Multi-objective improvement of software using co-evolution and smart seeding

Optimising non-functional properties of software is an important part of the implementation process. One such property is execution time, and compilers target a reduction in execution time using a variety of optimisation techniques. Compiler optimisation is not always able to produce semantically equivalent alternatives that improve execution times, even if such alternatives are known to exist. Often, this is due to the local nature of such optimisations. In this paper we present a novel framework for optimising existing software using a hybrid of evolutionary optimisation techniques. Given as input the implementation of a program or function, we use Genetic Programming to evolve a new semantically equivalent version, optimised to reduce execution time subject to a given probability distribution of inputs. We employ a co-evolved population of test cases to encourage the preservation of the program’s semantics, and exploit the original program through seeding of the population in order to focus the search. We carry out experiments to identify the important factors in maximising efficiency gains. Although in this work we have optimised execution time, other non-functional criteria could be optimised in a similar manner

Vacuum effects in an asymptotically uniformly accelerated frame with a constant magnetic field

In the present article we solve the Dirac-Pauli and Klein Gordon equations in an asymptotically uniformly accelerated frame when a constant magnetic field is present. We compute, via the Bogoliubov coefficients, the density of scalar and spin 1/2 particles created. We discuss the role played by the magnetic field and the thermal character of the spectrum.Comment: 17 pages. RevTe

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

Nonlinear evolution of dark matter and dark energy in the Chaplygin-gas cosmology

The hypothesis that dark matter and dark energy are unified through the Chaplygin gas is reexamined. Using generalizations of the spherical model which incorporate effects of the acoustic horizon we show that an initially perturbative Chaplygin gas evolves into a mixed system containing cold dark matter-like gravitational condensate.Comment: 11 pages, 3 figures, substantial revision, title changed, content changed, added references, to appear in JCA

Algorithmic iteration for computational intelligence

Machine awareness is a disputed research topic, in some circles considered a crucial step in realising Artificial General Intelligence. Understanding what that is, under which conditions such feature could arise and how it can be controlled is still a matter of speculation. A more concrete object of theoretical analysis is algorithmic iteration for computational intelligence, intended as the theoretical and practical ability of algorithms to design other algorithms for actions aimed at solving well-specified tasks. We know this ability is already shown by current AIs, and understanding its limits is an essential step in qualifying claims about machine awareness and Super-AI. We propose a formal translation of algorithmic iteration in a fragment of modal logic, formulate principles of transparency and faithfulness across human and machine intelligence, and consider the relevance to theoretical research on (Super)-AI as well as the practical import of our results

Soil fungal community shift evaluation as a potential cadaver decomposition indicator

Fungi metabolise organic matter in situ and so alter both the bio-/physico-chemical properties and microbial community structure of the ecosystem. In particular, they are responsible reportedly for specific stages of decomposition. Therefore, this study aimed to extend previous bacteria-based forensic ecogenomics research by investigating soil fungal community and cadaver decomposition interactions in microcosms with garden soil (20 kg, fresh weight) and domestic pig (Sus scrofa domesticus) carcass (5 kg, leg). Soil samples were collected at depths of 0–10 cm, 10–20 cm and 20–30 cm on days 3, 28 and 77 in the absence (control −Pg) and presence (experimental +Pg) of Sus scrofa domesticus and used for total DNA extraction and nested polymerase chain reaction and denaturing gradient gel electrophoresis (PCR–DGGE) profiling of the 18S rRNA gene. The Shannon–Wiener (H′) community diversity indices were 1.25 ± 0.21 and 1.49 ± 0.30 for the control and experimental microcosms, respectively, while comparable Simpson species dominance (S) values were 0.65 ± 0.109 and 0.75 ± 0.015. Generally, and in contrast to parallel studies of the bacterial 16S rRNA and 16S rDNA profiles, statistical analysis (t-test) of the 18S dynamics showed no mathematically significant shifts in fungal community diversity (H′; p = 0.142) and dominance (S; p = 0.392) during carcass decomposition, necessitating further investigations

Sperm fertilizing ability in vitro influences bovine blastocyst miRNA content

MicroRNAs (miRNAs) are small highly conserved non-coding RNA molecules that orchestrate a wide range of biological processes through post-transcriptional regulation of gene expression. During development, miRNAs play a key role in driving embryo patterning and morphogenesis in a specific and stage-dependent manner. Here, we investigated whether sperm from bulls with different fertilizing ability in vitro influence blastocyst quality and miRNA content. Results demonstrate that blastocysts obtained using sperm from high fertility sires (H group) display significantly greater cleavage and blastocyst development as well as greater transcript abundance in blastocysts for the developmental competence markers CDX2, KRT8, NANOG, OCT4, PLAC8, PTGS2, SOX17, and SOX2, compared to blastocysts generated using sperm from low fertility sires (L group). In parallel, high throughput deep sequencing and differential expression studies revealed that H blastocysts exhibit a greater miRNA content compared to L blastocysts, with hsa-miR-4755–5p and hsa-miR-548d-3p uniquely detected in the H group, and greater abundance of hsa-miR-1225–3p in the H group. Gene ontology (GO) and KEGG pathway analyses indicated that the 3 differentially expressed miRNAs identified are involved in the regulation of many biological mechanisms with a key role in aspects of early embryo development, including transcriptional regulation, cellular biosynthesis, nucleic acid metabolism, cellular differentiation, apoptosis, cytoskeleton remodeling, cell-to-cell interactions, and endocytosis. Overall, our results indicate that sperm fertilizing ability influences blastocyst developmental ability and miRNA content. In addition, we demonstrate an association between blastocyst quality and miRNA content, thus suggesting the possibility to score miRNA expression as biomarkers for improved routine embryo selection technologies to support assisted reproductive efforts

Vitamin d3 enriches ceramide content in exosomes released by embryonic hippocampal cells

The release of exosomes can lead to cell\u2013cell communication. Nutrients such as vitamin D3 and sphingolipids have important roles in many cellular functions, including proliferation, dif-ferentiation, senescence, and cancer. However, the specific composition of sphingolipids in exo-somes and their changes induced by vitamin D3 treatment have not been elucidated. Here, we ini-tially observed neutral sphingomyelinase and vitamin D receptors in exosomes released from HN9.10 embryonic hippocampal cells. Using ultrafast liquid chromatography tandem mass spec-trometry, we showed that exosomes are rich in sphingomyelin species compared to whole cells. To interrogate the possible functions of vitamin D3, we established the optimal conditions of cell treatment and we analyzed exosome composition. Vitamin D3 was identified as responsible for the vitamin D receptor loss, for the increase in neutral sphingomyelinase content and sphingomyelin changes. As a consequence, the generation of ceramide upon vitamin D3 treatment was evident. Incubation of the cells with neutral sphingomyelinase, or the same concentration of ceramide pro-duced in exosomes was necessary and sufficient to stimulate embryonic hippocampal cell differen-tiation, as vitamin D3. This is the first time that exosome ceramide is interrogated for mediate the effect of vitamin D3 in inducing cell differentiation