In the aftermath of disasters it is not uncommon for a large number of individuals, ranging from professional technical responders to untrained, albeit well meaning, volunteers, to converge on site of a disaster in order to offer to help victims or other responders. Because volunteers can be both a help and a hindrance in disaster response, they pose a paradox to professional responders at the scene. Through focus group interviews and in-depth structured interviews, this paper presents an extended example of how Urban Search and Rescue (US&R) task forces, a type of professional technical-responder organisation, interact with and utilise volunteers. Findings show that US&R task forces evaluate the volunteers in terms of their presumed legitimacy, utility, and potential liability or danger posed during the disaster response. Other responses to volunteers such as a feeling of powerlessness or the use of volunteers in non-technical ways are also explored. This paper demonstrates some key aspects of the relationship between volunteers and formal response organisations in disasters.

Hurricane Katrina created an unprecedented need for sheltering and temporary housing across a four-state area along the Gulf Coast. This article reviews the disaster literature with respect to sheltering and temporary housing and contrasts how these needs actually developed with respect to both the preimpact and postimpact evacuation situations. The article also investigates the ways that intergovernmental planning failed to anticipate the need for shelter/housing solutions or to implement effective measures to put those plans into operation.

Objective. This article offers a test of the normative explanation of collective behavior by examining the fire at the Station nightclub in Rhode Island that killed 100 and injured nearly 200 persons.Methods. Information on all persons at the club comes from content analysis of documents from the Rhode Island Police Department, the Rhode Island Office of the Attorney General, and The Providence Journal. We use negative binomial regression to test hypotheses about the effects of group-level predictors of the counts of dead and injured in 179 groups at the nightclub.Results. Results indicate that group-level factors such as distance of group members at the start of the fire, the number of intimate relations among them, the extent to which they had visited the nightclub prior to the incident, and the average length of the evacuation route they used predict counts of injured and dead. The research also looks at what behavioral differences exist between survivors and victims, ascertains the existence of role extension among employees of the nightclub, and provides support for the affirmation that dangerous contexts negate the protective influence of intimate relations in groups.Conclusion. We argue for the abandonment of current emphasis on irrationality and herd-like imitative behavior in studies of evacuation from structural fires in buildings and for the inclusion of group-level processes in social psychological explanations of these incidents.

Bioassay-guided fractionation of extracts from a Fijian red alga in the genus Callophycus resulted in the isolation of five new compounds of the diterpene-benzoate class. Bromophycoic acids A-E (1–5) were characterized by NMR and mass spectroscopic analyses and represent two novel carbon skeletons, one with an unusual proposed biosynthesis. These compounds display a range of activities against human tumor cell lines, malarial parasite, and bacterial pathogens including low micromolar suppression of MRSA and VREF.

We introduce new dynamic set intersection data structures, which we call 2-3 cuckoo filters and hash tables. These structures differ from the standard cuckoo hash tables and cuckoo filters in that they choose two out of three locations to store each item, instead of one out of two, ensuring that any item in an intersection of two structures will have at least one common location in both structures. We demonstrate the utility of these structures by using them in improved algorithms for listing triangles and answering set intersection queries in internal or external memory. For a graph G of n vertices and m edges, our internal-memory triangle listing algorithm runs in O(m (α(G) log w)/w + k) expected time, where α(G) is the arboricity of G, w is the number of bits in a machine word, and k is the number of output triangles. Our external-memory algorithm uses O(sort(n α(G)) + sort(m (α(G) log w)/w) + sort(k)) expected number of I/Os.