Higher Levels of Confusion: Rocket Sensors in the Northern Lights

In the summer of 2014 I spent nine weeks working with a team in the physics department of the University of Oslo in an attempt to determine if data from two sensors could be collected by one sensor. The two sensors, built by the University of New Hampshire and the University of Oslo, were part of the 2012 MICA rocket mission into the aurora borealis; they collected data on electron temperature and density respectively. Despite intense efforts, we were not successful in coming up with a relationship between the data sets of the two sensors. I learned that research often produces, if not definite results, then “higher levels of confusion,” which aid in the search for future answers

Seasonal Variations in the Metabolome and Bioactivity Profile of Fucus vesiculosus Extracted by an Optimised, Pressurised Liquid Extraction Protocol

The metabolism of seaweeds depends on environmental parameters, the availability of nutrients, and biotic/abiotic stresses; therefore, their chemical composition fluctuates throughout the year. This study investigated seasonal variations in the metabolome of the Baltic Sea brown alga Fucus vesiculosus and its potential relation to the bioactivity profile. By using a definitive screening design (DSD) combined with pressurised liquid extraction (PLE), an optimised protocol was developed to extract algal biomass monthly for a full calendar year. An untargeted metabolomics approach using ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MSn)-based molecular networking and manual dereplication was employed. The extracts were simultaneously screened for their in vitro antimicrobial, anticancer/apoptotic, and free radical scavenging activities. 44 compounds were putatively dereplicated in the metabolome. Many compounds were found to vary with the sampling month; phlorotannin total ion count (TIC) was highest in summer, whilst chlorophylls, lipids, and carotenoids peaked in winter and spring. The greatest radical scavenging and apoptotic activities against pancreas cancer cells observed in the summer months were attributed to high phlorotannin TIC. Methicillin-resistant Staphylococcus aureus (MRSA) inhibitory activity was produced year-round without a clear seasonal trend. This is the first study applying DSD-based optimised PLE extraction combined with a metabolome analysis of F. vesiculosus for the identification of seasonal variations in both metabolome and bioactivity

The building information modelling trajectory in facilities management: A review

There is a paucity of literature that examines building information modelling (BIM) for asset management within the architecture, engineering, construction and owner-operated (AECO) sector. This paper therefore presents a thorough review of published literature on the latest research and standards development that impact upon BIM and its application in facilities management (FM) during the operations and maintenance (O&M) phase of building usage. The purpose is to generate new ideas and provide polemic clarity geared to intellectually challenge readers from across a range of academic and industrial disciplines. The findings reveal that significant challenges facing the FM sector include the need for: greater consideration of long-term strategic aspirations; amelioration of data integration/interoperability issues; augmented knowledge management; enhanced performance measurement; and enriched training and competence development for facilities managers to better deal with the amorphous range of services covered by FM. Future work is also proposed in several key areas and includes: case studies to observe and report upon current practice and development; and supplementary research related to concepts of knowledge capture in relation to FM and the growing use of BIM for asset management

GeoSRM - online geospatial safety risk model for the GB rail network

RSSB and the University of Southampton's GeoData Institute have collaborated to research and develop a toolkit for managing large volumes of rail risk data. The pilot system encompasses concepts of highly complex geospatial 'big data', open standards, open source development tools and methodologies, and enables stakeholders to filter, analyse and visualise risk across the rail network, for a range of risk models. These include train derailments, suicides and passenger slip, trips and falls, and feature a wide range of spatially dependent parameters that affect the causal, escalation and consequence mechanisms. The risk has been calculated to a high resolution, splitting 2,100,000 m of track typically into 10 m sections. By creating geospatial representations of risk, the tool can help to identify risk hotspots and in this way contribute to the improvement of rail safety. Once scaled up to a National level and full range of risk models, the tool will deliver a powerful capability, unique across Europe. Further research is extending the prototype to incorporate live and historic environmental and related rail incident data to augment and improve the risk model