Computational Infrared Spectroscopy of 958 Phosphorus-Bearing Molecules

Phosphine is now well-established as a biosignature, which has risen to prominence with its recent tentative detection on Venus. To follow up this discovery and related future exoplanet biosignature detections, it is important to spectroscopically detect the presence of phosphorus-bearing atmospheric molecules that could be involved in the chemical networks producing, destroying or reacting with phosphine. We start by enumerating phosphorus-bearing molecules (P-molecules) that could potentially be detected spectroscopically in planetary atmospheres and collecting all available spectral data. Gaseous P-molecules are rare, with speciation information scarce. Very few molecules have high accuracy spectral data from experiment or theory; instead, the best current spectral data was obtained using a high-throughput computational algorithm, RASCALL, relying on functional group theory to efficiently produce approximate spectral data for arbitrary molecules based on their component functional groups. Here, we present a high-throughput approach utilizing established computational quantum chemistry methods (CQC) to produce a database of approximate infrared spectra for 958 P-molecules. These data are of interest for astronomy and astrochemistry (importantly identifying potential ambiguities in molecular assignments), improving RASCALL's underlying data, big data spectral analysis and future machine learning applications. However, this data will probably not be sufficiently accurate for secure experimental detections of specific molecules within complex gaseous mixtures in laboratory or astronomy settings. We chose the strongly performing harmonic ωB97X-D/def2-SVPD model chemistry for all molecules and test the more sophisticated and time-consuming GVPT2 anharmonic model chemistry for 250 smaller molecules. Limitations to our automated approach, particularly for the less robust GVPT2 method, are considered along with pathways to future improvements. Our CQC calculations significantly improve on existing RASCALL data by providing quantitative intensities, new data in the fingerprint region (crucial for molecular identification) and higher frequency regions (overtones, combination bands), and improved data for fundamental transitions based on the specific chemical environment. As the spectroscopy of most P-molecules have never been studied outside RASCALL and this approach, the new data in this paper is the most accurate spectral data available for most P-molecules and represent a significant advance in the understanding of the spectroscopic behavior of these molecules.</jats:p

Ladakh: Diverse, high-altitude extreme environments for off-earth analogue and astrobiology research

This paper highlights unique sites in Ladakh, India, investigated during our 2016 multidisciplinary pathfinding expedition to the region. We summarize our scientific findings and the site's potential to support science exploration, testing of new technologies and science protocols within the framework of astrobiology research. Ladakh has several accessible, diverse, pristine and extreme environments at very high altitudes (3000-5700 m above sea level). These sites include glacial passes, sand dunes, hot springs and saline lake shorelines with periglacial features. We report geological observations and environmental characteristics (of astrobiological significance) along with the development of regolith-landform maps for cold high passes. The effects of the diurnal water cycle on salt deliquescence were studied using the ExoMars Mission instrument mockup: HabitAbility: Brines, Irradiance and Temperature (HABIT). It recorded the existence of an interaction between the diurnal water cycle in the atmosphere and salts in the soil (which can serve as habitable liquid water reservoirs). Life detection assays were also tested to establish the best protocols for biomass measurements in brines, periglacial ice-mud and permafrost melt water environments in the Tso-Kar region. This campaign helped confirm the relevance of clays and brines as interest targets of research on Mars for biomarker preservation and life detection.The team would like to express its gratitude to BirbalSahni Institute of Palaeosciences, Department of Science and Technology,Office of Chief Wildlife Warden of Ladakh, Government of India for helpingarrange the requisite clearances and permits for the conducted work. Projectmentoring and guidance provided by Spaceward Bound members at NASAAmes Research Center. Financial and logistics support provided by TataMotors Ltd, Inspired Journeys Co, Pearl Travels Ltd and NationalGeographic Traveller India. Website and IT support provided by the BlueMarble Space Institute of Science. Audio-video documentation support pro-vided by Astroproject India and The H

