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A conceptual framework for studying collective reactions to events in location-based social media
Events are a core concept of spatial information, but location-based social media (LBSM) provide information on reactions to events. Individuals have varied degrees of agency in initiating, reacting to or modifying the course of events, and reactions include observations of occurrence, expressions containing sentiment or emotions, or a call to action. Key characteristics of reactions include referent events and information about who reacted, when, where and how. Collective reactions are composed of multiple individual reactions sharing common referents. They can be characterized according to the following dimensions: spatial, temporal, social, thematic and interlinkage. We present a conceptual framework, which allows characterization and comparison of collective reactions. For a thematically well-defined class of event such as storms, we can explore differences and similarities in collective attribution of meaning across space and time. Other events may have very complex spatio-temporal signatures (e.g. political processes such as Brexit or elections), which can be decomposed into series of individual events (e.g. a temporal window around the result of a vote). The purpose of our framework is to explore ways in which collective reactions to events in LBSM can be described and underpin the development of methods for analysing and understanding collective reactions to events
Adaptation of WASH Services Delivery to Climate Change and Other Sources of Risk and Uncertainty
This report urges WASH sector practitioners to take more seriously the threat of climate change and the consequences it could have on their work. By considering climate change within a risk and uncertainty framework, the field can use the multitude of approaches laid out here to adequately protect itself against a range of direct and indirect impacts. Eleven methods and tools for this specific type of risk management are described, including practical advice on how to implement them successfully
Theta synchronization over occipito‐temporal cortices during visual perception of body parts
Categorical clustering in the visual system is thought to have evolved as a function of intrinsic (intra-areal) and extrinsic (interareal) connectivity and experience. In the visual system, the extrastriate body area (EBA), an occipito-temporal region, responds to full body and body part images under the organizational principle of their functional/semantic meaning. Although frequency-specific modulations of neural activity associated with perceptive and cognitive functions are increasingly attracting the interest of neurophysiologists and cognitive neuroscientists, perceiving single body parts with different functional meaning and full body images induces time-frequency modulations over occipito-temporal electrodes are yet to be described. Here, we studied this issue by measuring EEG in participants who passively observed fingers, hands, arms and faceless full body images with four control plant stimuli, each bearing hierarchical analogy with the body stimuli. We confirmed that occipito-temporal electrodes (compatible with the location of EBA) show a larger event-related potential (ERP, N190) for body-related images. Furthermore, we identified a body part-specific (i.e. selective for hands and arms) theta event-related synchronization increase under the same electrodes. This frequency modulation associated with the perception of body effectors over occipito-temporal cortices is in line with recent findings of categorical organization of neural responses to human effectors in the visual system
Assessing, valuing and protecting our environment- is there a statistical challenge to be answered?
This short article describes some of the evolution in environmental regulation, management and monitoring and the information needs, closely aligned to the statistical challenges to deliver the evidence base for change and effect
Outlier detection techniques for wireless sensor networks: A survey
In the field of wireless sensor networks, those measurements that significantly deviate from the normal pattern of sensed data are considered as outliers. The potential sources of outliers include noise and errors, events, and malicious attacks on the network. Traditional outlier detection techniques are not directly applicable to wireless sensor networks due to the nature of sensor data and specific requirements and limitations of the wireless sensor networks. This survey provides a comprehensive overview of existing outlier detection techniques specifically developed for the wireless sensor networks. Additionally, it presents a technique-based taxonomy and a comparative table to be used as a guideline to select a technique suitable for the application at hand based on characteristics such as data type, outlier type, outlier identity, and outlier degree
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