Occupational release of engineered nanoparticles: A review

Characterising the release of different types of Engineered Nanoparticles (ENPs) from various processes is of critical importance for the assessment of human exposure, as well as understanding the possible health effects of these particles. Therefore, the main aim of this chapter is to present a comprehensive review of studies which report on the release of airborne ENPs in different nanotechnology workplaces. The chapter will cover topics of relevance to the occupational characterisation of ENP emissions, ranging from the identification of different particle release sources and scenarios, to measurement methods and working towards a more uniform approach to characterisation. Furthermore, a brief review of ENP exposure control strategies, together with the application of mathematical modelling as an effective tool for the characterisation of emissions at nanotechnology workplaces is included.

Reducing luminance contrast on the window wall and users’ interventions in an office room

High luminance contrast between windows and surrounding surfaces could cause discomfort glare, which could reduce office workers’ productivity. It might also increase energy usage of buildings due to occupants’ interventions in lighting conditions to improve indoor visual quality. It is presumed that increasing the luminance of the areas surrounding the windows using a supplementary system, such Light Emitting Diodes (LEDs), could reduce discomfort glare. This paper reports on the results of a pilot study in a conventional office in Brisbane, Australia. The outcomes of this study indicated that a supplementary LED system could reduce the luminance contrast on the window wall from values in the order of 24:1 to 12:1. The results suggest that this reduction could significantly reduce discomfort glare from windows, as well as diminishing the likelihood of users’ intention to turn on the ceiling lights and/ or to move the blind down.

Development and evaluation of a spatial decision support system for malaria elimination in Bhutan

Background: Bhutan has reduced its malaria incidence significantly in the last 5 years, and is aiming for malaria elimination by 2016. To assist with the management of the Bhutanese malaria elimination programme a spatial decision support system (SDSS) was developed. The current study aims to describe SDSS development and evaluate SDSS utility and acceptability through informant interviews. Methods: The SDSS was developed based on the open-source Quantum geographical information system (QGIS) and piloted to support the distribution of long-lasting insecticidal nets (LLINs) and indoor residual spraying (IRS) in the two sub-districts of Samdrup Jongkhar District. It was subsequently used to support reactive case detection (RACD) in the two sub-districts of Samdrup Jongkhar and two additional sub-districts in Sarpang District. Interviews were conducted to ascertain perceptions on utility and acceptability of 11 informants using the SDSS, including programme and district managers, and field workers. Results: A total of 1502 households with a population of 7165 were enumerated in the four sub-districts, and a total of 3491 LLINs were distributed with one LLIN per 1.7 persons. A total of 279 households representing 728 residents were involved with RACD. Informants considered that the SDSS was an improvement on previous methods for organizing LLIN distribution, IRS and RACD, and could be easily integrated into routine malaria and other vector-borne disease surveillance systems. Informants identified some challenges at the programme and field level, including the need for more skilled personnel to manage the SDSS, and more training to improve the effectiveness of SDSS implementation and use of hardware. Conclusions: The SDSS was well accepted and informants expected its use to be extended to other malaria reporting districts and other vector-borne diseases. Challenges associated with efficient SDSS use included adequate skills and knowledge, access to training and support, and availability of hardware including computers and global positioning system receivers.

Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.