Algorithms and tools for in silico design of cell factories

PhD thesis in Bioengineering

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.

Eco-efficient self-compacting concrete with reduced Portland cement content and high volume of fly ash and metakaolin

The eco-efficient, self-compacting concrete (SCC) production, containing low levels of cement in its formulation, shall contribute for the constructions' sustainability due to the decrease in Portland cement use, to the use of industrial residue, for beyond the minimization of the energy needed for its placement and compaction. In this context, the present paper intends to assess the viability of SCC production with low cement levels by determining the fresh and hardened properties of concrete containing high levels of fly ash (FA) and also metakaolin (MK). Hence, 6 different concrete formulations were produced and tested: two reference concretes made with 300 and 500 kg/m3 of cement; the others were produced in order to evaluate the effects of high replacement levels of cement. Cement replacement by FA of 60% and by 50% of FA plus 20% of MK were tested and the addition of hydrated lime in these two types of concrete were also studied. To evaluate the self-compacting ability slump flow test, T500, J-ring, V-funnel and L-box were performed. In the hardened state the compressive strength at 3, 7, 14, 21, 28 and 90 days of age was determined. The results showed that it is possible to produce low cement content SCC by replacing high levels of cement by mineral additions, meeting the rheological requirements for self-compacting, with moderate resistances from 25 to 30 MPa after 28 days.

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.

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.

HEP-Frame: A software engineered framework to aid the development and efficient multicore execution of scientific code

This work was supported by FCT (Fundação para a Ciência e Tecnologia) within Project Scope (UID/CEC/00319/2013), by LIP (Laboratório de Instrumentação e Física Experimental de Partículas) and by Project Search-ON2 (NORTE-07-0162- FEDER-000086), co-funded by the North Portugal Regional Operational Programme (ON.2 - O Novo Norte), under the National Strategic Reference Framework, through the European Regional Development Fund.

Unfuzzying fuzzy parsing

Dissertação de Mestrado em Engenharia Informática

In silico constraint-based strain optimization methods: the quest for optimal cell factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

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.

A new and efficient synthesis of N3-cycloalkylamino-6,8-diaminopurines

[Excerpt] The purine core is a privileged scaffold in medicinal chemistry and the biological relevance of purine derivatives makes them attractive targets in the preparation of combinatorial libraries.1,2 In particular, there is a great interest in the synthesis of 8-substituted purines due to their important potential as antiviral and anticancer agents.3 Reports on 8-aminopurines are limited and general methods to obtain these purine derivatives are still needed.4 Cyclic amines and hydrazines are key structural motifs in various bioactive agents.5 Here we report a novel, efficient and inexpensive method for the synthesis of 6,8-diaminopurines 4 incorporating cycloalkylamino substituents at N3position of the purine ring. (...)

A novel and efficient approach to new N3-substituted-6,8-diaminopurines

[Excerpt] Purine nucleobases are fundamental biochemicals in living organisms. They have been a valuable inspiration for drug design once they play several key roles in the cell.1 To the best of our knowledge, reported routes to 8-aminopurines are still scarce due to the difficulty in introducing amino groups in this position of the purine ring. Here we report a novel, inexpensive and facile synthetic method to generate N3,N6-disubstituted-6,8-diaminopurines. In our research group, a number of substituted purines have been obtained from a common imidazole precursor, the 5-amino-4-cyanoformimidoyl imidazole 1. Recently, a comprehensive study on the reactivity of imidazoles 1 with nucleophiles under acidic conditions led us to develop experimental methods to incorporate primary amines into the cyanoformimidoyl group.2 (...)

A new and efficient synthesis of benzoimidazopurine derivatives

[Excerpt] Purine nucleobases are essential biomolecules in living organisms. Playing several key roles in the cell, they have been a significant inspiration for drug design.1 Benzimidazole nucleus is an important pharmacophore in the development of molecules with pharmaceutical or biological interest. Benzimidazoles have been reported to display significant pharmacological activities such as antiulcer, antifungal, antiparkinson, anticancer and antibiotic.2 Fused structures incorporating these two scaffolds might be important for medicinal chemistry and, to the best of our knowledge, there are no reports of these systems in the literature. In particular, benzo[4,5]imidazo[2,1]purines seem to be novel and must be important target molecules in the heterocyclic synthesis. (...)

Cost-efficient one-part alkali-activated mortars with low global warming potential for floor heating systems applications

Increasing building energy efficiency is one the most cost-effective ways to reduce emissions. The use of thermal insulation materials mitigates heat loss in buildings, therefore minimising heat energy needs. In recent years, several papers were published on the subject of foam alkali-activated cements with enhanced thermal conductivity. However, on those papers cost analysis was strangely avoided. This paper presents experimental results on one-part alkali-activated cements. It also includes global warming potential assessment and cost analysis. Foam one-part alkali-activated cements cost simulations considering two carbon dioxide social costs scenarios are also included. The results show that one-part alkali-activated cements mixtures based on 26%OPC + 58.3%FA + 8%CS + 7.7%CH and 3.5% hydrogen peroxide constitute a promising cost-efficient (67 euro/m3), thermal insulation solution for floor heating systems. This mixture presents a low global warming potential of 443 KgCO2eq/m3. The results confirm that in both carbon dioxide social cost scenarios the mixture 26 OPC + 58.3 FA + 8 CS + 7.7 CH with 3.5% hydrogen peroxide foaming agent is still the most cost efficient.

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.