Hudumia: a platform to support spontaneous volunteers' situational awareness, coordination and safety underemergency scenarios

Spontaneous volunteers always emerge under emergency scenarios and are vital to a successful community response, yet some uncertainty subsists around their role and its inherent acceptance by official entities under emergency scenarios. In our research we have identified that most of the spontaneous volunteers do have none or little support from official entities, hence they end up facing critical problems as situational awareness, safety instructions and guidance, motivation and group organization. We argue that official entities still play a crucial role and should change some of their behaviors regarding spontaneous volunteerism. We aim with this thesis to design a software architecture and a framework in order to implement a solution to support spontaneous volunteerism under emergency scenarios along with a set of guidelines for the design of open information management systems. Together with the collaboration from both citizens and emergency professionals we have been able to attain several important contributions, as the clear identification of the roles taken by both spontaneous volunteers and professionals, the importance of volunteerism in overall community response and the role which open collaborative information management systems have in the community volunteering efforts. These conclusions have directly supported the design guidelines of our software solution proposal. In what concerns to methodology, we first review literature on technologies support to emergencies and how spontaneous volunteers actually challenge these systems. Following, we have performed a field research where we have observed that the emerging of spontaneous volunteer’s efforts imposes new requirements for the design of such systems, which leaded to the creation of a cluster of design guidelines that supported our software solution proposal to address the volunteers’ requirements. Finally we have architected and developed an online open information management tool which has been evaluated via usability engineering methods, usability user tests and heuristic evaluations.

Investigation of urinary volatile organic metabolites as potential cancer biomarkers by solid-phase microextraction in combination with gas chromatography-mass spectrometry

BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.