Significance of specific IgG against sensitizing antigens in extrinsic allergic alveolitis: Serological methods in EAA

The aim of our study is to find differences in IgG in sera of potentially exposed and nonexposed individuals and to detect differences in concentrations of specific serum IgG among subjects with and without EAA. Seventy-two patients being followed for suspected interstitial lung disease were included. Specific IgG in sera were established by ImmunoCAP. Serum concentrations of Aspergillus fumigatus, Candida albicans IgG and mixture of moulds IgG were higher in subjects with exposure to relevant inhalation antigens (p < 0.05). Patients exposed to parrot and mammal hair mixture had higher serum concentration of specific IgG (p < 0.05). Subjects without exposure to mites had lower serum IgG to Dermatophagoides pteronyssinus, Dermatophagoides farinae, Dermatophagoides microceras and Glycophagus domesticus (p < 0.05). Higher concentration of serum specific IgG may show previous exposure to this antigen. Even though mite specific IgG are not commonly tested in EAA patients, we suggest their immunomodulatory activity may influence susceptibility to other inhalation antigens. Resumo: O objetivo do nosso estudo é descobrir diferenças da IgG no soro de possíveis indi-víduos expostos e não-expostos, bem como detetar diferenças de concentrações da IgG sérica específico entre indivíduos com e sem AAE. Foram incluídos setenta e dois pacientes com suspeita de doença pulmonar intersticial. A IgG sérica específica foi definida pelo ImmunoCAP. As concentrações séricas de IgG para o Aspergillus fumigatus, Candida albicans e mistura de fungos foram superiores em sujeitos expostos a inalação de antigénios relevantes (p < 0,05). Os pacientes expostos a uma mistura de penas de papagaio e pelos de mamíferos apresentaram uma maior concentração sérica da IgG específica (p < 0,05). Os indivíduos sem exposição a ácaros apresentaram menor IgG sérica para Dermatophagoides pteronyssinus, D. farinae, D. microceras e Glycophagus domesticus (p < 0,05). Uma elevada concentração de IgG sérica específica pode indicar uma exposição prévia a este antigénio. Embora a IgG específica para os ácaros não seja normalmente testada em pacientes com AAE, referimos que a sua atividade imunomoduladora pode influenciar a suscetibilidade de outras inalações de antigénios. Keywords: Aeroallergen, Hypersensitivity pneumonitis, Immunoglobulins, Indoor environment, Palavras chave: Aeroalergénio, Pneumonite de hipersensibilidade, Imunoglobulinas, Ambiente interio

Population diversity analysis in adaptive differential evolution variants with unconventional randomization schemes

This research represents a detailed insight into the modern and popular hybridization of unconventional quasiperiodic/chaotic sequences and evolutionary computation. It is aimed at the influence of different randomization schemes on the population diversity, thus on the performance, of two selected adaptive Differential Evolution (DE) variants. Experiments are focused on the extensive investigation of totally ten different randomization schemes for the selection of individuals in DE algorithm driven by the default pseudo-random generator of Java environment and nine different two-dimensional discrete chaotic systems, as the unconventional chaotic pseudo-random number generators. The population diversity is recorded for 15 test functions from the CEC 2015 benchmark set in 10D. © 2019, Springer Nature Switzerland AG.Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2019/002]; COST (European Cooperation in Science & Technology) under Action (ImAppNIO) [CA15140]; COST (European Cooperation in Science & Technology) under Action (cHiPSet) [IC1406]; VSB-Technical University of Ostrava [SGS 2019/137

On relation between swarm and evolutionary dynamics and complex networks

This paper is an introduction to a novel method for visualizing the dynamics of evolutionary algorithms in the form of networks. The whole idea is based on the obvious similarity between interactions between individuals in a swarm and evolutionary algorithms and for example, users of social networks, linking between web pages, etc. In this paper, two completely different areas of research are merged: (complex) networks and evolutionary computation. As already mentioned, interactions among the individuals in a swarm and evolutionary algorithms can be considered like user interactions in social networks or just people in society. This induces hypothesis whether interactions inside of EAs can be taken like interactions in society or swarm colonies. The analogy between individuals in populations in an arbitrary evolutionary algorithm and vertices of a network is discussed, as well as between edges in a network and communication between individuals in a population. © Springer Nature Switzerland AG 2019

How unconventional chaotic pseudo-random generators influence population diversity in differential evolution

