclear Magnetic Resonance) and Diffuse Reflectance Infrared Fourier Transform (DRIFT) techniques. Phosphorylation induced a 2.5 fold increase of adsorption capacity in the first 10 minutes for cationic moiety like Methylene Blue (MB). Thorough description of MB adsorption process was performed by several isothermal models. Reconstructed fluorescent microscopy images depict distinct amounts of dye bound to the differently treated hair. The results of this work suggest that the enzymatic phosphorylation of keratins might have significant implications in hair shampooing and conditioning, where short application times of cationic components are of prime importance.

Desenvolvimento e actualização do controlo de um equipamento de prototipagem rápida

Dissertação de mestrado integrado em Engenharia Mecânica

Comprehensive comparison of a current-source and a voltage-source converter for three-phase EV fast battery chargers

This paper presents a comprehensive comparison of a current-source converter and a voltage-source converter for three-phase electric vehicle (EV) fast battery chargers. Taking into account that the current-source converter (CSC) is a natural buck-type converter, the output voltage can assume a wide range of values, which varies between zero and the maximum instantaneous value of the power grid phase-to-phase voltage. On the other hand, taking into account that the voltage-source converter (VSC) is a natural boost-type converter, the output voltage is always greater than the maximum instantaneous value of the power grid phase-to-phase voltage, and consequently, it is necessary to use a dc-dc buck-type converter for applications as EV fast battery chargers. Along the paper is described in detail the principle of operation of both the CSC and the VSC for EV fast chargers, as well as the main equations of the power theory and current control strategies. The comparison between both converters is mainly established in terms of the total harmonic distortion of the grid current and the estimated efficiency for a range of operation between 10 kW and 50 kW.

Three-phase three-level current-source converter for EVs fast battery charging systems

This paper presents a three-phase three-level fast battery charger for electric vehicles (EVs) based in a current-source converter (CSC). Compared with the traditional voltage-source converters used for fast battery chargers, the CSC can be seen as a natural buck-type converter, i.e., the output voltage can assume a wide range of values, which varies between zero and the maximum instantaneous value of the power grid phase-to-phase voltage. Moreover, using the CSC it is not necessary to use a dc-dc back-end converter in the battery side, and it is also possible to control the grid current in order to obtain a sinusoidal waveform, and in phase with the power grid voltage (unitary power factor). Along the paper is described in detail the proposed CSC for EVs fast battery charging systems: the circuit topology, the power control theory, the current control strategy and the grid synchronization algorithm. Several simulation results of the EV fast battery charger operating with a maximum power of 50 kW are presented.

Genetic algorithms for the non emergency patients transport service

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the paper. The authors would like to thank Dr. Elaine DeBock for reviewing the manuscript.

Comparing standard and low-cost tools for gradient evaluation along potential cycling paths

Promoting the use of non-motorized modes of transport, such as cycling, is an important contribution to the improvement of mobility, accessibility and equity in cities. Cycling offers a fast and cheap transportation option for short distances, helping to lower pollutant emissions and contributing to a healthier way of life. In order to make the cycling mode more competitive in relation to motorized traffic, it is necessary to evaluate the potential of alternatives from the perspective of the physical effort. One way to do so consists of assessing the suitability of locations for implementing cycling infrastructures. In this work, four tools to determine the gradient along potential cycling paths are compared. Furthermore, an evaluation of the reliability of some low-cost tools to measure this parameter was conducted, by comparison with standard measurements using cartographic plans, on a field case study applied to the city of Braga, Portugal. These tools revealed a good level of accuracy for the planning stage, but proved to be less reliable for use in design.

Hand gesture recognition system based in computer vision and machine learning

"Lecture notes in computational vision and biomechanics series, ISSN 2212-9391, vol. 19"

Comparison of single and multi-objective evolutionary algorithms for robust link-state routing

Traffic Engineering (TE) approaches are increasingly impor- tant in network management to allow an optimized configuration and resource allocation. In link-state routing, the task of setting appropriate weights to the links is both an important and a challenging optimization task. A number of different approaches has been put forward towards this aim, including the successful use of Evolutionary Algorithms (EAs). In this context, this work addresses the evaluation of three distinct EAs, a single and two multi-objective EAs, in two tasks related to weight setting optimization towards optimal intra-domain routing, knowing the network topology and aggregated traffic demands and seeking to mini- mize network congestion. In both tasks, the optimization considers sce- narios where there is a dynamic alteration in the state of the system, in the first considering changes in the traffic demand matrices and in the latter considering the possibility of link failures. The methods will, thus, need to simultaneously optimize for both conditions, the normal and the altered one, following a preventive TE approach towards robust configurations. Since this can be formulated as a bi-objective function, the use of multi-objective EAs, such as SPEA2 and NSGA-II, came nat- urally, being those compared to a single-objective EA. The results show a remarkable behavior of NSGA-II in all proposed tasks scaling well for harder instances, and thus presenting itself as the most promising option for TE in these scenarios.

