Effect of water vapour condensation on the radon content in subsurface air in a hypogeal inactive-volcanic environment in Galdar cave, Spain

Fluctuations of trace gas activity as a response to variations in weather and microclimate conditions were monitored over a year in a shallow volcanic cave (Painted Cave, Galdar, Canary Islands, Spain). 222Rn concentration was used due to its greater sensitivity to hygrothermal variations than CO2 concentration. Radon concentration in the cave increases as effective vapour condensation within the porous system of the rock surfaces inside the cave increases due to humidity levels of more than 70%. Condensed water content in pores was assessed and linked to a reduction in the direct passage of trace gases. Fluctuations in radon activity as a response to variations in weather and microclimate conditions were statistically identified by clustering entropy changes on the radon signal and parameterised to predict radon concentration anomalies. This raises important implications for other research fields, including the surveillance of shallow volcanic and seismic activity, preventive conservation of cultural heritage in indoor spaces, indoor air quality control and studies to improve understanding of the role of subterranean terrestrial ecosystems as reservoirs and/or temporary sources of trace gases.

Measuring color differences in gonioapparent materials used in the automotive industry

This paper illustrates how to design a visual experiment to measure color differences in gonioapparent materials and how to assess the merits of different advanced color-difference formulas trying to predict the results of such experiment. Successful color-difference formulas are necessary for industrial quality control and artificial color-vision applications. A color- difference formula must be accurate under a wide variety of experimental conditions including the use of challenging materials like, for example, gonioapparent samples. Improving the experimental design in a previous paper [Melgosaet al., Optics Express 22, 3458-3467 (2014)], we have tested 11 advanced color-difference formulas from visual assessments performed by a panel of 11 observers with normal colorvision using a set of 56 nearly achromatic colorpairs of automotive gonioapparent samples. Best predictions of our experimental results were found for the AUDI2000 color-difference formula, followed by color-difference formulas based on the color appearance model CIECAM02. Parameters in the original weighting function for lightness in the AUDI2000 formula were optimized obtaining small improvements. However, a power function from results provided by the AUDI2000 formula considerably improved results, producing values close to the inter-observer variability in our visual experiment. Additional research is required to obtain a modified AUDI2000 color-difference formula significantly better than the current one.

Radon gas. Environmental concentration measures and remediation actions in exposed buildings

The main contribution to the radiological impact from natural radiation received by general population is due to the emission of radon (222Rn). The objective of this project is the study of radon gas as a radioactive element in our buildings (existing and future constructions) to avoid its influence in interior rooms. The proposed methodology reflects different aspects of natural radioactivity in buildings, their sources, their control criteria and regulatory framework; aspects related to the presence of radon in our constructions, entryways, measurement methodology for indoor environmental concentration are studied; other protection solutions and remediation measures in both existing buildings and new construction projects are analyzed. In conclusion, the paper presents previous evaluation tools, the analysis of existing concentration and the choice of the most appropriate mitigation / remediation measures depending on each case, through the establishment of different architectural proposals to plan actions against radon where necessary.

Intelligent Decision-Making System Frameworks for a Digital Plan of Work: A Theoretical Investigation for the Construction Industry

The construction industry is characterised by fragmentation and suffers from lack of collaboration, often adopting adversarial working practices to achieve deliverables. For the UK Government and construction industry, BIM is a game changer aiming to rectify this fragmentation and promote collaboration. However it has become clear that there is an essential need to have better controls and definitions of both data deliverables and data classification. Traditional methods and techniques for collating and inputting data have shown to be time consuming and provide little to improve or add value to the overall task of improving deliverables. Hence arose the need in the industry to develop a Digital Plan of Work (DPoW) toolkit that would aid the decision making process, providing the required control over the project workflows and data deliverables, and enabling better collaboration through transparency of need and delivery. The specification for the existing Digital Plan of Work (DPoW) was to be, an industry standard method of describing geometric, requirements and data deliveries at key stages of the project cycle, with the addition of a structured and standardised information classification system. However surveys and interviews conducted within this research indicate that the current DPoW resembles a digitised version of the pre-existing plans of work and does not push towards the data enriched decision-making abilities that advancements in technology now offer. A Digital Framework is not simply the digitisation of current or historic standard methods and procedures, it is a new intelligent driven digital system that uses new tools, processes, procedures and work flows to eradicate waste and increase efficiency. In addition to reporting on conducted surveys above, this research paper will present a theoretical investigation into usage of Intelligent Decision Support Systems within a digital plan of work framework. Furthermore this paper will present findings on the suitability to utilise advancements in intelligent decision-making system frameworks and Artificial Intelligence for a UK BIM Framework. This should form the foundations of decision-making for projects implemented at BIM level 2. The gap identified in this paper is that the current digital toolkit does not incorporate the intelligent characteristics available in other industries through advancements in technology and collation of vast amounts of data that a digital plan of work framework could have access to and begin to develop, learn and adapt for decision-making through the live interaction of project stakeholders.