A profluorescent azaphenalene nitroxide for nitroxide-mediated polymerization

A novel nitroxide-mediated polymerization (NMP) control agent; 1,1,3,3-tetramethyl-2,3-dihydro-2-azaphenalen-2-yloxyl (TMAO), was used in the free-radical polymerization of styrene. The conversion of styrene during NMP was studied using FT-Raman spectroscopy and the effectiveness of TMAO as a NMP control agent was assessed by GPC analysis. Fidelity of the TMAO-alkoxyamine end-group on the synthesized polymers was confirmed by GPC, UV-Vis and fluorescence spectroscopic analyses. Comparison to the well known NMP control agent, TEMPO was made. TMAO showed control of molecular weight approaching that of TEMPO. Attempts to improve the properties of TMAO as an NMP control agent by synthesizing an analogue with bulkier substituents around the nitroxide did not generate the target molecule but demonstrated some of the interesting chemistry of the azaphenalene ring system

Start playing with your food : fun food experiences with mobile social media

Healthy and sustainable food is gaining more attention from consumers, industry, and researchers. Yet many approaches to date are limited to information dissemination, advertisement or education. We have embarked on a three year collaborative research project (2011 – 2013) to explore urban food practices – eating, cooking, growing food – to support the well-being of people and the environment. Our overall goal is to employ a user-centred interaction design research approach to inform the development of entertaining, real-time, mobile and networked applications, engaging playful feedback to build motivation. Our aspiration for this study is to deliver usable and useful mobile and situated interaction prototypes that employ individual and group strategies to foster food cultures that provide new pathways to produce, share and enjoy food that is green, healthy, and fun.

Are low CO2 emitters in rural areas also socially excluded? An empirical investigation of travel diary data from rural Northern Ireland

The reduction of CO2 emissions and social exclusion are two key elements of UK transport strategy. Despite intensive research on each theme, little effort has so far been made linking the relationship between emissions and social exclusion. In addition, current knowledge on each theme is limited to urban areas; little research is available on these themes for rural areas. This research contributes to this gap in the literature by analysing 157 weekly activity-travel diary data collected from three case study areas with differential levels of area accessibility and area mobility options, located in rural Northern Ireland. Individual weekly CO2 emission levels from personal travel diaries (both hot exhaust emission and cold-start emission) were calculated using average speed models for different modes of transport. The socio-spatial patterns associated with CO2 emissions were identified using a general linear model whereas binary logistic regression analyses were conducted to identify mode choice behaviour and activity patterns. This research found groups that emitted a significantly lower level of CO2 included individuals living in an area with a higher level of accessibility and mobility, non-car, non-working, and low-income older people. However, evidence in this research also shows that although certain groups (e.g. those working, and residing in an area with a lower level of accessibility) emitted higher levels of CO2, their rate of participation in activities was however found to be significantly lower compared to their counterparts. Based on the study findings, this research highlights the need for both soft (e.g. teleworking) and physical (e.g. accessibility planning) policy measures in rural areas in order to meet government’s stated CO2 reduction targets while at the same time enhancing social inclusion.

Living characteristics of the free-radical ring-closing polymerization of diallyldimethylammonium chloride

In this communication we provide the most recent results on RAFT-mediated ring-closing polymerization of diallyldimethylammonium chloride (DADMAC). The polymerization was carried out in aqueous solution employing 2,2′-azobis(2-methylpropionamidine)-dihydrochloride as the free radical initiator and trithiocarbonate RAFT agent (2-{[(dodecylsulfanyl)carbonothioyl sulfanyl]}propanoic acid, DoPAT) as the controlling RAFT agent. The results show that – while the system is not as completely controlled as previously described – it is nevertheless possible to mediate the polymerization of DADMAC and impart some living characteristics onto the system. The initial study on the RAFT-mediated polymerization of DADMAC may have overestimated the degree of livingness within this reaction. However, it is possible – at low conversions – for some living characteristics to be observed, as the evolution of molecular weight with conversion is linear. In addition, polymers with a reasonably narrow polydispersity can be isolated.

Determining operational measures from multi-camera surveillance systems using soft biometrics

CCTV and surveillance networks are increasingly being used for operational as well as security tasks. One emerging area of technology that lends itself to operational analytics is soft biometrics. Soft biometrics can be used to describe a person and detect them throughout a sparse multi-camera network. This enables them to be used to perform tasks such as determining the time taken to get from point to point, and the paths taken through an environment by detecting and matching people across disjoint views. However, in a busy environment where there are 100's if not 1000's of people such as an airport, attempting to monitor everyone is highly unrealistic. In this paper we propose an average soft biometric, that can be used to identity people who look distinct, and are thus suitable for monitoring through a large, sparse camera network. We demonstrate how an average soft biometric can be used to identify unique people to calculate operational measures such as the time taken to travel from point to point.

Activity modelling in crowded environments : a soft decision approach

Probabilistic topic models have recently been used for activity analysis in video processing, due to their strong capacity to model both local activities and interactions in crowded scenes. In those applications, a video sequence is divided into a collection of uniform non-overlaping video clips, and the high dimensional continuous inputs are quantized into a bag of discrete visual words. The hard division of video clips, and hard assignment of visual words leads to problems when an activity is split over multiple clips, or the most appropriate visual word for quantization is unclear. In this paper, we propose a novel algorithm, which makes use of a soft histogram technique to compensate for the loss of information in the quantization process; and a soft cut technique in the temporal domain to overcome problems caused by separating an activity into two video clips. In the detection process, we also apply a soft decision strategy to detect unusual events.We show that the proposed soft decision approach outperforms its hard decision counterpart in both local and global activity modelling.