Localization in underground tunnels

Positioning technologies are becoming ubiquitous and are being used more and more frequently for supporting a large variety of applica- tions. For outdoor applications, global navigation satellite systems (GNSSs), such as the global positioning system (GPS), are the most common and popular choice because of their wide coverage. GPS is also augmented with network-based systems that exploit existing wireless and mobile networks for providing positioning functions where GPS is not available or to save energy in battery-powered devices. Indoors, GNSSs are not a viable solution, but many applications require very accurate, fast, and exible positioning, tracking, and navigation functions. These and other requirements have stim- ulated research activities, in both industry and academia, where a variety of fundamental principles, techniques, and sensors are being integrated to provide positioning functions to many applications. The large majority of positioning technologies is for indoor environments, and most of the existing commercial products have been developed for use in of ce buildings, airports, shopping malls, factory plants, and similar spaces. There are, however, other spaces where positioning, tracking, and navigation systems play a central role in safety and in rescue operations, as well as in supporting speci c activities or for scienti c research activities in other elds. Among those spaces are underground tunnels, mines, and even underwater wells and caves. This chapter describes the research efforts over the past few years that have been put into the development of positioning systems for underground tun- nels, with particular emphasis in the case of the Large Hadron Collider (LHC) at CERN (the European Organization for Nuclear Research), where localiza- tion aims at enabling more automatic and unmanned radiation surveys. Examples of positioning and localization systems that have been devel- oped in the past few years for underground facilities are presented in the fol- lowing section, together with a brief characterization of those spaces’ special conditions and the requirements of some of the most common applications. Section 5.2 provides a short overview of some of the most representative research efforts that are currently being carried out by many research teams around the world. In addition, some of the fundamental principles and tech- niques are identi ed, such as the use of leaky coaxial cables, as used at the LHC. In Section 5.3, we introduce the speci c environment of the LHC and de ne the positioning requirements for the envisaged application. This is followed by a detailed description of our approach and the results that have been achieved so far. Some last comments and remarks are presented in a nal section.

An immunity based configuration for multilayer single featured biometric authentication algorithms

Immune systems have been used in the last years to inspire approaches for several computational problems. This paper focus on behavioural biometric authentication algorithms’ accuracy enhancement by using them more than once and with different thresholds in order to first simulate the protection provided by the skin and then look for known outside entities, like lymphocytes do. The paper describes the principles that support the application of this approach to Keystroke Dynamics, an authentication biometric technology that decides on the legitimacy of a user based on his typing pattern captured on he enters the username and/or the password and, as a proof of concept, the accuracy levels of one keystroke dynamics algorithm when applied to five legitimate users of a system both in the traditional and in the immune inspired approaches are calculated and the obtained results are compared.

Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

Testing Nelder-Mead based repulsion algorithms for multiple roots of nonlinear systems via a two-level factorial design of experiments

This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

Corrigendum to “Short-term changes in light distortion in orthokeratology subjects"

Artigo completo publicado na revista "BioMed Research International, (2015), 1-7" e disponível no RepositóriUM em: http://hdl.handle.net/1822/33375

Short-term corneal changes with gas-permeable contact lens wear in keratoconus subjects: a comparison of two fitting approaches

Purpose: To evaluate changes in anterior corneal topography and higher-order aberrations (HOA) after 14-days of rigid gas-permeable (RGP) contact lens (CL) wear in keratoconus subjects comparing two different fitting approaches. Methods: Thirty-one keratoconus subjects (50 eyes) without previous history of CL wear were recruited for the study. Subjects were randomly fitted to either an apical-touch or three-pointtouch fitting approach. The lens’ back optic zone radius (BOZR) was 0.4 mm and 0.1 mm flatter than the first definite apical clearance lens, respectively. Differences between the baseline and post-CL wear for steepest, flattest and average corneal power (ACP) readings, central corneal astigmatism (CCA), maximum tangential curvature (KTag), anterior corneal surface asphericity, anterior corneal surface HOA and thinnest corneal thickness measured with Pentacam were compared. Results: A statistically significant flattening was found over time on the flattest and steepest simulated keratometry and ACP in apical-touch group (all p < 0.01). A statistically significant reduction in KTag was found in both groups after contact lens wear (all p < 0.05). Significant reduction was found over time in CCA (p = 0.001) and anterior corneal asphericity in both groups (p < 0.001). Thickness at the thinnest corneal point increased significantly after CL wear (p < 0.0001). Coma-like and total HOA root mean square (RMS) error were significantly reduced following CL wearing in both fitting approaches (all p < 0.05). Conclusion: Short-term rigid gas-permeable CL wear flattens the anterior cornea, increases the thinnest corneal thickness and reduces anterior surface HOA in keratoconus subjects. Apicaltouch was associated with greater corneal flattening in comparison to three-point-touch lens wear.

Bootstrap performance profiles in stochastic algorithms assessment

Optimization with stochastic algorithms has become a relevant research field. Due to its stochastic nature, its assessment is not straightforward and involves integrating accuracy and precision. Performance profiles for the mean do not show the trade-off between accuracy and precision, and parametric stochastic profiles require strong distributional assumptions and are limited to the mean performance for a large number of runs. In this work, bootstrap performance profiles are used to compare stochastic algorithms for different statistics. This technique allows the estimation of the sampling distribution of almost any statistic even with small samples. Multiple comparison profiles are presented for more than two algorithms. The advantages and drawbacks of each assessment methodology are discussed.