Light-weight and adaptive reasoning for mobile web services

The growth of smart phones and PDAs coupled with the emergence of Web Services as the de facto technology for supporting seamless heterogeneous integration has led to an emerging focus on mobile services. This emergence of mobile services necessitates service selection mechanisms that are accurate and efficient. Service selection involves matching of a user's requirements against the available services in the user's environment. It is well established that accuracy in service matching is improved by the use of semantics as opposed to simpler approaches such as keyword / interface matching. Semantic matching is performed by semantic reasoners. Current approaches to semantics based service selection tend to perform matching using external / remote high performance servers, because reasoning is a computationally complex and resource intensive activity that does not scale well to mobile devices. However, there are several advantages of performing semantic service matching on-board the mobile device. For instance, on-board matching avoids the overheads associated with the provision and maintenance of external servers to perform matching remotely. Additionally, continuous network access to a remote server has been shown to be a relatively higher drain on a mobile device's battery power when compared to processing activities. Furthermore, a connection may not always be available since mobile devices suffer from intermittent connectivity and frequent disconnection. There may also privacy concerns with transmitting sensitive data to a third party remote server (e.g. a user's shopping preferences and habits). Therefore, in this thesis we propose and develop a novel light-weight and adaptive approach for on-board semantic mobile matching. This thesis makes two significant contributions. Firstly, due to computational complexity, current reasoners cannot perform matching of large ontologies on mobile resource constrained devices. Therefore, we propose and develop mTableaux which enables mobile semantic matching by performing optimisations of the well-known Tableaux algorithm that is used in many of the state-of-the-art open source and commercial reasoners today. These optimisations result in improving the computational efficiency of the semantic reasoning process with a specific focus on scaling to mobile devices, without significantly reducing result accuracy. Secondly, current reasoners typically produce only a positive or negative result under an "all or nothing" principle in which the matching task must be completed in full before a result is provided. Therefore, we propose and develop an adaptive and incremental approach to deliver the outputs of a reasoning task. This allows a mobile user to get valid partial results from a reasoner depending on constraints such as changing context, time or availability of computational resources. We have implemented our proposed light-weight and adaptive reasoning strategies, and conducted extensive experimental performance evaluations which clearly demonstrate that our strategies improve response time and enable incremental matching. Our performance evaluations clearly demonstrate that the efficiency improvements in response time do not compromise accuracy. This evaluation includes tests on a resource constrained mobile device and a comparison of our approach against commercial and open source reasoners in desktop environments, using two realistic application scenarios as well as publicly available ontologies. In summary this dissertation has addressed the problem of enabling efficient and accurate mobile reasoning on small devices to meet dynamic resource levels and user needs in mobile environments. The research done over the course of this dissertation has been published in one international journal paper, seven conference papers and one workshop paper