This research focuses on the modern hybridization of the discrete chaotic dynamics and the evolutionary computation. It is aimed at the influence of chaotic sequences on the population diversity as well as at the algorithm performance of the simple parameter adaptive Differential Evolution (DE) strategy: jDE. Experiments are focused on the extensive investigation of totally ten different randomization schemes for the selection of individuals in DE algorithm driven by the default pseudo random generator of Java environment and nine different two-dimensional discrete chaotic systems, as the chaotic pseudo-random number generators. The population diversity and jDE convergence are recorded for 15 test functions from the CEC 2015 benchmark set in 30D. © Springer International Publishing AG, part of Springer Nature 2018.2018/177; IC406; MSMT-7778/2014, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; LO1303, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; 710577, Horizon 2020; CA15140; IGA/CebiaTech/2018/003; CZ.1.05/2.1.00/03.0089, FEDER, European Regional Development FundMinistry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2018/003]; COST ActionEuropean Cooperation in Science and Technology (COST) [CA15140, IC406]; SGS [2018/177]; VSB-TUO; EU's Horizon 2020 research and innovation programme [710577

Randomization of individuals selection in differential evolution

This research deals with the hybridization of two computational intelligence fields, which are the chaos theory and evolutionary algorithms. Experiments are focused on the extensive investigation on the different randomization schemes for selection of individuals in differential evolution algorithm (DE). This research is focused on the hypothesis whether the different distribution of different pseudo-random numbers or the similar distribution additionally enhanced with hidden complex chaotic dynamics providing the unique sequencing are more beneficial to the heuristic performance. This paper investigates the utilization of the two-dimensional discrete chaotic systems, which are Burgers and Lozi maps, as the chaotic pseudo-random number generators (CPRNGs) embedded into the DE. Through the utilization of either chaotic systems or equal identified pseudo-random number distribution, it is possible to entirely keep or remove the hidden complex chaotic dynamics from the generated pseudo random data series. This research utilizes set of 4 selected simple benchmark functions, and five different randomizations schemes; further results are compared against canonical DE. © Springer Nature Switzerland AG 2019

A brief overview of the synergy between metaheuristics and unconventional dynamics

This brief review paper focuses on the modern and original hybridization of the unconventional dynamics and the metaheuristic optimization algorithms. It discusses the concept of chaos-based optimization in general, i.e. the influence of chaotic sequences on the population diversity as well as at the metaheuristics performance. Further, the non-random processes used in evolutionary algorithms, and finally also the examples of the evolving complex network dynamics as the unconventional tool for the visualization and analysis of the population in popular optimization metaheuristics. This work should inspire the researchers for applying such methods and take advantage of possible performance improvements for the optimization tasks. © Springer Nature Switzerland AG 2020

Is chaotic randomization advantageous for higher dimensional optimization problems?

The focus of this work is the deeper insight into arising serious research questions connected with the growing popularity of combining metaheuristic algorithms and chaotic sequences showing quasi-periodic patterns. This paper reports analysis on the performance of popular and CEC 2019 competition winning strategy of Differential Evolution (DE), which is jDE, for optimization problems of higher dimensions. Experiments utilize ten chaos-driven quasi-random schemes for the indices selection and chaotic-driven crossover operations in the DE. All important performance characteristics are recorded and analyzed with simple descriptive statistics, Friedman rank tests and target-based comparisons analyzing distribution of hitting p% best minimum values over all versions and runs of jDE. The test suite was CEC 2015 in 50D. © 2020, Springer Nature Switzerland AG

Insight into adaptive differential evolution variants with unconventional randomization schemes

The focus of this work is the deeper insight into arising serious research questions connected with the growing popularity of combining metaheuristic algorithms and chaotic sequences showing quasi-periodic patterns. This paper reports an analysis of population dynamics by linking three elements like distribution of the results, population diversity, and differences between strategies of Differential Evolution (DE). Experiments utilize two frequently studied self-adaptive DE versions, which are simpler jDE and SHADE, further an original DE variant for comparisons, and totally ten chaos-driven quasi-random schemes for the indices selection in the DE. All important performance characteristics and population diversity are recorded and analyzed for the CEC 2015 benchmark set in 30D. © Springer Nature Switzerland AG 2020

Towards human cell simulation

The faithful reproduction and accurate prediction of the phe-notypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. For instance, many quantitative data (e.g., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. Though, even with a candidate parameterization, the simulation of mechanistic models could be challenging due to the extreme computational effort required. In this context, model reduction techniques and High-Performance Computing infrastructures could be leveraged to mitigate these issues. In addition, as cellular processes are characterized by multiple scales of temporal and spatial organization, novel hybrid simulators able to harmonize different modeling approaches (e.g., logic-based, constraint-based, continuous deterministic, discrete stochastic, spatial) should be designed. This chapter describes a putative unified approach to tackle these challenging tasks, hopefully paving the way to the definition of large-scale comprehensive models that aim at the comprehension of the cell behavior by means of computational tools