Evolutionary optimization of aerofoil profile

This thesis deals with the heuristic optimization of an F1A free flight airfoil. The goal is to generate an airfoil that is better than the ones currently in use. We implemented three optimization algorithms, differential evolution (DE), Firework algorithm (FA) and Particle swarm optimization (PSO). Currently used airfoils, called LDA (Low-drag airfoil) are able to obtain high speed in the phase of climbing but in the free flight phase they fly poorly compared to their predecessors. With the help of optimization methods we aim to find an airfoil that performs both tasks well. All heuristic algorithms were developed in java programming language using a customized JMetal library. Each airfoil is presented with two Bézier curves, one for the upper and one for the lower half of the foil. This kind of presentation gives us more freedom and control, but it comes at a price - the software may generate irregular shapes due to randomness. That is why it is important to pay attention to structural constraints (i.e. airfoil thickness). Airfoils are evaluated using Xfoil [3] which calculates the characteristics of an airfoil. Our experiments show that L/D ratio is not a good indicator of airfoil quality and one has to take into account other parameters as well. A multi-objective criteria function would therefore be advisable

Additional file 12: Figure S1. of Construction of an integrative regulatory element and variation map of the murine Tst locus

Integrated gene transcription regulatory elements for atlas development. Schematic of elements affecting gene transcription and expression at the level of chromatin state (histone modifications, DNA methylation, chromatin accessibility), through transcription factors and RNA polymerase binding, variation impact and microRNAs miRNAs influence. (JPG 1035 kb

Additional file 11: Figure S2. of Construction of an integrative regulatory element and variation map of the murine Tst locus

Primers positions used in sequencing the Tst locus. A) Positions of primers used for amplification of ~ 3 kb segments (A, B, C) of Tst region. B) Location of PCR primers for detailed sequencing of A, B, and C segments. (JPG 4083 kb

Additional file 8: Table S8. of Construction of an integrative regulatory element and variation map of the murine Tst locus

Predicted miRNA target sites. (DOCX 22 kb

Additional file 9: Table S9. of Construction of an integrative regulatory element and variation map of the murine Tst locus

Merged mouse single nucleotide polymorphisms (SNP) from Ensembl and Mouse genomes project (Wellcome Trust Sanger Institute). (DOCX 63 kb

Genetic identification of thiosulfate sulfurtransferase as an adipocyte-expressed antidiabetic target in mice selected for leanness.

The discovery of genetic mechanisms for resistance to obesity and diabetes may illuminate new therapeutic strategies for the treatment of this global health challenge. We used the polygenic \u27lean\u27 mouse model, which has been selected for low adiposity over 60 generations, to identify mitochondrial thiosulfate sulfurtransferase (Tst; also known as rhodanese) as a candidate obesity-resistance gene with selectively increased expression in adipocytes. Elevated adipose Tst expression correlated with indices of metabolic health across diverse mouse strains. Transgenic overexpression of Tst in adipocytes protected mice from diet-induced obesity and insulin-resistant diabetes. Tst-deficient mice showed markedly exacerbated diabetes, whereas pharmacological activation of TST ameliorated diabetes in mice. Mechanistically, TST selectively augmented mitochondrial function combined with degradation of reactive oxygen species and sulfide. In humans, TST mRNA expression in adipose tissue correlated positively with insulin sensitivity in adipose tissue and negatively with fat mass. Thus, the genetic identification of Tst as a beneficial regulator of adipocyte mitochondrial function may have therapeutic significance for individuals with type 2 diabetes. Nat Med 2016 Jul; 22(7):771-9