Light-weight and adaptive reasoning for mobile web services

The growth of smart phones and PDAs coupled with the emergence of Web Services as the de facto technology for supporting seamless heterogeneous integration has led to an emerging focus on mobile services. This emergence of mobile services necessitates service selection mechanisms that are accurate and efficient. Service selection involves matching of a user's requirements against the available services in the user's environment. It is well established that accuracy in service matching is improved by the use of semantics as opposed to simpler approaches such as keyword / interface matching. Semantic matching is performed by semantic reasoners. Current approaches to semantics based service selection tend to perform matching using external / remote high performance servers, because reasoning is a computationally complex and resource intensive activity that does not scale well to mobile devices. However, there are several advantages of performing semantic service matching on-board the mobile device. For instance, on-board matching avoids the overheads associated with the provision and maintenance of external servers to perform matching remotely. Additionally, continuous network access to a remote server has been shown to be a relatively higher drain on a mobile device's battery power when compared to processing activities. Furthermore, a connection may not always be available since mobile devices suffer from intermittent connectivity and frequent disconnection. There may also privacy concerns with transmitting sensitive data to a third party remote server (e.g. a user's shopping preferences and habits). Therefore, in this thesis we propose and develop a novel light-weight and adaptive approach for on-board semantic mobile matching. This thesis makes two significant contributions. Firstly, due to computational complexity, current reasoners cannot perform matching of large ontologies on mobile resource constrained devices. Therefore, we propose and develop mTableaux which enables mobile semantic matching by performing optimisations of the well-known Tableaux algorithm that is used in many of the state-of-the-art open source and commercial reasoners today. These optimisations result in improving the computational efficiency of the semantic reasoning process with a specific focus on scaling to mobile devices, without significantly reducing result accuracy. Secondly, current reasoners typically produce only a positive or negative result under an "all or nothing" principle in which the matching task must be completed in full before a result is provided. Therefore, we propose and develop an adaptive and incremental approach to deliver the outputs of a reasoning task. This allows a mobile user to get valid partial results from a reasoner depending on constraints such as changing context, time or availability of computational resources. We have implemented our proposed light-weight and adaptive reasoning strategies, and conducted extensive experimental performance evaluations which clearly demonstrate that our strategies improve response time and enable incremental matching. Our performance evaluations clearly demonstrate that the efficiency improvements in response time do not compromise accuracy. This evaluation includes tests on a resource constrained mobile device and a comparison of our approach against commercial and open source reasoners in desktop environments, using two realistic application scenarios as well as publicly available ontologies. In summary this dissertation has addressed the problem of enabling efficient and accurate mobile reasoning on small devices to meet dynamic resource levels and user needs in mobile environments. The research done over the course of this dissertation has been published in one international journal paper, seven conference papers and one workshop paper

Dehydration Enhances Prebiotic Lipid Remodeling and Vesicle Formation in Acidic Environments

The encapsulation of genetic polymers inside lipid bilayer compartments is a vital step in the emergence of cell-based life. However, even though acidic conditions promote many reactions required for generating prebiotic building blocks, prebiotically-relevant lipids tend to form denser aggregates at acidic pHs rather than prebiotically useful vesicles that exhibit sufficient solute encapsulation. Here we describe how dehydration/rehydration (DR) events, a prebiotically-relevant physicochemical process known to promote polymerization reactions, can remodel dense lipid aggregates into thin-walled vesicles capable of RNA encapsulation even at acidic pHs. Furthermore, DR events appears to favor the encapsulation of RNA within thin-walled vesicles over more lipid-rich vesicles, thus conferring such vesicles a selective advantage

Influence of Metal Ions on Model Protoamphiphilic Vesicular Systems: Insights from Laboratory and Analogue Studies

Metal ions strongly affect the self-assembly and stability of membranes composed of prebiotically relevant amphiphiles (protoamphiphiles). Therefore, evaluating the behavior of such amphiphiles in the presence of ions is a crucial step towards assessing their potential as model protocell compartments. We have recently reported vesicle formation by N-acyl amino acids (NAAs), an interesting class of protoamphiphiles containing an amino acid linked to a fatty acid via an amide linkage. Herein, we explore the effect of ions on the self-assembly and stability of model N-oleoyl glycine (NOG)-based membranes. Microscopic analysis showed that the blended membranes of NOG and Glycerol 1-monooleate (GMO) were more stable than pure NOG vesicles, both in the presence of monovalent and divalent cations, with the overall vesicle stability being 100-fold higher in the presence of a monovalent cation. Furthermore, both pure NOG and NOG + GMO mixed systems were able to self-assemble into vesicles in natural water samples containing multiple ions that were collected from active hot spring sites. Our study reveals that several aspects of the metal ion stability of NAA-based membranes are comparable to those of fatty acid-based systems, while also confirming the robustness of compositionally heterogeneous membranes towards high metal ion concentrations. Pertinently, the vesicle formation by NAA-based systems in terrestrial hot spring samples indicates the conduciveness of these low ionic strength freshwater systems for facilitating prebiotic membrane-assembly processes. This further highlights their potential to serve as a plausible niche for the emergence of cellular life on the early Earth