In this task, you are given an abstract of article. Your task is to generate title for this article. Preferred titles are under thirty words.

[EX Q]: OBJECTIVE To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems and spatial scan statistic (SaTScan).
METHODS We obtained BFV disease cases, population and statistical local areas (SLAs) boundary data from Queensland Health and Australian Bureau of Statistics, respectively, during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200 km radius and varying time windows from 1 to 12 months were chosen (for the space-time analysis).
RESULTS The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations.
CONCLUSIONS This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing ongoing surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.
[EX A]: Spatial and temporal clusters of Barmah Forest virus disease in Queensland, Australia.

[EX Q]: The mammalian genome harbors thousands of long noncoding RNA (lncRNA) genes. Recent studies have indicated the involvement of several of these lncRNAs in the regulation of gene expression. lncRNAs play crucial roles in various biological processes ranging from epigenetic gene regulation, transcriptional control, to post-transcriptional regulation. lncRNAs are localized in various subcellular compartments, and major proportion of these are retained in the cell nucleus and could be broadly classified as nuclear-retained lncRNAs (nrRNAs). Based on the identified functions, members of the nrRNAs execute diverse roles, including providing architectural support to the hierarchical subnuclear organization and influencing the recruitment of chromatin modifier factors to specific chromatin sites. In this review, we will summarize the recently described roles of mammalian nrRNAs in controlling gene expression by influencing chromatin organization, transcription, pre-mRNA processing, nuclear organization, and their involvement in disease.
[EX A]: Functional insights into the role of nuclear-retained long noncoding RNAs in gene expression control in mammalian cells

[EX Q]: CONTEXT Health care applications of autoidentification technologies, such as radio frequency identification (RFID), have been proposed to improve patient safety and also the tracking and tracing of medical equipment. However, electromagnetic interference (EMI) by RFID on medical devices has never been reported.
OBJECTIVE To assess and classify incidents of EMI by RFID on critical care equipment.
DESIGN AND SETTING Without a patient being connected, EMI by 2 RFID systems (active 125 kHz and passive 868 MHz) was assessed under controlled conditions during May 2006, in the proximity of 41 medical devices (in 17 categories, 22 different manufacturers) at the Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands. Assessment took place according to an international test protocol. Incidents of EMI were classified according to a critical care adverse events scale as hazardous, significant, or light.
RESULTS In 123 EMI tests (3 per medical device), RFID induced 34 EMI incidents: 22 were classified as hazardous, 2 as significant, and 10 as light. The passive 868-MHz RFID signal induced a higher number of incidents (26 incidents in 41 EMI tests; 63%) compared with the active 125-kHz RFID signal (8 incidents in 41 EMI tests; 20%); difference 44% (95% confidence interval, 27%-53%; P < .001). The passive 868-MHz RFID signal induced EMI in 26 medical devices, including 8 that were also affected by the active 125-kHz RFID signal (26 in 41 devices; 63%). The median distance between the RFID reader and the medical device in all EMI incidents was 30 cm (range, 0.1-600 cm).
CONCLUSIONS In a controlled nonclinical setting, RFID induced potentially hazardous incidents in medical devices. Implementation of RFID in the critical care environment should require on-site EMI tests and updates of international standards.
[EX A]:
Electromagnetic interference from radio frequency identification inducing potentially hazardous incidents in critical care medical equipment.