Infrared spectroscopy of astrophysically relevant hydrocarbons

This thesis is about the study of hydrocarbons via infrared spectroscopy. Hydrocarbons play an important role in the chemistry of a variety of astronomical environments from the diffuse interstellar medium to dense hydrocarbon atmospheres of solar system bodies (e.g., planetary atmospheres of Jupiter and Saturn’s moon Titan) and exoplanets. For most astronomical objects, the determination of chemical abundances, and consequently an understanding of the chemical evolution relies upon the observation of molecular spectra. However, to date astronomical models need to make assumptions, because not all of the molecules expected have been observed. This is due, in part, to a lack of accurate spectral data, which is needed for unambiguous identification. Using a combination of high-resolution infrared experiments and/or high level ab initio calculations of vibration frequencies and ground state spectroscopic constants, the infrared spectral data of HC2H, HC4H, HC6H, HC8H, C3H4, c-C3H3+ and Dn-PAHs (polycyclic aromatic hydrocarbons, PAH) are studied and presented, in order to fill in some of the missing spectral data. Laboratory astrophysics and astrochemistr

13C Mono-Substituted Isotopologues of Propyne (H_3CCCH): Investigating the Acetylenic CH Stretch Perturbation

Laboratory astrophysics and astrochemistr

Laboratory gas-phase detection of the cyclopropenyl cation (c-C3H3)

The cyclopropenyl cation (c-C3H3 +) is the smallest aromatic hydrocarbon molecule and considered to be a pivotal intermediate in ion–molecule reactions in space. An astronomical identification has been prohibited so far, because of a lack of gas-phase data. Here we report the first high resolution infrared laboratory gas-phase spectrum of the ν4 (C–H asymmetric stretching) fundamental band of c-C3H3 +. The c-C3H3 + cations are generated in supersonically expanding planar plasma by discharging a propyne/helium gas pulse, yielding a rotational temperature of ∼35 K. The absorption spectrum is recorded in the 3.19μm region using sensitive continuous-wave cavity ring-down spectroscopy. The analysis of about 130 ro-vibrational transitions results in precise spectroscopic parameters. These constants allow for an accurate comparison with high-level theoretical predictions, and provide the relevant information needed to search for this astrochemically relevant carbo-cation in space.NWO-VICILaboratory astrophysics and astrochemistr

The high-resolution infrared spectrum of the ν3 + ν5 combination band of jet-cooled propyne

Laboratory astrophysics and astrochemistr

Stretching Our Knowledge of the Electronic Ground State of C_3: the Spectroscopy of Stretching Modes of C_3

Laboratory astrophysics and astrochemistr

Deuterated polycyclic aromatic hydrocarbons: Revisited

Interstellar matter and star formatio

High-resolution laser spectroscopy of the A ̃ 1 Pi u - X ̃ 1 Sigma g+ transition of 13C12C12C and 12C13C12C

Laboratory astrophysics and astrochemistr

Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure

Heart failure (HF) is a leading cause of morbidity and mortality worldwide. A small proportion of HF cases are attributable to monogenic cardiomyopathies and existing genome-wide association studies (GWAS) have yielded only limited insights, leaving the observed heritability of HF largely unexplained. We report results from a GWAS meta-analysis of HF comprising 47,309 cases and 930,014 controls. Twelve independent variants at 11 genomic loci are associated with HF, all of which demonstrate one or more associations with coronary artery disease (CAD), atrial fibrillation, or reduced left ventricular function, suggesting shared genetic aetiology. Functional analysis of non-CAD-associated loci implicate genes involved in cardiac development (MYOZ1, SYNPO2L), protein homoeostasis (BAG3), and cellular senescence (CDKN1A). Mendelian randomisation analysis supports causal roles for several HF risk factors, and demonstrates CAD-independent effects for atrial fibrillation, body mass index, and hypertension. These findings extend our knowledge of the pathways underlying HF and may inform new therapeutic strategies

Associations of autozygosity with a broad range of human phenotypes

In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding

Geographic profiling applied to testing models of bumble-bee foraging

Geographical profiling (GP) was originally developed as a statistical tool to help police forces prioritize lists of suspects in investigations of serial crimes. GP uses the location of related crime sites to make inferences about where the offender is most likely to live, and has been extremely successful in criminology. Here, we show how GP is applicable to experimental studies of animal foraging, using the bumble-bee Bombus terrestris. GP techniques enable us to simplify complex patterns of spatial data down to a small number of parameters (2-3) for rigorous hypothesis testing. Combining computer model simulations and experimental observation of foraging bumble-bees, we demonstrate that GP can be used to discriminate between foraging patterns resulting from (i) different hypothetical foraging algorithms and (ii) different food item (flower) densities. We also demonstrate that combining experimental and simulated data can be used to elucidate animal foraging strategies: specifically that the foraging patterns of real bumble-bees can be reliably discriminated from three out of nine hypothetical foraging algorithms. We suggest that experimental systems, like foraging bees, could be used to test and refine GP model predictions, and that GP offers a useful technique to analyse spatial animal behaviour data in both the laboratory and field